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Applications

OpenShift Container Platform 4.1

Creating and managing applications on OpenShift Container Platform 4.1

Red Hat OpenShift Documentation Team

Abstract

This document provides instructions for the various ways to create and manage instances of user-provisioned applications running on OpenShift Container Platform. It introduces concepts and tasks related to building applications using the Operator Framework, as well as provisioning applications using the Open Service Broker API.

Chapter 1. Projects

1.1. Working with projects

A project allows a community of users to organize and manage their content in isolation from other communities.

1.1.1. Creating a project using the web console

If allowed by your cluster administrator, you can create a new project.

Procedure

  1. Navigate to HomeProjects.
  2. Click Create Project.
  3. Enter your project details.
  4. Click Create.

1.1.2. Creating a project using the CLI

If allowed by your cluster administrator, you can create a new project.

Procedure

  1. Run:
$ oc new-project <project_name> \
    --description="<description>" --display-name="<display_name>"

For example:

$ oc new-project hello-openshift \
    --description="This is an example project" \
    --display-name="Hello OpenShift"
Note

The number of projects you are allowed to create may be limited by the system administrator. After your limit is reached, you might have to delete an existing project in order to create a new one.

1.1.3. Viewing a project using the web console

Procedure

  1. Navigate to HomeProjects.
  2. Select a project to view.

    On this page, click the Resources button to see workloads in the project and click the Dashboard button to see metrics and details about the project.

1.1.4. Viewing a project using the CLI

When viewing projects, you are restricted to seeing only the projects you have access to view based on the authorization policy.

Procedure

  1. To view a list of projects, run:

    $ oc get projects
  2. You can change from the current project to a different project for CLI operations. The specified project is then used in all subsequent operations that manipulate project-scoped content:

    $ oc project <project_name>

1.1.5. Adding to a project

Procedure

  1. Navigate to HomeProjects.
  2. Select a project.
  3. In the upper right-hand corner of the Project Status menu, click Add, then choose from the provided options.

1.1.6. Checking project status using the web console

Procedure

  1. Navigate to HomeProjects.
  2. Select a project to see its status.

1.1.7. Checking project status using the CLI

Procedure

  1. Run:

    $ oc status

    This command provides a high-level overview of the current project, with its components and their relationships.

1.1.8. Deleting a project using the web console

Procedure

  1. Navigate to HomeProjects.
  2. Locate the project that you want to delete from the list of projects.
  3. On the far right side of the project listing, select Delete Project from the menu. If you do not have permissions to delete the project, the Delete Project option is grayed out and the option is not clickable.

1.1.9. Deleting a project using the CLI

When you delete a project, the server updates the project status to Terminating from Active. Then, the server clears all content from a project that is in the Terminating state before finally removing the project. While a project is in Terminating status, you cannot add new content to the project. Projects can be deleted from the CLI or the web console.

Procedure

  1. Run:

    $ oc delete project <project_name>

1.2. Creating a project as another user

Impersonation allows you to create a project as a different user.

1.2.1. API impersonation

A request to the OpenShift Container Platform API can include an Impersonate-User header, which indicates that the requester wants the request handled as though it came from the specified user.

Before User A can impersonate User B, User A is authenticated. Then, an authorization check occurs to ensure that User A is allowed to impersonate the user named User B. If User A is requesting to impersonate a service account, system:serviceaccount:namespace:name, OpenShift Container Platform confirms that User A can impersonate the serviceaccount named name in namespace. If the check fails, the request fails with a 403 (Forbidden) error code.

By default, project administrators and editors can impersonate service accounts in their namespace. The sudoers role allows a user to impersonate system:admin, which in turn has cluster administrator permissions. The ability to impersonate system:admin grants some protection against typos, but not security, for someone administering the cluster. For example, running oc delete nodes --all fails, but running oc delete nodes --all --as=system:admin succeeds.

1.2.2. Impersonating a user when you create a project

You can impersonate a different user when you create a project request. Because system:authenticated:oauth is the only bootstrap group that can create project requests, you must impersonate that group.

Procedure

  • To create a project request on behalf of a different user:

    $ oc new-project <project> --as=<user> \
        --as-group=system:authenticated --as-group=system:authenticated:oauth

1.3. Configuring project creation

In OpenShift Container Platform, projects are used to group and isolate related objects. When a request is made to create a new project using the web console or oc new-project command, an endpoint in OpenShift Container Platform is used to provision the project according to a template, which can be customized.

As a cluster administrator, you can allow and configure how developers and service accounts can create, or self-provision, their own projects.

1.3.1. About project creation

The OpenShift Container Platform API server automatically provisions new projects based on the project template that is identified by the projectRequestTemplate parameter in the cluster’s project configuration resource. If the parameter is not defined, the API server creates a default template that creates a project with the requested name, and assigns the requesting user to the admin role for that project.

When a project request is submitted, the API substitutes the following parameters into the template:

Table 1.1. Default project template parameters

ParameterDescription

PROJECT_NAME

The name of the project. Required.

PROJECT_DISPLAYNAME

The display name of the project. May be empty.

PROJECT_DESCRIPTION

The description of the project. May be empty.

PROJECT_ADMIN_USER

The user name of the administrating user.

PROJECT_REQUESTING_USER

The user name of the requesting user.

Access to the API is granted to developers with the self-provisioner role and the self-provisioners cluster role binding. This role is available to all authenticated developers by default.

1.3.2. Modifying the template for new projects

As a cluster administrator, you can modify the default project template so that new projects are created using your custom requirements.

To create your own custom project template:

Procedure

  1. Log in as a user with cluster-admin privileges.
  2. Generate the default project template:

    $ oc adm create-bootstrap-project-template -o yaml > template.yaml
  3. Use a text editor to modify the generated template.yaml file by adding objects or modifying existing objects.
  4. The project template must be created in the openshift-config namespace. Load your modified template:

    $ oc create -f template.yaml -n openshift-config
  5. Edit the project configuration resource using the web console or CLI.

    • Using the web console:

      1. Navigate to the AdministrationCluster Settings page.
      2. Click Global Configuration to view all configuration resources.
      3. Find the entry for Project and click Edit YAML.
    • Using the CLI:

      1. Edit the project.config.openshift.io/cluster resource:

        $ oc edit project.config.openshift.io/cluster
  6. Update the spec section to include the projectRequestTemplate and name parameters, and set the name of your uploaded project template. The default name is project-request.

    Project configuration resource with custom project template

    apiVersion: config.openshift.io/v1
    kind: Project
    metadata:
      ...
    spec:
      projectRequestTemplate:
        name: <template_name>

  7. After you save your changes, create a new project to verify that your changes were successfully applied.

1.3.3. Disabling project self-provisioning

You can prevent an authenticated user group from self-provisioning new projects.

Procedure

  1. Log in as a user with cluster-admin privileges.
  2. View the self-provisioners cluster role binding usage by running the following command:

    $ oc describe clusterrolebinding.rbac self-provisioners
    
    Name:		self-provisioners
    Labels:		<none>
    Annotations:	rbac.authorization.kubernetes.io/autoupdate=true
    Role:
      Kind:	ClusterRole
      Name:	self-provisioner
    Subjects:
      Kind	Name				Namespace
      ----	----				---------
      Group	system:authenticated:oauth

    Review the subjects in the self-provisioners section.

  3. Remove the self-provisioner cluster role from the group system:authenticated:oauth.

    • If the self-provisioners cluster role binding binds only the self-provisioner role to the system:authenticated:oauth group, run the following command:

      $ oc patch clusterrolebinding.rbac self-provisioners -p '{"subjects": null}'
    • If the self-provisioners cluster role binding binds the self-provisioner role to more users, groups, or service accounts than the system:authenticated:oauth group, run the following command:

      $ oc adm policy \
          remove-cluster-role-from-group self-provisioner \
          system:authenticated:oauth
  4. Edit the self-provisioners cluster role binding to prevent automatic updates to the role. Automatic updates reset the cluster roles to the default state.

    • To update the role binding using the CLI:

      1. Run the following command:

        $ oc edit clusterrolebinding.rbac self-provisioners
      2. In the displayed role binding, set the rbac.authorization.kubernetes.io/autoupdate parameter value to false, as shown in the following example:

        apiVersion: authorization.openshift.io/v1
        kind: ClusterRoleBinding
        metadata:
          annotations:
            rbac.authorization.kubernetes.io/autoupdate: "false"
          ...
    • To update the role binding by using a single command:

      $ oc patch clusterrolebinding.rbac self-provisioners -p '{ "metadata": { "annotations": { "rbac.authorization.kubernetes.io/autoupdate": "false" } } }'
  5. Login as an authenticated user and verify that it can no longer self-provision a project:

    $ oc new-project test
    
    Error from server (Forbidden): You may not request a new project via this API.

    Consider customizing this project request message to provide more helpful instructions specific to your organization.

1.3.4. Customizing the project request message

When a developer or a service account that is unable to self-provision projects makes a project creation request using the web console or CLI, the following error message is returned by default:

You may not request a new project via this API.

Cluster administrators can customize this message. Consider updating it to provide further instructions on how to request a new project specific to your organization. For example:

  • To request a project, contact your system administrator at projectname@example.com.
  • To request a new project, fill out the project request form located at https://internal.example.com/openshift-project-request.

To customize the project request message:

Procedure

  1. Edit the project configuration resource using the web console or CLI.

    • Using the web console:

      1. Navigate to the AdministrationCluster Settings page.
      2. Click Global Configuration to view all configuration resources.
      3. Find the entry for Project and click Edit YAML.
    • Using the CLI:

      1. Log in as a user with cluster-admin privileges.
      2. Edit the project.config.openshift.io/cluster resource:

        $ oc edit project.config.openshift.io/cluster
  2. Update the spec section to include the projectRequestMessage parameter and set the value to your custom message:

    Project configuration resource with custom project request message

    apiVersion: config.openshift.io/v1
    kind: Project
    metadata:
      ...
    spec:
      projectRequestMessage: <message_string>

    For example:

    apiVersion: config.openshift.io/v1
    kind: Project
    metadata:
      ...
    spec:
      projectRequestMessage: To request a project, contact your system administrator at projectname@example.com.
  3. After you save your changes, attempt to create a new project as a developer or service account that is unable to self-provision projects to verify that your changes were successfully applied.

Chapter 2. Operators

2.1. Understanding Operators

Conceptually, Operators take human operational knowledge and encode it into software that is more easily shared with consumers.

Operators are pieces of software that ease the operational complexity of running another piece of software. They act like an extension of the software vendor’s engineering team, watching over a Kubernetes environment (such as OpenShift Container Platform) and using its current state to make decisions in real time. Advanced Operators are designed to handle upgrades seamlessly, react to failures automatically, and not take shortcuts, like skipping a software backup process to save time.

More technically, Operators are a method of packaging, deploying, and managing a Kubernetes application.

A Kubernetes application is an app that is both deployed on Kubernetes and managed using the Kubernetes APIs and kubectl or oc tooling. To be able to make the most of Kubernetes, you require a set of cohesive APIs to extend in order to service and manage your apps that run on Kubernetes. Think of Operators as the runtime that manages this type of app on Kubernetes.

2.1.1. Why use Operators?

Operators provide:

  • Repeatability of installation and upgrade.
  • Constant health checks of every system component.
  • Over-the-air (OTA) updates for OpenShift components and ISV content.
  • A place to encapsulate knowledge from field engineers and spread it to all users, not just one or two.
Why deploy on Kubernetes?
Kubernetes (and by extension, OpenShift Container Platform) contains all of the primitives needed to build complex distributed systems – secret handling, load balancing, service discovery, autoscaling – that work across on-premise and cloud providers.
Why manage your app with Kubernetes APIs and kubectl tooling?
These APIs are feature rich, have clients for all platforms and plug into the cluster’s access control/auditing. An Operator uses the Kubernetes' extension mechanism, Custom Resource Definitions (CRDs), so your custom object, for example MongoDB, looks and acts just like the built-in, native Kubernetes objects.
How do Operators compare with Service Brokers?
A Service Broker is a step towards programmatic discovery and deployment of an app. However, because it is not a long running process, it cannot execute Day 2 operations like upgrade, failover, or scaling. Customizations and parameterization of tunables are provided at install time, versus an Operator that is constantly watching your cluster’s current state. Off-cluster services continue to be a good match for a Service Broker, although Operators exist for these as well.

2.1.2. Operator Framework

The Operator Framework is a family of tools and capabilities to deliver on the customer experience described above. It is not just about writing code; testing, delivering, and updating Operators is just as important. The Operator Framework components consist of open source tools to tackle these problems:

Operator SDK
Assists Operator authors in bootstrapping, building, testing, and packaging their own Operator based on their expertise without requiring knowledge of Kubernetes API complexities.
Operator Lifecycle Manager
Controls the installation, upgrade, and role-based access control (RBAC) of Operators in a cluster. Deployed by default in OpenShift Container Platform 4.1.
Operator Metering
Collects operational metrics about Operators on the cluster for Day 2 management and aggregating usage metrics.
OperatorHub
Web console for discovering and installing Operators on your cluster. Deployed by default in OpenShift Container Platform 4.1.

These tools are designed to be composable, so you can use any that are useful to you.

2.1.3. Operator maturity model

The level of sophistication of the management logic encapsulated within an Operator can vary. This logic is also in general highly dependent on the type of the service represented by the Operator.

One can however generalize the scale of the maturity of an Operator’s encapsulated operations for certain set of capabilities that most Operators can include. To this end, the following Operator Maturity model defines five phases of maturity for generic day two operations of an Operator:

Figure 2.1. Operator maturity model

operator maturity model

The above model also shows how these capabilities can best be developed through the Operator Framework’s Helm, Go, and Ansible capabilities.

2.2. Understanding the Operator Lifecycle Manager

This guide outlines the workflow and architecture of the Operator Lifecycle Manager (OLM) in OpenShift Container Platform.

2.2.1. Overview of the Operator Lifecycle Manager

In OpenShift Container Platform 4.1, the Operator Lifecycle Manager (OLM) helps users install, update, and manage the lifecycle of all Operators and their associated services running across their clusters. It is part of the Operator Framework, an open source toolkit designed to manage Kubernetes native applications (Operators) in an effective, automated, and scalable way.

Figure 2.2. Operator Lifecycle Manager workflow

olm workflow

The OLM runs by default in OpenShift Container Platform 4.1, which aids cluster administrators in installing, upgrading, and granting access to Operators running on their cluster. The OpenShift Container Platform web console provides management screens for cluster administrators to install Operators, as well as grant specific projects access to use the catalog of Operators available on the cluster.

For developers, a self-service experience allows provisioning and configuring instances of databases, monitoring, and big data services without having to be subject matter experts, because the Operator has that knowledge baked into it.

2.2.2. ClusterServiceVersions (CSVs)

A ClusterServiceVersion (CSV) is a YAML manifest created from Operator metadata that assists the Operator Lifecycle Manager (OLM) in running the Operator in a cluster. It is the metadata that accompanies an Operator container image, used to populate user interfaces with information like its logo, description, and version. It is also a source of technical information needed to run the Operator, like the RBAC rules it requires and which Custom Resources (CRs) it manages or depends on.

A CSV is composed of:

Metadata
  • Application metadata:

    • Name, description, version (semver compliant), links, labels, icon, etc.
Install strategy
  • Type: Deployment

    • Set of service accounts and required permissions
    • Set of Deployments.
Custom Resource Definitions (CRDs)
  • Type
  • Owned: Managed by this service
  • Required: Must exist in the cluster for this service to run
  • Resources: A list of resources that the Operator interacts with
  • Descriptors: Annotate CRD spec and status fields to provide semantic information

2.2.3. Operator Lifecycle Manager architecture

The Operator Lifecycle Manager (OLM) is composed of two Operators: the OLM Operator and the Catalog Operator.

Each of these Operators are responsible for managing the Custom Resource Definitions (CRDs) that are the basis for the OLM framework:

Table 2.1. CRDs managed by OLM and Catalog Operators

ResourceShort nameOwnerDescription

ClusterServiceVersion

csv

OLM

Application metadata: name, version, icon, required resources, installation, etc.

InstallPlan

ip

Catalog

Calculated list of resources to be created in order to automatically install or upgrade a CSV.

CatalogSource

catsrc

Catalog

A repository of CSVs, CRDs, and packages that define an application.

Subscription

sub

Catalog

Keeps CSVs up to date by tracking a channel in a package.

OperatorGroup

og

OLM

Configures all Operators deployed in the same namespace as the OperatorGroup object to watch for their Custom Resource (CR) in a list of namespaces or cluster-wide.

Each of these Operators are also responsible for creating resources:

Table 2.2. Resources created by OLM and Catalog Operators

ResourceOwner

Deployments

OLM

ServiceAccounts

(Cluster)Roles

(Cluster)RoleBindings

Custom Resource Definitions (CRDs)

Catalog

ClusterServiceVersions (CSVs)

2.2.3.1. OLM Operator

The OLM Operator is responsible for deploying applications defined by CSV resources after the required resources specified in the CSV are present in the cluster.

The OLM Operator is not concerned with the creation of the required resources; users can choose to manually create these resources using the CLI, or users can choose to create these resources using the Catalog Operator. This separation of concern enables users incremental buy-in in terms of how much of the OLM framework they choose to leverage for their application.

While the OLM Operator is often configured to watch all namespaces, it can also be operated alongside other OLM Operators so long as they all manage separate namespaces.

OLM Operator workflow

  • Watches for ClusterServiceVersion (CSVs) in a namespace and checks that requirements are met. If so, runs the install strategy for the CSV.

    Note

    A CSV must be an active member of an OperatorGroup in order for the install strategy to be run.

2.2.3.2. Catalog Operator

The Catalog Operator is responsible for resolving and installing CSVs and the required resources they specify. It is also responsible for watching CatalogSources for updates to packages in channels and upgrading them (optionally automatically) to the latest available versions.

A user that wishes to track a package in a channel creates a Subscription resource configuring the desired package, channel, and the CatalogSource from which to pull updates. When updates are found, an appropriate InstallPlan is written into the namespace on behalf of the user.

Users can also create an InstallPlan resource directly, containing the names of the desired CSV and an approval strategy, and the Catalog Operator creates an execution plan for the creation of all of the required resources. After it is approved, the Catalog Operator creates all of the resources in an InstallPlan; this then independently satisfies the OLM Operator, which proceeds to install the CSVs.

Catalog Operator workflow

  • Has a cache of CRDs and CSVs, indexed by name.
  • Watches for unresolved InstallPlans created by a user:

    • Finds the CSV matching the name requested and adds it as a resolved resource.
    • For each managed or required CRD, adds it as a resolved resource.
    • For each required CRD, finds the CSV that manages it.
  • Watches for resolved InstallPlans and creates all of the discovered resources for it (if approved by a user or automatically).
  • Watches for CatalogSources and Subscriptions and creates InstallPlans based on them.

2.2.3.3. Catalog Registry

The Catalog Registry stores CSVs and CRDs for creation in a cluster and stores metadata about packages and channels.

A package manifest is an entry in the Catalog Registry that associates a package identity with sets of CSVs. Within a package, channels point to a particular CSV. Because CSVs explicitly reference the CSV that they replace, a package manifest provides the Catalog Operator all of the information that is required to update a CSV to the latest version in a channel (stepping through each intermediate version).

2.2.4. OperatorGroups

An OperatorGroup is an OLM resource that provides multitenant configuration to OLM-installed Operators. An OperatorGroup selects a set of target namespaces in which to generate required RBAC access for its member Operators. The set of target namespaces is provided by a comma-delimited string stored in the CSV’s olm.targetNamespaces annotation. This annotation is applied to member Operator’s CSV instances and is projected into their deployments.

2.2.4.1. OperatorGroup membership

An Operator is considered a member of an OperatorGroup if the following conditions are true:

  • The Operator’s CSV exists in the same namespace as the OperatorGroup.
  • The Operator’s CSV’s InstallModes support the set of namespaces targeted by the OperatorGroup.

An InstallMode consists of an InstallModeType field and a boolean Supported field. A CSV’s spec can contain a set of InstallModes of four distinct InstallModeTypes:

Table 2.3. InstallModes and supported OperatorGroups

InstallModeTypeDescription

OwnNamespace

The Operator can be a member of an OperatorGroup that selects its own namespace.

SingleNamespace

The Operator can be a member of an OperatorGroup that selects one namespace.

MultiNamespace

The Operator can be a member of an OperatorGroup that selects more than one namespace.

AllNamespaces

The Operator can be a member of an OperatorGroup that selects all namespaces (target namespace set is the empty string "").

Note

If a CSV’s spec omits an entry of InstallModeType, then that type is considered unsupported unless support can be inferred by an existing entry that implicitly supports it.

2.2.4.1.1. Troubleshooting OperatorGroup membership
  • If more than one OperatorGroup exists in a single namespace, any CSV created in that namespace will transition to a failure state with the reason TooManyOperatorGroups. CSVs in a failed state for this reason will transition to pending once the number of OperatorGroups in their namespaces reaches one.
  • If a CSV’s InstallModes do not support the target namespace selection of the OperatorGroup in its namespace, the CSV will transition to a failure state with the reason UnsupportedOperatorGroup. CSVs in a failed state for this reason will transition to pending once either the OperatorGroup’s target namespace selection changes to a supported configuration, or the CSV’s InstallModes are modified to support the OperatorGroup’s target namespace selection.

2.2.4.2. Target namespace selection

Specify the set of namespaces for the OperatorGroup using a label selector with the spec.selector field:

apiVersion: operators.coreos.com/v1alpha2
kind: OperatorGroup
metadata:
  name: my-group
  namespace: my-namespace
  spec:
    selector:
      matchLabels:
        cool.io/prod: "true"

You can also explicitly name the target namespaces using the spec.targetNamespaces field:

apiVersion: operators.coreos.com/v1alpha2
kind: OperatorGroup
metadata:
  name: my-group
  namespace: my-namespace
spec:
  targetNamespaces:
  - my-namespace
  - my-other-namespace
  - my-other-other-namespace
Note

If both spec.targetNamespaces and spec.selector are defined, spec.selector is ignored.

Alternatively, you can omit both spec.selector and spec.targetNamespaces to specify a global OperatorGroup, which selects all namespaces:

apiVersion: operators.coreos.com/v1alpha2
kind: OperatorGroup
metadata:
  name: my-group
  namespace: my-namespace

The resolved set of selected namespaces is shown in an OperatorGroup’s status.namespaces field. A global OperatorGroup’s status.namespace contains the empty string (""), which signals to a consuming Operator that it should watch all namespaces.

2.2.4.3. OperatorGroup CSV annotations

Member CSVs of an OperatorGroup have the following annotations:

AnnotationDescription

olm.operatorGroup=<group_name>

Contains the name of the OperatorGroup.

olm.operatorGroupNamespace=<group_namespace>

Contains the namespace of the OperatorGroup.

olm.targetNamespaces=<target_namespaces>

Contains a comma-delimited string that lists the OperatorGroup’s target namespace selection.

Note

All annotations except olm.targetNamespaces are included with copied CSVs. Omitting the olm.targetNamespaces annotation on copied CSVs prevents the duplication of target namespaces between tenants.

2.2.4.4. Provided APIs annotation

Information about what GroupVersionKinds (GVKs) are provided by an OperatorGroup are shown in an olm.providedAPIs annotation. The annotation’s value is a string consisting of <kind>.<version>.<group> delimited with commas. The GVKs of CRDs and APIServices provided by all active member CSVs of an OperatorGroup are included.

Review the following example of an OperatorGroup with a single active member CSV that provides the PackageManifest resource:

apiVersion: operators.coreos.com/v1alpha2
kind: OperatorGroup
metadata:
  annotations:
    olm.providedAPIs: PackageManifest.v1alpha1.packages.apps.redhat.com
  name: olm-operators
  namespace: local
  ...
spec:
  selector: {}
  serviceAccount:
    metadata:
      creationTimestamp: null
  targetNamespaces:
  - local
status:
  lastUpdated: 2019-02-19T16:18:28Z
  namespaces:
  - local

2.2.4.5. Role-based access control

When an OperatorGroup is created, three ClusterRoles are generated. Each contains a single AggregationRule with a ClusterRoleSelector set to match a label, as shown below:

ClusterRoleLabel to match

<operatorgroup_name>-admin

olm.opgroup.permissions/aggregate-to-admin: <operatorgroup_name>

<operatorgroup_name>-edit

olm.opgroup.permissions/aggregate-to-edit: <operatorgroup_name>

<operatorgroup_name>-view

olm.opgroup.permissions/aggregate-to-view: <operatorgroup_name>

The following RBAC resources are generated when a CSV becomes an active member of an OperatorGroup, as long as the CSV is watching all namespaces with the AllNamespaces InstallMode and is not in a failed state with reason InterOperatorGroupOwnerConflict.

Table 2.4. ClusterRoles generated for each API resource from a CRD

ClusterRoleSettings

<kind>.<group>-<version>-admin

Verbs on <kind>:

  • *

Aggregation labels:

  • rbac.authorization.k8s.io/aggregate-to-admin: true
  • olm.opgroup.permissions/aggregate-to-admin: <operatorgroup_name>

<kind>.<group>-<version>-edit

Verbs on <kind>:

  • create
  • update
  • patch
  • delete

Aggregation labels:

  • rbac.authorization.k8s.io/aggregate-to-edit: true
  • olm.opgroup.permissions/aggregate-to-edit: <operatorgroup_name>

<kind>.<group>-<version>-view

Verbs on <kind>:

  • get
  • list
  • watch

Aggregation labels:

  • rbac.authorization.k8s.io/aggregate-to-view: true
  • olm.opgroup.permissions/aggregate-to-view: <operatorgroup_name>

<kind>.<group>-<version>-view-crdview

Verbs on apiextensions.k8s.io customresourcedefinitions <crd-name>:

  • get

Aggregation labels:

  • rbac.authorization.k8s.io/aggregate-to-view: true
  • olm.opgroup.permissions/aggregate-to-view: <operatorgroup_name>

Table 2.5. ClusterRoles generated for each API resource from an APIService

ClusterRoleSettings

<kind>.<group>-<version>-admin

Verbs on <kind>:

  • *

Aggregation labels:

  • rbac.authorization.k8s.io/aggregate-to-admin: true
  • olm.opgroup.permissions/aggregate-to-admin: <operatorgroup_name>

<kind>.<group>-<version>-edit

Verbs on <kind>:

  • create
  • update
  • patch
  • delete

Aggregation labels:

  • rbac.authorization.k8s.io/aggregate-to-edit: true
  • olm.opgroup.permissions/aggregate-to-edit: <operatorgroup_name>

<kind>.<group>-<version>-view

Verbs on <kind>:

  • get
  • list
  • watch

Aggregation labels:

  • rbac.authorization.k8s.io/aggregate-to-view: true
  • olm.opgroup.permissions/aggregate-to-view: <operatorgroup_name>

Additional Roles and RoleBindings

  • If the CSV defines exactly one target namespace that contains *, then a ClusterRole and corresponding ClusterRoleBinding are generated for each permission defined in the CSV’s permissions field. All resources generated are given the olm.owner: <csv_name> and olm.owner.namespace: <csv_namespace> labels.
  • If the CSV does not define exactly one target namespace that contains *, then all Roles and RoleBindings in the Operator namespace with the olm.owner: <csv_name> and olm.owner.namespace: <csv_namespace> labels are copied into the target namespace.

2.2.4.6. Copied CSVs

OLM creates copies of all active member CSVs of an OperatorGroup in each of that OperatorGroup’s target namespaces. The purpose of a copied CSV is to tell users of a target namespace that a specific Operator is configured to watch resources created there. Copied CSVs have a status reason Copied and are updated to match the status of their source CSV. The olm.targetNamespaces annotation is stripped from copied CSVs before they are created on the cluster. Omitting the target namespace selection avoids the duplication of target namespaces between tenants. Copied CSVs are deleted when their source CSV no longer exists or the OperatorGroup that their source CSV belongs to no longer targets the copied CSV’s namespace.

2.2.4.7. Static OperatorGroups

An OperatorGroup is static if its spec.staticProvidedAPIs field is set to true. As a result, OLM does not modify the OperatorGroup’s olm.providedAPIs annotation, which means that it can be set in advance. This is useful when a user wants to use an OperatorGroup to prevent resource contention in a set of namespaces but does not have active member CSVs that provide the APIs for those resources.

Below is an example of an OperatorGroup that protects Prometheus resources in all namespaces with the something.cool.io/cluster-monitoring: "true" annotation:

apiVersion: operators.coreos.com/v1alpha2
kind: OperatorGroup
metadata:
  name: cluster-monitoring
  namespace: cluster-monitoring
  annotations:
    olm.providedAPIs: Alertmanager.v1.monitoring.coreos.com,Prometheus.v1.monitoring.coreos.com,PrometheusRule.v1.monitoring.coreos.com,ServiceMonitor.v1.monitoring.coreos.com
spec:
  staticProvidedAPIs: true
  selector:
    matchLabels:
      something.cool.io/cluster-monitoring: "true"

2.2.4.8. OperatorGroup intersection

Two OperatorGroups are said to have intersecting provided APIs if the intersection of their target namespace sets is not an empty set and the intersection of their provided API sets, defined by olm.providedAPIs annotations, is not an empty set.

A potential issue is that OperatorGroups with intersecting provided APIs can compete for the same resources in the set of intersecting namespaces.

Note

When checking intersection rules, an OperatorGroup’s namespace is always included as part of its selected target namespaces.

2.2.4.8.1. Rules for intersection

Each time an active member CSV synchronizes, OLM queries the cluster for the set of intersecting provided APIs between the CSV’s OperatorGroup and all others. OLM then checks if that set is an empty set:

  • If true and the CSV’s provided APIs are a subset of the OperatorGroup’s:

    • Continue transitioning.
  • If true and the CSV’s provided APIs are not a subset of the OperatorGroup’s:

    • If the OperatorGroup is static:

      • Clean up any deployments that belong to the CSV.
      • Transition the CSV to a failed state with status reason CannotModifyStaticOperatorGroupProvidedAPIs.
    • If the OperatorGroup is not static:

      • Replace the OperatorGroup’s olm.providedAPIs annotation with the union of itself and the CSV’s provided APIs.
  • If false and the CSV’s provided APIs are not a subset of the OperatorGroup’s:

    • Clean up any deployments that belong to the CSV.
    • Transition the CSV to a failed state with status reason InterOperatorGroupOwnerConflict.
  • If false and the CSV’s provided APIs are a subset of the OperatorGroup’s:

    • If the OperatorGroup is static:

      • Clean up any deployments that belong to the CSV.
      • Transition the CSV to a failed state with status reason CannotModifyStaticOperatorGroupProvidedAPIs.
    • If the OperatorGroup is not static:

      • Replace the OperatorGroup’s olm.providedAPIs annotation with the difference between itself and the CSV’s provided APIs.
Note

Failure states caused by OperatorGroups are non-terminal.

The following actions are performed each time an OperatorGroup synchronizes:

  • The set of provided APIs from active member CSVs is calculated from the cluster. Note that copied CSVs are ignored.
  • The cluster set is compared to olm.providedAPIs, and if olm.providedAPIs contains any extra APIs, then those APIs are pruned.
  • All CSVs that provide the same APIs across all namespaces are requeued. This notifies conflicting CSVs in intersecting groups that their conflict has possibly been resolved, either through resizing or through deletion of the conflicting CSV.

2.2.5. Metrics

The OLM exposes certain OLM-specific resources for use by the Prometheus-based OpenShift Container Platform cluster monitoring stack.

Table 2.6. Metrics exposed by OLM

NameDescription

csv_count

Number of CSVs successfully registered.

install_plan_count

Number of InstallPlans.

subscription_count

Number of Subscriptions.

csv_upgrade_count

Monotonic count of CatalogSources.

2.3. Understanding the OperatorHub

This guide outlines the architecture of the OperatorHub.

2.3.1. Overview of the OperatorHub

The OperatorHub is available via the OpenShift Container Platform web console and is the interface that cluster administrators use to discover and install Operators. With one click, an Operator can be pulled from their off-cluster source, installed and subscribed on the cluster, and made ready for engineering teams to self-service manage the product across deployment environments using the Operator Lifecycle Manager (OLM).

Cluster administrators can choose from OperatorSources grouped into the following categories:

CategoryDescription

Red Hat Operators

Red Hat products packaged and shipped by Red Hat. Supported by Red Hat.

Certified Operators

Products from leading independent software vendors (ISVs). Red Hat partners with ISVs to package and ship. Supported by the ISV.

Community Operators

Optionally-visible software maintained by relevant representatives in the operator-framework/community-operators GitHub repository. No official support.

Custom Operators

Operators you add to the cluster yourself. If you have not added any Custom Operators, the Custom category does not appear in the Web console on your OperatorHub.

The OperatorHub component is installed and run as an Operator by default on OpenShift Container Platform in the openshift-marketplace namespace.

2.3.2. OperatorHub architecture

The OperatorHub component’s Operator manages two Custom Resource Definitions (CRDs): an OperatorSource and a CatalogSourceConfig.

Note

Although some OperatorSource and CatalogSourceConfig information is exposed through the OperatorHub user interface, those files are only used directly by those who are creating their own Operators.

2.3.2.1. OperatorSource

For each Operator, the OperatorSource is used to define the external data store used to store Operator bundles. A simple OperatorSource includes:

FieldDescription

type

To identify the data store as an application registry, type is set to appregistry.

endpoint

Currently, Quay is the external data store used by the OperatorHub, so the endpoint is set to https://quay.io/cnr for the Quay.io appregistry.

registryNamespace

For a Community Operator, this is set to community-operator.

displayName

Optionally set to a name that appears in the OperatorHub user interface for the Operator.

publisher

Optionally set to the person or organization publishing the Operator, so it can be displayed on the OperatorHub.

2.3.2.2. CatalogSourceConfig

An Operator’s CatalogSourceConfig is used to enable an Operator present in the OperatorSource on the cluster.

A simple CatalogSourceConfig must identify:

FieldDescription

targetNamespace

The location where the Operator would be deployed and updated, such as openshift-operators. This is a namespace that the OLM watches.

packages

A comma-separated list of packages that make up the content of the Operator.

2.4. Adding Operators to a cluster

This guide walks cluster administrators through installing Operators to an OpenShift Container Platform cluster.

2.4.1. Installing Operators from the OperatorHub

As a cluster administrator, you can install an Operator from the OperatorHub using the OpenShift Container Platform web console or the CLI. You can then subscribe the Operator to one or more namespaces to make it available for developers on your cluster.

During installation, you must determine the following initial settings for the Operator:

Installation Mode
Choose All namespaces on the cluster (default) to have the Operator installed on all namespaces or choose individual namespaces, if available, to only install the Operator on selected namespaces. This example chooses All namespaces…​ to make the Operator available to all users and projects.
Update Channel
If an Operator is available through multiple channels, you can choose which channel you want to subscribe to. For example, to deploy from the stable channel, if available, select it from the list.
Approval Strategy
You can choose Automatic or Manual updates. If you choose Automatic updates for an installed Operator, when a new version of that Operator is available, the Operator Lifecycle Manager (OLM) automatically upgrades the running instance of your Operator without human intervention. If you select Manual updates, when a newer version of an Operator is available, the OLM creates an update request. As a cluster administrator, you must then manually approve that update request to have the Operator updated to the new version.

2.4.1.1. Installing from the OperatorHub using the web console

This procedure uses the Couchbase Operator as an example to install and subscribe to an Operator from the OperatorHub using the OpenShift Container Platform web console.

Prerequisites

  • Access to an OpenShift Container Platform cluster using an account with cluster-admin permissions.

Procedure

  1. Navigate in the web console to the Catalog → OperatorHub page.
  2. Scroll or type a keyword into the Filter by keyword box (in this case, Couchbase) to find the Operator you want.

    Figure 2.3. Filter Operators by keyword

    olm operatorhub
  3. Select the Operator. For a Community Operator, you are warned that Red Hat does not certify those Operators. You must acknowledge that warning before continuing. Information about the Operator is displayed.
  4. Read the information about the Operator and click Install.
  5. On the Create Operator Subscription page:

    1. Select one of the following:

      • All namespaces on the cluster (default) installs the Operator in the default openshift-operators namespace to watch and be made available to all namespaces in the cluster. This option is not always available.
      • A specific namespace on the cluster allows you to choose a specific, single namespace in which to install the Operator. The Operator will only watch and be made available for use in this single namespace.
    2. Select an Update Channel (if more than one is available).
    3. Select Automatic or Manual approval strategy, as described earlier.
  6. Click Subscribe to make the Operator available to the selected namespaces on this OpenShift Container Platform cluster.
  7. From the Catalog → Operator Management page, you can monitor an Operator Subscription’s installation and upgrade progress.

    1. If you selected a Manual approval strategy, the Subscription’s upgrade status will remain Upgrading until you review and approve its Install Plan.

      Figure 2.4. Manually approving from the Install Plan page

      olm manualapproval

      After approving on the Install Plan page, the Subscription upgrade status moves to Up to date.

    2. If you selected an Automatic approval strategy, the upgrade status should resolve to Up to date without intervention.

      Figure 2.5. Subscription upgrade status Up to date

      olm uptodate
  8. After the Subscription’s upgrade status is Up to date, select Catalog → Installed Operators to verify that the Couchbase ClusterServiceVersion (CSV) eventually shows up and its Status ultimately resolves to InstallSucceeded in the relevant namespace.

    Note

    For the All namespaces…​ Installation Mode, the status resolves to InstallSucceeded in the openshift-operators namespace, but the status is Copied if you check in other namespaces.

    If it does not:

    1. Switch to the Catalog → Operator Management page and inspect the Operator Subscriptions and Install Plans tabs for any failure or errors under Status.
    2. Check the logs in any Pods in the openshift-operators project (or other relevant namespace if A specific namespace…​ Installation Mode was selected) on the Workloads → Pods page that are reporting issues to troubleshoot further.

2.4.1.2. Installing from the OperatorHub using the CLI

Instead of using the OpenShift Container Platform web console, you can install an Operator from the OperatorHub using the CLI. Use the oc command to create or update a CatalogSourceConfig object, then add a Subscription object.

Note

The web console version of this procedure handles the creation of the CatalogSourceConfig and Subscription objects behind the scenes for you, appearing as if it was one step.

Prerequisites

  • Access to an OpenShift Container Platform cluster using an account with cluster-admin permissions.
  • Install the oc command to your local system.

Procedure

  1. View the list of Operators available to the cluster from the OperatorHub:

    $ oc get packagemanifests -n openshift-marketplace
    NAME                     AGE
    amq-streams              14h
    packageserver            15h
    couchbase-enterprise     14h
    mongodb-enterprise       14h
    etcd                     14h
    myoperator               14h
    ...
  2. To identify the Operators to enable on the cluster, create a CatalogSourceConfig object YAML file (for example, csc.cr.yaml). Include one or more packages listed in the previous step (such as couchbase-enterprise or etcd). For example:

    Example CatalogSourceConfig

    apiVersion: operators.coreos.com/v1
    kind: CatalogSourceConfig
    metadata:
      name: example
      namespace: openshift-marketplace
    spec:
      targetNamespace: openshift-operators 1
      packages: myoperator 2

    1
    Set the targetNamespace to identify the namespace where you want the Operator to be available. The openshift-operators namespace is watched by the Operator Lifecycle Manager (OLM).
    2
    Set packages to a comma-separated list of Operators to which you want to subscribe.

    The Operator generates a CatalogSource from your CatalogSourceConfig in the namespace specified in targetNamespace.

  3. Create the CatalogSourceConfig to enable the specified Operators in the selected namespace:

    $ oc apply -f csc.cr.yaml
  4. Create a Subscription object YAML file (for example, myoperator-sub.yaml) to subscribe a namespace to an Operator. Note that the namespace you pick must have an OperatorGroup that matches the installMode (either AllNamespaces or SingleNamespace modes):

    Example Subscription

    apiVersion: operators.coreos.com/v1alpha1
    kind: Subscription
    metadata:
      name: myoperator
      namespace: openshift-operators
    spec:
      channel: alpha
      name: myoperator 1
      source: example 2
      sourceNamespace: openshift-operators

    1
    Name of the Operator to subscribe to.
    2
    Name of the CatalogSource that was created.
  5. Create the Subscription object:

    $ oc apply -f myoperator-sub.yaml

    At this point, the OLM is now aware of the selected Operator. A ClusterServiceVersion (CSV) for the Operator should appear in the target namespace, and APIs provided by the Operator should be available for creation.

  6. Later, if you want to install more Operators:

    1. Update your CatalogSourceConfig file (in this example, csc.cr.yaml) with more packages. For example:

      Example updated CatalogSourceConfig

      apiVersion: operators.coreos.com/v1
      kind: CatalogSourceConfig
      metadata:
        name: example
        namespace: openshift-marketplace
      spec:
        targetNamespace: global
        packages: myoperator,another-operator 1

      1
      Add new packages to existing package list.
    2. Update the CatalogSourceConfig object:

      $ oc apply -f csc.cr.yaml
    3. Create additional Subscription objects for the new Operators.

Additional resources

  • To install custom Operators to a cluster using the OperatorHub, you must first upload your Operator artifacts to Quay.io, then add your own OperatorSource to your cluster. Optionally, you can add Secrets to your Operator to provide authentication. After, you can manage the Operator in your cluster as you would any other Operator. For these steps, see Testing Operators.

2.5. Deleting Operators from a cluster

To delete (uninstall) an Operator from your cluster, you can simply delete the subscription to remove it from the subscribed namespace. If you want a clean slate, you can also remove the operator CSV and deployment, then delete Operator’s entry in the CatalogSourceConfig. The following text describes how to delete Operators from a cluster using either the web console or the command line.

2.5.1. Deleting Operators from a cluster using the web console

To delete an installed Operator from the selected namespace through the web console, follow these steps:

Procedure

  1. Select the Operator to delete. There are two paths to do this:

    • From the CatalogOperatorHub page:

      1. Scroll or type a keyword into the Filter by keyword box (in this case, jaeger) to find the Operator you want and click on it.
      2. Click Uninstall.
    • From the CatalogOperator Management page:

      1. Select the namespace where the Operator is installed from the Project list. For cluster-wide Operators, the default is openshift-operators.
      2. From the Operator Subscriptions tab, find the Operator you want to delete (in this example, jaeger) and click the Options menu kebab at the end of its entry.

        olm operator delete
      3. Click Remove Subscription.
  2. When prompted by the Remove Subscription window, optionally select the Also completely remove the jaeger Operator from the selected namespace check box if you want all components related to the installation to be removed. This removes the CSV, which in turn removes the Pods, Deployments, CRDs, and CRs associated with the Operator.
  3. Select Remove. This Operator will stop running and no longer receive updates.
Note

Although the Operator is no longer installed or receiving updates, that Operator will still appear on the Operator Catalogs list, ready to re-subscribe. To remove the Operator from that listing, you can delete the Operator’s entry in the CatalogSourceConfig from the command line (as shown in last step of "Deleting operators from a cluster using the CLI").

2.5.2. Deleting Operators from a cluster using the CLI

Instead of using the OpenShift Container Platform web console, you can delete an Operator from your cluster by using the CLI. You do this by deleting the Subscription and ClusterServiceVersion from the targetNamespace, then editing the CatalogSourceConfig to remove the Operator’s package name.

Prerequisites

  • Access to an OpenShift Container Platform cluster using an account with cluster-admin permissions.
  • Install the oc command on your local system.

Procedure

In this example, there are two operators (Jaeger and Descheduler) installed in the openshift-operators namespace. The goal is to remove Jaeger without removing Descheduler.

  1. Delete the Operator’s subscription (for example, jaeger):

    $ oc delete subscription jaeger -n openshift-operators
    subscription.operators.coreos.com "jaeger" deleted
  2. Check the current version of the subscribed Operator (for example, jaeger):

    $ oc get subscription jaeger -n openshift-operators -o yaml | grep currentCSV
      currentCSV: jaeger-operator.v1.8.2
  3. Delete the CSV for the Operator (jaeger) in the targetNamespace (openshift-operators):

    $ oc delete clusterserviceversion jaeger-operator.v1.8.2 -n openshift-operators
    clusterserviceversion.operators.coreos.com "jaeger-operator.v1.8.2" deleted
  4. Display the contents of the CatalogSourceConfig resource and review the list of packages in the spec section:

    $ oc get catalogsourceconfig -n openshift-marketplace \
        installed-community-openshift-operators -o yaml

    For example, the spec section might appear as follows:

    Example of CatalogSourceConfig

    spec:
      csDisplayName: Community Operators
      csPublisher: Community
      packages: jaeger,descheduler
      targetNamespace: openshift-operators

  5. Remove the Operator from the CatalogSourceConfig in one of two ways:

    • If you have multiple Operators, edit the CatalogSourceConfig resource and remove the Operator’s package:

      $ oc edit catalogsourceconfig -n openshift-marketplace \
          installed-community-openshift-operators

      Remove the package from the packages line, as shown:

      Example of modified packages in CatalogSourceConfig

        packages: descheduler

      Save the change and the marketplace-operator will reconcile the CatalogSourceConfig.

    • If there is only one Operator in the CatalogSourceConfig, you can remove it by deleting the entire CatalogSourceConfig as follows:

      $ oc delete catalogsourceconfig -n openshift-marketplace \
          installed-community-openshift-operators

2.6. Creating applications from installed Operators

This guide walks developers through an example of creating applications from an installed Operator using the OpenShift Container Platform 4.1 web console.

2.6.1. Creating an etcd cluster using an Operator

This procedure walks through creating a new etcd cluster using the etcd Operator, managed by the Operator Lifecycle Manager (OLM).

Prerequisites

  • Access to an OpenShift Container Platform 4.1 cluster
  • The etcd Operator already installed cluster-wide by an administrator

Procedure

  1. Create a new project in the OpenShift Container Platform web console for this procedure. This example uses a project called my-etcd.
  2. Navigate to the Catalogs → Installed Operators page. The Operators that have been installed to the cluster by the cluster administrator and are available for use are shown here as a list of ClusterServiceVersions (CSVs). CSVs are used to launch and manage the software provided by the Operator.

    Tip

    You can get this list from the CLI using:

    $ oc get csv
  3. On the Installed Operators page, click Copied, and then click the etcd Operator to view more details and available actions:

    Figure 2.6. etcd Operator overview

    etcd operator overview

    As shown under Provided APIs, this Operator makes available three new resource types, including one for an etcd Cluster (the EtcdCluster resource). These objects work similar to the built-in native Kubernetes ones, such as Deployments or ReplicaSets, but contain logic specific to managing etcd.

  4. Create a new etcd cluster:

    1. In the etcd Cluster API box, click Create New.
    2. The next screen allows you to make any modifications to the minimal starting template of an EtcdCluster object, such as the size of the cluster. For now, click Create to finalize. This triggers the Operator to start up the Pods, Services, and other components of the new etcd cluster.
  5. Click the Resources tab to see that your project now contains a number of resources created and configured automatically by the Operator.

    Figure 2.7. etcd Operator resources

    etcd operator resources

    Verify that a Kubernetes service has been created that allows you to access the database from other Pods in your project.

  6. All users with the edit role in a given project can create, manage, and delete application instances (an etcd cluster, in this example) managed by Operators that have already been created in the project, in a self-service manner, just like a cloud service. If you want to enable additional users with this ability, project administrators can add the role using the following command:

    $ oc policy add-role-to-user edit <user> -n <target_project>

You now have an etcd cluster that will react to failures and rebalance data as Pods become unhealthy or are migrated between nodes in the cluster. Most importantly, cluster administrators or developers with proper access can now easily use the database with their applications.

2.7. Managing resources from Custom Resource Definitions

This guide describes how developers can manage Custom Resources (CRs) that come from Custom Resource Definitions (CRDs).

2.7.1. Custom Resource Definitions

In the Kubernetes API, a resource is an endpoint that stores a collection of API objects of a certain kind. For example, the built-in Pods resource contains a collection of Pod objects.

A Custom Resource Definition (CRD) object defines a new, unique object Kind in the cluster and lets the Kubernetes API server handle its entire lifecycle.

Custom Resource (CR) objects are created from CRDs that have been added to the cluster by a cluster administrator, allowing all cluster users to add the new resource type into projects.

Operators in particular make use of CRDs by packaging them with any required RBAC policy and other software-specific logic. Cluster administrators can also add CRDs manually to the cluster outside of an Operator’s lifecycle, making them available to all users.

Note

While only cluster administrators can create CRDs, developers can create the CR from an existing CRD if they have read and write permission to it.

2.7.2. Creating Custom Resources from a file

After a Custom Resource Definition (CRD) has been added to the cluster, Custom Resources (CRs) can be created with the CLI from a file using the CR specification.

Prerequisites

  • CRD added to the cluster by a cluster administrator.

Procedure

  1. Create a YAML file for the CR. In the following example definition, the cronSpec and image custom fields are set in a CR of Kind: CronTab. The Kind comes from the spec.kind field of the CRD object.

    Example YAML file for a CR

    apiVersion: "stable.example.com/v1" 1
    kind: CronTab 2
    metadata:
      name: my-new-cron-object 3
      finalizers: 4
      - finalizer.stable.example.com
    spec: 5
      cronSpec: "* * * * /5"
      image: my-awesome-cron-image

    1
    Specify the group name and API version (name/version) from the Custom Resource Definition.
    2
    Specify the type in the CRD.
    3
    Specify a name for the object.
    4
    Specify the finalizers for the object, if any. Finalizers allow controllers to implement conditions that must be completed before the object can be deleted.
    5
    Specify conditions specific to the type of object.
  2. After you create the file, create the object:

    $ oc create -f <file_name>.yaml

2.7.3. Inspecting Custom Resources

You can inspect Custom Resource (CR) objects that exist in your cluster using the CLI.

Prerequisites

  • A CR object exists in a namespace to which you have access.

Procedure

  1. To get information on a specific Kind of a CR, run:

    $ oc get <kind>

    For example:

    $ oc get crontab
    
    NAME                 KIND
    my-new-cron-object   CronTab.v1.stable.example.com

    Resource names are not case-sensitive, and you can use either the singular or plural forms defined in the CRD, as well as any short name. For example:

    $ oc get crontabs
    $ oc get crontab
    $ oc get ct
  2. You can also view the raw YAML data for a CR:

    $ oc get <kind> -o yaml
    $ oc get ct -o yaml
    
    apiVersion: v1
    items:
    - apiVersion: stable.example.com/v1
      kind: CronTab
      metadata:
        clusterName: ""
        creationTimestamp: 2017-05-31T12:56:35Z
        deletionGracePeriodSeconds: null
        deletionTimestamp: null
        name: my-new-cron-object
        namespace: default
        resourceVersion: "285"
        selfLink: /apis/stable.example.com/v1/namespaces/default/crontabs/my-new-cron-object
        uid: 9423255b-4600-11e7-af6a-28d2447dc82b
      spec:
        cronSpec: '* * * * /5' 1
        image: my-awesome-cron-image 2
    1 2
    Custom data from the YAML that you used to create the object displays.

Chapter 3. Service brokers

3.1. Installing the service catalog

Important

The service catalog is deprecated in OpenShift Container Platform 4. Equivalent and better functionality is present in the Operator Framework and Operator Lifecycle Manager (OLM).

3.1.1. About the service catalog

When developing microservices-based applications to run on cloud native platforms, there are many ways to provision different resources and share their coordinates, credentials, and configuration, depending on the service provider and the platform.

To give developers a more seamless experience, OpenShift Container Platform includes a service catalog, an implementation of the Open Service Broker API (OSB API) for Kubernetes. This allows users to connect any of their applications deployed in OpenShift Container Platform to a wide variety of service brokers.

The service catalog allows cluster administrators to integrate multiple platforms using a single API specification. The OpenShift Container Platform web console displays the cluster service classes offered by service brokers in the service catalog, allowing users to discover and instantiate those services for use with their applications.

As a result, service users benefit from ease and consistency of use across different types of services from different providers, while service providers benefit from having one integration point that gives them access to multiple platforms.

The service catalog is not installed by default in OpenShift Container Platform 4.

3.1.2. Installing service catalog

If you plan on using any of the services from the OpenShift Ansible Broker or Template Service Broker, you must install the service catalog by completing the following steps.

The custom resources for the service catalog’s API server and controller manager are created by default in OpenShift Container Platform, but initially have a managementState of Removed. To install the service catalog, you must change the managementState for these resources to Managed.

Procedure

  1. Enable the service catalog API server.

    1. Use the following command to edit the service catalog API server resource.

      $ oc edit servicecatalogapiservers
    2. Under spec, set the managementState field to Managed:

      spec:
        logLevel: Normal
        managementState: Managed
    3. Save the file to apply the changes.

      The Operator installs the service catalog API server component. As of OpenShift Container Platform 4, this component is installed into the openshift-service-catalog-apiserver namespace.

  2. Enable the service catalog controller manager.

    1. Use the following command to edit the service catalog controller manager resource.

      $ oc edit servicecatalogcontrollermanagers
    2. Under spec, set the managementState field to Managed:

      spec:
        logLevel: Normal
        managementState: Managed
    3. Save the file to apply the changes.

      The Operator installs the service catalog controller manager component. As of OpenShift Container Platform 4, this component is installed into the openshift-service-catalog-controller-manager namespace.

3.2. Installing the Template Service Broker

You can install the Template Service Broker to gain access to the template applications that it provides.

Important

The Template Service Broker is deprecated in OpenShift Container Platform 4. Equivalent and better functionality is present in the Operator Framework and Operator Lifecycle Manager (OLM).

3.2.1. About the Template Service Broker

The Template Service Broker gives the service catalog visibility into the default Instant App and Quickstart templates that have shipped with OpenShift Container Platform since its initial release. The Template Service Broker can also make available as a service anything for which an OpenShift Container Platform template has been written, whether provided by Red Hat, a cluster administrator or user, or a third-party vendor.

By default, the Template Service Broker shows objects that are globally available from the openshift project. It can also be configured to watch any other project that a cluster administrator chooses.

The Template Service Broker is not installed by default in OpenShift Container Platform 4.

3.2.2. Installing the Template Service Broker Operator

Prerequisites

  • You have installed the service catalog.

Procedure

The following procedure installs the Template Service Broker Operator using the web console.

  1. Create a namespace.

    1. Navigate in the web console to AdministrationNamespaces and click Create Namespace.
    2. Enter openshift-template-service-broker in the Name field and click Create.

      Note

      The namespace must start with openshift-.

  2. Navigate to the CatalogOperatorHub page. Verify that the openshift-template-service-broker project is selected.
  3. Select Template Service Broker Operator.
  4. Read the information about the Operator and click Install.
  5. Review the default selections and click Subscribe.

Next, you must start the Template Service Broker in order to access the template applications it provides.

3.2.3. Starting the Template Service Broker

After you have installed the Template Service Broker Operator, you can start the Template Service Broker using the following procedure.

Prerequisites

  • You have installed the service catalog.
  • You have installed the Template Service Broker Operator.

Procedure

  1. Navigate in the web console to CatalogInstalled Operators and select the openshift-template-service-broker project.
  2. Select the Template Service Broker Operator.
  3. Under Provided APIs, click Create New for Template Service Broker.
  4. Review the default YAML and click Create.
  5. Verify that the Template Service Broker has started.

    After the Template Service Broker has started, you can view the available template applications by navigating to CatalogDeveloper Catalog and selecting the Service Class checkbox. Note that it may take a few minutes for the Template Service Broker to start and the template applications to be available.

    If you do not yet see these Service classes, you can check the status of the following items:

    • Template Service Broker Pod status

      • From the WorkloadsPods page for the openshift-template-service-broker project, verify that the Pod that starts with apiserver- has a status of Running and readiness of Ready.
    • Cluster service broker status

      • From the CatalogBroker ManagementService Brokers page, verify that the template-service-broker service broker has a status of Ready.
    • Service catalog controller manager Pod logs

      • From the WorkloadsPods page for the openshift-service-catalog-controller-manager project, review the logs for each of the Pods and verify that you see a log entry with the message Successfully fetched catalog entries from broker.

3.3. Provisioning template applications

3.3.1. Provisioning template applications

The following procedure provisions an example PostgreSQL template application that was made available by the Template Service Broker.

Prerequisites

  • The service catalog is installed.
  • The Template Service Broker is installed.

Procedure

  1. Create a project.

    1. Navigate in the web console to HomeProjects and click Create Project.
    2. Enter test-postgresql in the Name field and click Create.
  2. Create a service instance.

    1. Navigate to the CatalogDeveloper Catalog page.
    2. Select the PostgreSQL (Ephemeral) template application and click Create Service Instance.
    3. Review the default selections and set any other required fields, and click Create.
    4. Go to CatalogProvisioned Services and verify that the postgresql-ephemeral service instance is created and has a status of Ready.

      You can check the progress on the HomeEvents page. After a few moments, you should see an event for postgresql-ephemeral with the message "The instance was provisioned successfully".

  3. Create a service binding.

    1. From the Provisioned Services page, click postgresql-ephemeral and click Create Service Binding.
    2. Review the default service binding name and click Create.

      This creates a new secret for binding using the name provided.

  4. Review the secret that was created.

    1. Navigate to WorkloadsSecrets and verify that a secret named postgresql-ephemeral was created.
    2. Click postgresql-ephemeral and review the key-value pairs in the Data section, which are used for binding to other apps.

3.4. Uninstalling the Template Service Broker

You can uninstall the Template Service Broker if you no longer require access to the template applications that it provides.

Important

The Template Service Broker is deprecated in OpenShift Container Platform 4. Equivalent and better functionality is present in the Operator Framework and Operator Lifecycle Manager (OLM).

3.4.1. Uninstalling the Template Service Broker

The following procedure uninstalls the Template Service Broker and its Operator using the web console.

Warning

Do not uninstall the Template Service Broker if there are any provisioned services from it in your cluster, otherwise you might encounter errors when trying to manage the services.

Prerequisites

  • The Template Service Broker is installed.

Procedure

This procedure assumes that you installed the Template Service Broker into the openshift-template-service-broker project.

  1. Uninstall the Template Service Broker.

    1. Navigate to CatalogInstalled Operators and select the openshift-template-service-broker project from the drop-down menu.
    2. Click Template Service Broker Operator.
    3. Select the Template Service Broker tab.
    4. Click template-service-broker.
    5. From the Actions drop-down menu, select Delete Template Service Broker.
    6. Click Delete from the confirmation pop-up window.

      The Template Service Broker is now uninstalled, and template applications will soon be removed from the Developer Catalog.

  2. Uninstall the Template Service Broker Operator.

    1. Navigate to CatalogOperator Management and select the openshift-template-service-broker project from the drop-down menu.
    2. Click View subscription for the Template Service Broker Operator.
    3. Select templateservicebroker.
    4. From the Actions drop-down menu, select Remove Subscription.
    5. Verify that the checkbox is checked next to Also completely remove the templateservicebroker Operator from the selected namespace and click Remove.

      The Template Service Broker Operator is no longer installed in your cluster.

After the Template Service Broker is uninstalled, users will no longer have access to the template applications provided by the Template Service Broker.

3.5. Installing the OpenShift Ansible Broker

You can install the OpenShift Ansible Broker to gain access to the service bundles that it provides.

Important

The OpenShift Ansible Broker is deprecated in OpenShift Container Platform 4. Equivalent and better functionality is present in the Operator Framework and Operator Lifecycle Manager (OLM).

3.5.1. About the OpenShift Ansible Broker

The OpenShift Ansible Broker is an implementation of the Open Service Broker (OSB) API that manages applications defined by Ansible playbook bundles (APBs). APBs provide a method for defining and distributing container applications in OpenShift Container Platform, and consist of a bundle of Ansible playbooks built into a container image with an Ansible runtime. APBs leverage Ansible to create a standard mechanism to automate complex deployments.

The OpenShift Ansible Broker follows this basic workflow:

  1. A user requests the list of available applications from the service catalog using the OpenShift Container Platform web console.
  2. The service catalog requests the list of available applications from the OpenShift Ansible Broker.
  3. The OpenShift Ansible Broker communicates with a defined container image registry to learn which APBs are available.
  4. The user issues a request to provision a specific APB.
  5. The OpenShift Ansible Broker fulfills the user’s provision request by invoking the provision method on the APB.

The OpenShift Ansible Broker is not installed by default in OpenShift Container Platform 4.

3.5.1.1. Ansible playbook bundles

An Ansible playbook bundle (APB) is a lightweight application definition that allows you to leverage existing investment in Ansible roles and playbooks.

APBs use a simple directory with named playbooks to perform OSB API actions, such as provision and bind. Metadata defined in the apb.yml file contains a list of required and optional parameters for use during deployment.

3.5.2. Installing the OpenShift Ansible Service Broker Operator

Prerequisites

  • You have installed the service catalog.

Procedure

The following procedure installs the OpenShift Ansible Service Broker Operator using the web console.

  1. Create a namespace.

    1. Navigate in the web console to AdministrationNamespaces and click Create Namespace.
    2. Enter openshift-ansible-service-broker in the Name field and openshift.io/cluster-monitoring=true in the Labels field and click Create.

      Note

      The namespace must start with openshift-.

  2. Create a cluster role binding.

    1. Navigate to AdministrationRole Bindings and click Create Binding.
    2. For the Binding Type, select Cluster-wide Role Binding (ClusterRoleBinding).
    3. For the Role Binding, enter ansible-service-broker in the Name field.
    4. For the Role, select admin.
    5. For the Subject, choose the Service Account option, select the openshift-ansible-service-broker namespace, and enter openshift-ansible-service-broker-operator in the Subject Name field.
    6. Click Create.
  3. Create a secret to connect to the Red Hat Container Catalog.

    1. Navigate to WorkloadsSecrets. Verify that the openshift-ansible-service-broker project is selected.
    2. Click CreateKey/Value Secret.
    3. Enter asb-registry-auth as the Secret Name.
    4. Add a Key of username and a Value of your Red Hat Container Catalog user name.
    5. Click Add Key/Value and add a Key of password and a Value of your Red Hat Container Catalog password.
    6. Click Create.
  4. Navigate to the CatalogOperatorHub page. Verify that the openshift-ansible-service-broker project is selected.
  5. Select OpenShift Ansible Service Broker Operator.
  6. Read the information about the Operator and click Install.
  7. Review the default selections and click Subscribe.

Next, you must start the OpenShift Ansible Broker in order to access the service bundles it provides.

3.5.3. Starting the OpenShift Ansible Broker

After you have installed the OpenShift Ansible Service Broker Operator, you can start the OpenShift Ansible Broker using the following procedure.

Prerequisites

  • You have installed the service catalog.
  • You have installed the OpenShift Ansible Service Broker Operator.

Procedure

  1. Navigate in the web console to CatalogInstalled Operators and select the openshift-ansible-service-broker project.
  2. Select the OpenShift Ansible Service Broker Operator.
  3. Under Provided APIs, click Create New for Automation Broker.
  4. Add the following to the spec field in the default YAML provided:

    registry:
      - name: rhcc
        type: rhcc
        url: https://registry.redhat.io
        auth_type: secret
        auth_name: asb-registry-auth

    This references the secret that was created when installing the OpenShift Ansible Service Broker Operator, which allows you to connect to the Red Hat Container Catalog.

  5. Set any additional OpenShift Ansible Broker configuration options and click Create.
  6. Verify that the OpenShift Ansible Broker has started.

    After the OpenShift Ansible Broker has started, you can view the available service bundles by navigating to CatalogDeveloper Catalog and selecting the Service Class checkbox. Note that it may take a few minutes for the OpenShift Ansible Broker to start and the service bundles to be available.

    If you do not yet see these Service classes, you can check the status of the following items:

    • OpenShift Ansible Broker Pod status

      • From the WorkloadsPods page for the openshift-ansible-service-broker project, verify that the Pod that starts with asb- has a status of Running and readiness of Ready.
    • Cluster service broker status

      • From the CatalogBroker ManagementService Brokers page, verify that the ansible-service-broker service broker has a status of Ready.
    • Service catalog controller manager Pod logs

      • From the WorkloadsPods page for the openshift-service-catalog-controller-manager project, review the logs for each of the Pods and verify that you see a log entry with the message Successfully fetched catalog entries from broker.

3.5.3.1. OpenShift Ansible Broker configuration options

You can set the following options for your OpenShift Ansible Broker.

Table 3.1. OpenShift Ansible Broker configuration options

YAML keyDescriptionDefault value

brokerName

The name used to identify the broker instance.

ansible-service-broker

brokerNamespace

The namespace where the broker resides.

openshift-ansible-service-broker

brokerImage

The fully qualified image used for the broker.

docker.io/ansibleplaybookbundle/origin-ansible-service-broker:v4.0

brokerImagePullPolicy

The pull policy used for the broker image itself.

IfNotPresent

brokerNodeSelector

The node selector string used for the broker’s deployment.

''

registries

Expressed as a yaml list of broker registry configs, allowing the user to configure the image registries the broker will discover and source its APBs from.

See the default registries array.

logLevel

The log level used for the broker’s logs.

info

apbPullPolicy

The pull policy used for APB Pods.

IfNotPresent

sandboxRole

The role granted to the service account used to execute APBs.

edit

keepNamespace

Whether the transient namespace created to run the APB is deleted after the conclusion of the APB, regardless of the result.

false

keepNamespaceOnError

Whether the transient namespace created to run the APB is deleted after the conclusion of the APB, only in the event of an error result.

false

bootstrapOnStartup

Whether or not the broker should run its bootstrap routine on startup.

true

refreshInterval

The interval of time between broker bootstraps, refreshing its inventory of APBs.

600s

launchApbOnBind

Experimental: Toggles the broker executing APBs on bind operations.

false

autoEscalate

Whether the broker should escalate the permissions of a user while running the APB. This should typically remain false since the broker performs originating user authorization to ensure that the user has permissions granted to the APB sandbox.

false

outputRequest

Whether to output the low level HTTP requests that the broker receives.

false

Default array for registries

- type: rhcc
  name: rhcc
  url: https://registry.redhat.io
  white_list:
  - ".*-apb$"
  auth_type: secret
  auth_name: asb-registry-auth

3.6. Configuring the OpenShift Ansible Broker

Important

The OpenShift Ansible Broker is deprecated in OpenShift Container Platform 4. Equivalent and better functionality is present in the Operator Framework and Operator Lifecycle Manager (OLM).

3.6.1. Configuring the OpenShift Ansible Broker

The following procedure customizes the settings for your OpenShift Ansible Broker.

Prerequisites

  • You have installed and started the OpenShift Ansible Broker.

Procedure

This procedure assumes that you used ansible-service-broker both as the OpenShift Ansible Broker name and the project that it was installed into.

  1. Navigate in the web console to CatalogInstalled Operators and select the ansible-service-broker project.
  2. Select the OpenShift Ansible Service Broker Operator.
  3. On the Automation Broker tab, select ansible-service-broker.
  4. On the YAML tab, add or update any OpenShift Ansible Broker configuration options under the spec field.

    For example:

    spec:
      keepNamespace: true
      sandboxRole: edit
  5. Click Save to apply these changes.

3.6.1.1. OpenShift Ansible Broker configuration options

You can set the following options for your OpenShift Ansible Broker.

Table 3.2. OpenShift Ansible Broker configuration options

YAML keyDescriptionDefault value

brokerName

The name used to identify the broker instance.

ansible-service-broker

brokerNamespace

The namespace where the broker resides.

openshift-ansible-service-broker

brokerImage

The fully qualified image used for the broker.

docker.io/ansibleplaybookbundle/origin-ansible-service-broker:v4.0

brokerImagePullPolicy

The pull policy used for the broker image itself.

IfNotPresent

brokerNodeSelector

The node selector string used for the broker’s deployment.

''

registries

Expressed as a yaml list of broker registry configs, allowing the user to configure the image registries the broker will discover and source its APBs from.

See the default registries array.

logLevel

The log level used for the broker’s logs.

info

apbPullPolicy

The pull policy used for APB Pods.

IfNotPresent

sandboxRole

The role granted to the service account used to execute APBs.

edit

keepNamespace

Whether the transient namespace created to run the APB is deleted after the conclusion of the APB, regardless of the result.

false

keepNamespaceOnError

Whether the transient namespace created to run the APB is deleted after the conclusion of the APB, only in the event of an error result.

false

bootstrapOnStartup

Whether or not the broker should run its bootstrap routine on startup.

true

refreshInterval

The interval of time between broker bootstraps, refreshing its inventory of APBs.

600s

launchApbOnBind

Experimental: Toggles the broker executing APBs on bind operations.

false

autoEscalate

Whether the broker should escalate the permissions of a user while running the APB. This should typically remain false since the broker performs originating user authorization to ensure that the user has permissions granted to the APB sandbox.

false

outputRequest

Whether to output the low level HTTP requests that the broker receives.

false

Default array for registries

- type: rhcc
  name: rhcc
  url: https://registry.redhat.io
  white_list:
  - ".*-apb$"
  auth_type: secret
  auth_name: asb-registry-auth

3.6.2. Configuring monitoring for the OpenShift Ansible Broker

In order for Prometheus to monitor the OpenShift Ansible Broker, you must create the following resources to grant Prometheus permission to access the namespace where the OpenShift Ansible Broker was installed.

Prerequisites

  • The OpenShift Ansible Broker is installed.

    Note

    This procedure assumes that you installed the OpenShift Ansible Broker into the openshift-ansible-service-broker namespace.

Procedure

  1. Create the role.

    1. Navigate to AdministrationRoles and click Create Role.
    2. Replace the YAML in the editor with the following:

      apiVersion: rbac.authorization.k8s.io/v1
      kind: Role
      metadata:
        name: prometheus-k8s
        namespace: openshift-ansible-service-broker
      rules:
      - apiGroups:
        - ""
        resources:
        - services
        - endpoints
        - pods
        verbs:
        - get
        - list
        - watch
    3. Click Create.
  2. Create the role binding.

    1. Navigate to AdministrationRole Bindings and click Create Binding.
    2. For the Binding Type, select Namespace Role Binding (RoleBinding).
    3. For the Role Binding, enter prometheus-k8s in the Name field and openshift-ansible-service-broker in the Namespace field.
    4. For the Role, select prometheus-k8s.
    5. For the Subject, choose the Service Account option, select the openshift-monitoring namespace, and enter prometheus-k8s in the Subject Name field.
    6. Click Create.

Prometheus will now have access to OpenShift Ansible Broker metrics.

3.7. Provisioning service bundles

3.7.1. Provisioning service bundles

The following procedure provisions an example PostgreSQL service bundle (APB) that was made available by the OpenShift Ansible Broker.

Prerequisites

  • The service catalog is installed.
  • The OpenShift Ansible Broker is installed.

Procedure

  1. Create a project.

    1. Navigate in the web console to HomeProjects and click Create Project.
    2. Enter test-postgresql-apb in the Name field and click Create.
  2. Create a service instance.

    1. Navigate to the CatalogDeveloper Catalog page.
    2. Select the PostgreSQL (APB) service bundle and click Create Service Instance.
    3. Review the default selections and set any other required fields, and click Create.
    4. Go to CatalogProvisioned Services and verify that the dh-postgresql-apb service instance is created and has a status of Ready.

      You can check the progress on the HomeEvents page. After a few moments, you should see an event for dh-postgresql-apb with the message "The instance was provisioned successfully".

  3. Create a service binding.

    1. From the Provisioned Services page, click dh-postgresql-apb and click Create Service Binding.
    2. Review the default service binding name and click Create.

      This creates a new secret for binding using the name provided.

  4. Review the secret that was created.

    1. Navigate to WorkloadsSecrets and verify that a secret named dh-postgresql-apb was created.
    2. Click dh-postgresql-apb and review the key-value pairs in the Data section, which are used for binding to other apps.

3.8. Uninstalling the OpenShift Ansible Broker

You can uninstall the OpenShift Ansible Broker if you no longer require access to the service bundles that it provides.

Important

The OpenShift Ansible Broker is deprecated in OpenShift Container Platform 4. Equivalent and better functionality is present in the Operator Framework and Operator Lifecycle Manager (OLM).

3.8.1. Uninstalling the OpenShift Ansible Broker

The following procedure uninstalls the OpenShift Ansible Broker and its Operator using the web console.

Warning

Do not uninstall the OpenShift Ansible Broker if there are any provisioned services from it in your cluster, otherwise you might encounter errors when trying to manage the services.

Prerequisites

  • The OpenShift Ansible Broker is installed.

Procedure

This procedure assumes that you installed the OpenShift Ansible Broker into the openshift-ansible-service-broker project.

  1. Uninstall the OpenShift Ansible Broker.

    1. Navigate to CatalogInstalled Operators and select the openshift-ansible-service-broker project from the drop-down menu.
    2. Click OpenShift Ansible Service Broker Operator.
    3. Select the Automation Broker tab.
    4. Click ansible-service-broker.
    5. From the Actions drop-down menu, select Delete Automation Broker.
    6. Click Delete from the confirmation pop-up window.

      The OpenShift Ansible Broker is now uninstalled, and service bundles will soon be removed from the Developer Catalog.

  2. Uninstall the OpenShift Ansible Service Broker Operator.

    1. Navigate to CatalogOperator Management and select the openshift-ansible-service-broker project from the drop-down menu.
    2. Click View subscription for the OpenShift Ansible Service Broker Operator.
    3. Select automationbroker.
    4. From the Actions drop-down menu, select Remove Subscription.
    5. Verify that the checkbox is checked next to Also completely remove the automationbroker Operator from the selected namespace and click Remove.

      The OpenShift Ansible Service Broker Operator is no longer installed in your cluster.

After the OpenShift Ansible Broker is uninstalled, users will no longer have access to the service bundles provided by the OpenShift Ansible Broker.

Chapter 4. Deployments

4.1. Understanding Deployments and DeploymentConfigs

Deployments and DeploymentConfigs in OpenShift Container Platform are API objects that provide two similar but different methods for fine-grained management over common user applications. They are composed of the following separate API objects:

  • A DeploymentConfig or a Deployment, either of which describes the desired state of a particular component of the application as a Pod template.
  • DeploymentConfigs involve one or more ReplicationControllers, which contain a point-in-time record of the state of a DeploymentConfig as a Pod template. Similarly, Deployments involve one or more ReplicaSets, a successor of ReplicationControllers.
  • One or more Pods, which represent an instance of a particular version of an application.

4.1.1. Building blocks of a deployment

Deployments and DeploymentConfigs are enabled by the use of native Kubernetes API objects ReplicationControllers and ReplicaSets, respectively, as their building blocks.

Users do not have to manipulate ReplicationControllers, ReplicaSets, or Pods owned by DeploymentConfigs or Deployments. The deployment systems ensures changes are propagated appropriately.

Tip

If the existing deployment strategies are not suited for your use case and you must run manual steps during the lifecycle of your deployment, then you should consider creating a Custom deployment strategy.

The following sections provide further details on these objects.

4.1.1.1. ReplicationControllers

A ReplicationController ensures that a specified number of replicas of a Pod are running at all times. If Pods exit or are deleted, the ReplicationController acts to instantiate more up to the defined number. Likewise, if there are more running than desired, it deletes as many as necessary to match the defined amount.

A ReplicationController configuration consists of:

  • The number of replicas desired (which can be adjusted at runtime).
  • A Pod definition to use when creating a replicated Pod.
  • A selector for identifying managed Pods.

A selector is a set of labels assigned to the Pods that are managed by the ReplicationController. These labels are included in the Pod definition that the ReplicationController instantiates. The ReplicationController uses the selector to determine how many instances of the Pod are already running in order to adjust as needed.

The ReplicationController does not perform auto-scaling based on load or traffic, as it does not track either. Rather, this requires its replica count to be adjusted by an external auto-scaler.

The following is an example definition of a ReplicationController:

apiVersion: v1
kind: ReplicationController
metadata:
  name: frontend-1
spec:
  replicas: 1  1
  selector:    2
    name: frontend
  template:    3
    metadata:
      labels:  4
        name: frontend 5
    spec:
      containers:
      - image: openshift/hello-openshift
        name: helloworld
        ports:
        - containerPort: 8080
          protocol: TCP
      restartPolicy: Always
1
The number of copies of the Pod to run.
2
The label selector of the Pod to run.
3
A template for the Pod the controller creates.
4
Labels on the Pod should include those from the label selector.
5
The maximum name length after expanding any parameters is 63 characters.

4.1.1.2. ReplicaSets

Similar to a ReplicationController, a ReplicaSet is a native Kubernetes API object that ensures a specified number of pod replicas are running at any given time. The difference between a ReplicaSet and a ReplicationController is that a ReplicaSet supports set-based selector requirements whereas a replication controller only supports equality-based selector requirements.

Note

Only use ReplicaSets if you require custom update orchestration or do not require updates at all. Otherwise, use Deployments. ReplicaSets can be used independently, but are used by deployments to orchestrate pod creation, deletion, and updates. Deployments manage their ReplicaSets automatically, provide declarative updates to pods, and do not have to manually manage the ReplicaSets that they create.

The following is an example ReplicaSet definition:

apiVersion: apps/v1
kind: ReplicaSet
metadata:
  name: frontend-1
  labels:
    tier: frontend
spec:
  replicas: 3
  selector: 1
    matchLabels: 2
      tier: frontend
    matchExpressions: 3
      - {key: tier, operator: In, values: [frontend]}
  template:
    metadata:
      labels:
        tier: frontend
    spec:
      containers:
      - image: openshift/hello-openshift
        name: helloworld
        ports:
        - containerPort: 8080
          protocol: TCP
      restartPolicy: Always
1
A label query over a set of resources. The result of matchLabels and matchExpressions are logically conjoined.
2
Equality-based selector to specify resources with labels that match the selector.
3
Set-based selector to filter keys. This selects all resources with key equal to tier and value equal to frontend.

4.1.2. DeploymentConfigs

Building on ReplicationControllers, OpenShift Container Platform adds expanded support for the software development and deployment lifecycle with the concept of DeploymentConfigs. In the simplest case, a DeploymentConfig creates a new ReplicationController and lets it start up Pods.

However, OpenShift Container Platform deployments from DeploymentConfigs also provide the ability to transition from an existing deployment of an image to a new one and also define hooks to be run before or after creating the ReplicationController.

The DeploymentConfig deployment system provides the following capabilities:

  • A DeploymentConfig, which is a template for running applications.
  • Triggers that drive automated deployments in response to events.
  • User-customizable deployment strategies to transition from the previous version to the new version. A strategy runs inside a Pod commonly referred as the deployment process.
  • A set of hooks (lifecycle hooks) for executing custom behavior in different points during the lifecycle of a deployment.
  • Versioning of your application in order to support rollbacks either manually or automatically in case of deployment failure.
  • Manual replication scaling and autoscaling.

When you create a DeploymentConfig, a ReplicationController is created representing the DeploymentConfig’s Pod template. If the DeploymentConfig changes, a new ReplicationController is created with the latest Pod template, and a deployment process runs to scale down the old ReplicationController and scale up the new one.

Instances of your application are automatically added and removed from both service load balancers and routers as they are created. As long as your application supports graceful shutdown when it receives the TERM signal, you can ensure that running user connections are given a chance to complete normally.

The OpenShift Container Platform DeploymentConfig object defines the following details:

  1. The elements of a ReplicationController definition.
  2. Triggers for creating a new deployment automatically.
  3. The strategy for transitioning between deployments.
  4. Lifecycle hooks.

Each time a deployment is triggered, whether manually or automatically, a deployer Pod manages the deployment (including scaling down the old ReplicationController, scaling up the new one, and running hooks). The deployment pod remains for an indefinite amount of time after it completes the Deployment in order to retain its logs of the Deployment. When a deployment is superseded by another, the previous ReplicationController is retained to enable easy rollback if needed.

Example DeploymentConfig definition

apiVersion: v1
kind: DeploymentConfig
metadata:
  name: frontend
spec:
  replicas: 5
  selector:
    name: frontend
  template: { ... }
  triggers:
  - type: ConfigChange 1
  - imageChangeParams:
      automatic: true
      containerNames:
      - helloworld
      from:
        kind: ImageStreamTag
        name: hello-openshift:latest
    type: ImageChange  2
  strategy:
    type: Rolling      3

1
A ConfigChange trigger causes a new Deployment to be created any time the ReplicationController template changes.
2
An ImageChange trigger causes a new Deployment to be created each time a new version of the backing image is available in the named imagestream.
3
The default Rolling strategy makes a downtime-free transition between Deployments.

4.1.3. Deployments

Kubernetes provides a first-class, native API object type in OpenShift Container Platform called Deployments. Deployments serve as a descendant of the OpenShift Container Platform-specific DeploymentConfig.

Like DeploymentConfigs, Deployments describe the desired state of a particular component of an application as a Pod template. Deployments create ReplicaSets, which orchestrate Pod lifecycles.

For example, the following Deployment definition creates a ReplicaSet to bring up one hello-openshift Pod:

Deployment definition

apiVersion: apps/v1
kind: Deployment
metadata:
  name: hello-openshift
spec:
  replicas: 1
  selector:
    matchLabels:
      app: hello-openshift
  template:
    metadata:
      labels:
        app: hello-openshift
    spec:
      containers:
      - name: hello-openshift
        image: openshift/hello-openshift:latest
        ports:
        - containerPort: 80

4.1.4. Comparing Deployments and DeploymentConfigs

Both Kubernetes Deployments and OpenShift Container Platform-provided DeploymentConfigs are supported in OpenShift Container Platform; however, it is recommended to use Deployments unless you need a specific feature or behavior provided by DeploymentConfigs.

The following sections go into more detail on the differences between the two object types to further help you decide which type to use.

4.1.4.1. Design

One important difference between Deployments and DeploymentConfigs is the properties of the CAP theorem that each design has chosen for the rollout process. DeploymentConfigs prefer consistency, whereas Deployments take availability over consistency.

For DeploymentConfigs, if a node running a deployer Pod goes down, it will not get replaced. The process waits until the node comes back online or is manually deleted. Manually deleting the node also deletes the corresponding Pod. This means that you can not delete the Pod to unstick the rollout, as the kubelet is responsible for deleting the associated Pod.

However, Deployments rollouts are driven from a controller manager. The controller manager runs in high availability mode on masters and uses leader election algorithms to value availability over consistency. During a failure it is possible for other masters to act on the same Deployment at the same time, but this issue will be reconciled shortly after the failure occurs.

4.1.4.2. DeploymentConfigs-specific features

Automatic rollbacks

Currently, Deployments do not support automatically rolling back to the last successfully deployed ReplicaSet in case of a failure.

Triggers

Deployments have an implicit ConfigChange trigger in that every change in the pod template of a deployment automatically triggers a new rollout. If you do not want new rollouts on pod template changes, pause the deployment:

$ oc rollout pause deployments/<name>
Lifecycle hooks

Deployments do not yet support any lifecycle hooks.

Custom strategies

Deployments do not support user-specified Custom deployment strategies yet.

4.1.4.3. Deployments-specific features

Rollover

The deployment process for Deployments is driven by a controller loop, in contrast to DeploymentConfigs which use deployer pods for every new rollout. This means that a Deployment can have as many active ReplicaSets as possible, and eventually the deployment controller will scale down all old ReplicaSets and scale up the newest one.

DeploymentConfigs can have at most one deployer pod running, otherwise multiple deployers end up conflicting while trying to scale up what they think should be the newest ReplicationController. Because of this, only two ReplicationControllers can be active at any point in time. Ultimately, this translates to faster rapid rollouts for Deployments.

Proportional scaling

Because the Deployment controller is the sole source of truth for the sizes of new and old ReplicaSets owned by a Deployment, it is able to scale ongoing rollouts. Additional replicas are distributed proportionally based on the size of each ReplicaSet.

DeploymentConfigs cannot be scaled when a rollout is ongoing because the DeploymentConfig controller will end up having issues with the deployer process about the size of the new ReplicationController.

Pausing mid-rollout

Deployments can be paused at any point in time, meaning you can also pause ongoing rollouts. On the other hand, you cannot pause deployer pods currently, so if you try to pause a DeploymentConfig in the middle of a rollout, the deployer process will not be affected and will continue until it finishes.

4.2. Managing deployment processes

4.2.1. Managing DeploymentConfigs

DeploymentConfigs can be managed from the OpenShift Container Platform web console’s Workloads page or using the oc CLI. The following procedures show CLI usage unless otherwise stated.

4.2.1.1. Starting a deployment

You can start a rollout to begin the deployment process of your application.

Procedure

  1. To start a new deployment process from an existing DeploymentConfig, run the following command:

    $ oc rollout latest dc/<name>
    Note

    If a deployment process is already in progress, the command displays a message and a new ReplicationController will not be deployed.

4.2.1.2. Viewing a deployment

You can view a deployment to get basic information about all the available revisions of your application.

Procedure

  1. To show details about all recently created ReplicationControllers for the provided DeploymentConfig, including any currently running deployment process, run the following command:

    $ oc rollout history dc/<name>
  2. To view details specific to a revision, add the --revision flag:

    $ oc rollout history dc/<name> --revision=1
  3. For more detailed information about a deployment configuration and its latest revision, use the oc describe command:

    $ oc describe dc <name>

4.2.1.3. Retrying a deployment

If the current revision of your DeploymentConfig failed to deploy, you can restart the deployment process.

Procedure

  1. To restart a failed deployment process:

    $ oc rollout retry dc/<name>

    If the latest revision of it was deployed successfully, the command displays a message and the deployment process is not be retried.

    Note

    Retrying a deployment restarts the deployment process and does not create a new deployment revision. The restarted ReplicationController has the same configuration it had when it failed.

4.2.1.4. Rolling back a deployment

Rollbacks revert an application back to a previous revision and can be performed using the REST API, the CLI, or the web console.

Procedure

  1. To rollback to the last successful deployed revision of your configuration:

    $ oc rollout undo dc/<name>

    The DeploymentConfig’s template is reverted to match the deployment revision specified in the undo command, and a new ReplicationController is started. If no revision is specified with --to-revision, then the last successfully deployed revision is used.

  2. Image change triggers on the DeploymentConfig are disabled as part of the rollback to prevent accidentally starting a new deployment process soon after the rollback is complete.

    To re-enable the image change triggers:

    $ oc set triggers dc/<name> --auto
Note

DeploymentConfigs also support automatically rolling back to the last successful revision of the configuration in case the latest deployment process fails. In that case, the latest template that failed to deploy stays intact by the system and it is up to users to fix their configurations.

4.2.1.5. Executing commands inside a container

You can add a command to a container, which modifies the container’s startup behavior by overruling the image’s ENTRYPOINT. This is different from a lifecycle hook, which instead can be run once per deployment at a specified time.

Procedure

  1. Add the command parameters to the spec field of the DeploymentConfig. You can also add an args field, which modifies the command (or the ENTRYPOINT if command does not exist).

    spec:
      containers:
        -
        name: <container_name>
        image: 'image'
        command:
          - '<command>'
        args:
          - '<argument_1>'
          - '<argument_2>'
          - '<argument_3>'

    For example, to execute the java command with the -jar and /opt/app-root/springboots2idemo.jar arguments:

    spec:
      containers:
        -
        name: example-spring-boot
        image: 'image'
        command:
          - java
        args:
          - '-jar'
          - /opt/app-root/springboots2idemo.jar

4.2.1.6. Viewing deployment logs

Procedure

  1. To stream the logs of the latest revision for a given DeploymentConfig:

    $ oc logs -f dc/<name>

    If the latest revision is running or failed, the command returns the logs of the process that is responsible for deploying your pods. If it is successful, it returns the logs from a Pod of your application.

  2. You can also view logs from older failed deployment processes, if and only if these processes (old ReplicationControllers and their deployer Pods) exist and have not been pruned or deleted manually:

    $ oc logs --version=1 dc/<name>

4.2.1.7. Deployment triggers

A DeploymentConfig can contain triggers, which drive the creation of new deployment processes in response to events inside the cluster.

Warning

If no triggers are defined on a DeploymentConfig, a ConfigChange trigger is added by default. If triggers are defined as an empty field, deployments must be started manually.

ConfigChange deployment triggers

The ConfigChange trigger results in a new ReplicationController whenever configuration changes are detected in the Pod template of the DeploymentConfig.

Note

If a ConfigChange trigger is defined on a DeploymentConfig, the first ReplicationController is automatically created soon after the DeploymentConfig itself is created and it is not paused.

ConfigChange deployment trigger

triggers:
  - type: "ConfigChange"

ImageChange deployment triggers

The ImageChange trigger results in a new ReplicationController whenever the content of an imagestreamtag changes (when a new version of the image is pushed).

ImageChange deployment trigger

triggers:
  - type: "ImageChange"
    imageChangeParams:
      automatic: true 1
      from:
        kind: "ImageStreamTag"
        name: "origin-ruby-sample:latest"
        namespace: "myproject"
      containerNames:
        - "helloworld"

1
If the imageChangeParams.automatic field is set to false, the trigger is disabled.

With the above example, when the latest tag value of the origin-ruby-sample imagestream changes and the new image value differs from the current image specified in the DeploymentConfig’s helloworld container, a new ReplicationController is created using the new image for the helloworld container.

Note

If an ImageChange trigger is defined on a DeploymentConfig (with a ConfigChange trigger and automatic=false, or with automatic=true) and the ImageStreamTag pointed by the ImageChange trigger does not exist yet, then the initial deployment process will automatically start as soon as an image is imported or pushed by a build to the ImageStreamTag.

4.2.1.7.1. Setting deployment triggers

Procedure

  1. You can set deployment triggers for a DeploymentConfig using the oc set triggers command. For example, to set a ImageChangeTrigger, use the following command:

    $ oc set triggers dc/<dc_name> \
        --from-image=<project>/<image>:<tag> -c <container_name>

4.2.1.8. Setting deployment resources

Note

This resource is available only if a cluster administrator has enabled the ephemeral storage technology preview. This feature is disabled by default.

A deployment is completed by a Pod that consumes resources (memory, CPU, and ephemeral storage) on a node. By default, Pods consume unbounded node resources. However, if a project specifies default container limits, then Pods consume resources up to those limits.

You can also limit resource use by specifying resource limits as part of the deployment strategy. Deployment resources can be used with the Recreate, Rolling, or Custom deployment strategies.

Procedure

  1. In the following example, each of resources, cpu, memory, and ephemeral-storage is optional:

    type: "Recreate"
    resources:
      limits:
        cpu: "100m" 1
        memory: "256Mi" 2
        ephemeral-storage: "1Gi" 3
    1
    cpu is in CPU units: 100m represents 0.1 CPU units (100 * 1e-3).
    2
    memory is in bytes: 256Mi represents 268435456 bytes (256 * 2 ^ 20).
    3
    ephemeral-storage is in bytes: 1Gi represents 1073741824 bytes (2 ^ 30). This applies only if your cluster administrator enabled the ephemeral storage technology preview.

    However, if a quota has been defined for your project, one of the following two items is required:

    • A resources section set with an explicit requests:

        type: "Recreate"
        resources:
          requests: 1
            cpu: "100m"
            memory: "256Mi"
            ephemeral-storage: "1Gi"
      1
      The requests object contains the list of resources that correspond to the list of resources in the quota.
    • A limit range defined in your project, where the defaults from the LimitRange object apply to Pods created during the deployment process.

    To set deployment resources, choose one of the above options. Otherwise, deploy Pod creation fails, citing a failure to satisfy quota.

4.2.1.9. Scaling manually

In addition to rollbacks, you can exercise fine-grained control over the number of replicas by manually scaling them.

Note

Pods can also be autoscaled using the oc autoscale command.

Procedure

  1. To manually scale a DeploymentConfig, use the oc scale command. For example, the following command sets the replicas in the frontend DeploymentConfig to 3.

    $ oc scale dc frontend --replicas=3

    The number of replicas eventually propagates to the desired and current state of the deployment configured by the DeploymentConfig frontend.

4.2.1.10. Accessing private repositories from DeploymentConfigs

You can add a Secret to your DeploymentConfig so that it can access images from a private repository. This procedure shows the OpenShift Container Platform web console method.

Procedure

  1. Create a new project.
  2. From the Workloads page, create a Secret that contains credentials for accessing a private image repository.
  3. Create a DeploymentConfig.
  4. On the DeploymentConfig editor page, set the Pull Secret and save your changes.

4.2.1.11. Assigning pods to specific nodes

You can use node selectors in conjunction with labeled nodes to control Pod placement.

Cluster administrators can set the default node selector for a project in order to restrict Pod placement to specific nodes. As a developer, you can set a node selector on a Pod configuration to restrict nodes even further.

Procedure

  1. To add a node selector when creating a pod, edit the Pod configuration, and add the nodeSelector value. This can be added to a single Pod configuration, or in a Pod template:

    apiVersion: v1
    kind: Pod
    spec:
      nodeSelector:
        disktype: ssd
    ...

    Pods created when the node selector is in place are assigned to nodes with the specified labels. The labels specified here are used in conjunction with the labels added by a cluster administrator.

    For example, if a project has the type=user-node and region=east labels added to a project by the cluster administrator, and you add the above disktype: ssd label to a Pod, the Pod is only ever scheduled on nodes that have all three labels.

    Note

    Labels can only be set to one value, so setting a node selector of region=west in a Pod configuration that has region=east as the administrator-set default, results in a Pod that will never be scheduled.

4.2.1.12. Running a Pod with a different service account

You can run a Pod with a service account other than the default.

Procedure

  1. Edit the DeploymentConfig:

    $ oc edit dc/<deployment_config>
  2. Add the serviceAccount and serviceAccountName parameters to the spec field, and specify the service account you want to use:

    spec:
      securityContext: {}
      serviceAccount: <service_account>
      serviceAccountName: <service_account>

4.3. Using DeploymentConfig strategies

A deployment strategy is a way to change or upgrade an application. The aim is to make the change without downtime in a way that the user barely notices the improvements.

Because the end user usually accesses the application through a route handled by a router, the deployment strategy can focus on DeploymentConfig features or routing features. Strategies that focus on the DeploymentConfig impact all routes that use the application. Strategies that use router features target individual routes.

Many deployment strategies are supported through the DeploymentConfig, and some additional strategies are supported through router features. DeploymentConfig strategies are discussed in this section.

Choosing a deployment strategy

Consider the following when choosing a deployment strategy:

  • Long-running connections must be handled gracefully.
  • Database conversions can be complex and must be done and rolled back along with the application.
  • If the application is a hybrid of microservices and traditional components, downtime might be required to complete the transition.
  • You must have the infrastructure to do this.
  • If you have a non-isolated test environment, you can break both new and old versions.

A deployment strategy uses readiness checks to determine if a new Pod is ready for use. If a readiness check fails, the DeploymentConfig retries to run the Pod until it times out. The default timeout is 10m, a value set in TimeoutSeconds in dc.spec.strategy.*params.

4.3.1. Rolling strategy

A rolling deployment slowly replaces instances of the previous version of an application with instances of the new version of the application. The Rolling strategy is the default deployment strategy used if no strategy is specified on a DeploymentConfig.

A rolling deployment typically waits for new pods to become ready via a readiness check before scaling down the old components. If a significant issue occurs, the rolling deployment can be aborted.

When to use a Rolling deployment:

  • When you want to take no downtime during an application update.
  • When your application supports having old code and new code running at the same time.

A Rolling deployment means you to have both old and new versions of your code running at the same time. This typically requires that your application handle N-1 compatibility.

Example Rolling strategy definition

strategy:
  type: Rolling
  rollingParams:
    updatePeriodSeconds: 1 1
    intervalSeconds: 1 2
    timeoutSeconds: 120 3
    maxSurge: "20%" 4
    maxUnavailable: "10%" 5
    pre: {} 6
    post: {}

1
The time to wait between individual Pod updates. If unspecified, this value defaults to 1.
2
The time to wait between polling the deployment status after update. If unspecified, this value defaults to 1.
3
The time to wait for a scaling event before giving up. Optional; the default is 600. Here, giving up means automatically rolling back to the previous complete deployment.
4
maxSurge is optional and defaults to 25% if not specified. See the information below the following procedure.
5
maxUnavailable is optional and defaults to 25% if not specified. See the information below the following procedure.
6
pre and post are both lifecycle hooks.

The Rolling strategy:

  1. Executes any pre lifecycle hook.
  2. Scales up the new ReplicationController based on the surge count.
  3. Scales down the old ReplicationController based on the max unavailable count.
  4. Repeats this scaling until the new ReplicationController has reached the desired replica count and the old ReplicationController has been scaled to zero.
  5. Executes any post lifecycle hook.
Important

When scaling down, the Rolling strategy waits for Pods to become ready so it can decide whether further scaling would affect availability. If scaled up Pods never become ready, the deployment process will eventually time out and result in a deployment failure.

The maxUnavailable parameter is the maximum number of Pods that can be unavailable during the update. The maxSurge parameter is the maximum number of Pods that can be scheduled above the original number of Pods. Both parameters can be set to either a percentage (e.g., 10%) or an absolute value (e.g., 2). The default value for both is 25%.

These parameters allow the deployment to be tuned for availability and speed. For example:

  • maxUnavailable*=0 and maxSurge*=20% ensures full capacity is maintained during the update and rapid scale up.
  • maxUnavailable*=10% and maxSurge*=0 performs an update using no extra capacity (an in-place update).
  • maxUnavailable*=10% and maxSurge*=10% scales up and down quickly with some potential for capacity loss.

Generally, if you want fast rollouts, use maxSurge. If you have to take into account resource quota and can accept partial unavailability, use maxUnavailable.

4.3.1.1. Canary deployments

All Rolling deployments in OpenShift Container Platform are canary deployments; a new version (the canary) is tested before all of the old instances are replaced. If the readiness check never succeeds, the canary instance is removed and the DeploymentConfig will be automatically rolled back.

The readiness check is part of the application code and can be as sophisticated as necessary to ensure the new instance is ready to be used. If you must implement more complex checks of the application (such as sending real user workloads to the new instance), consider implementing a Custom deployment or using a blue-green deployment strategy.

4.3.1.2. Creating a Rolling deployment

Rolling deployments are the default type in OpenShift Container Platform. You can create a Rolling deployment using the CLI.

Procedure

  1. Create an application based on the example deployment images found in DockerHub:

    $ oc new-app openshift/deployment-example
  2. If you have the router installed, make the application available via a route (or use the service IP directly)

    $ oc expose svc/deployment-example
  3. Browse to the application at deployment-example.<project>.<router_domain> to verify you see the v1 image.
  4. Scale the DeploymentConfig up to three replicas:

    $ oc scale dc/deployment-example --replicas=3
  5. Trigger a new deployment automatically by tagging a new version of the example as the latest tag:

    $ oc tag deployment-example:v2 deployment-example:latest
  6. In your browser, refresh the page until you see the v2 image.
  7. When using the CLI, the following command shows how many Pods are on version 1 and how many are on version 2. In the web console, the Pods are progressively added to v2 and removed from v1:

    $ oc describe dc deployment-example

During the deployment process, the new ReplicationController is incrementally scaled up. After the new Pods are marked as ready (by passing their readiness check), the deployment process continues.

If the Pods do not become ready, the process aborts, and the DeploymentConfig rolls back to its previous version.

4.3.2. Recreate strategy

The Recreate strategy has basic rollout behavior and supports lifecycle hooks for injecting code into the deployment process.

Example Recreate strategy definition

strategy:
  type: Recreate
  recreateParams: 1
    pre: {} 2
    mid: {}
    post: {}

1
recreateParams are optional.
2
pre, mid, and post are lifecycle hooks.

The Recreate strategy:

  1. Executes any pre lifecycle hook.
  2. Scales down the previous deployment to zero.
  3. Executes any mid lifecycle hook.
  4. Scales up the new deployment.
  5. Executes any post lifecycle hook.
Important

During scale up, if the replica count of the deployment is greater than one, the first replica of the deployment will be validated for readiness before fully scaling up the deployment. If the validation of the first replica fails, the deployment will be considered a failure.

When to use a Recreate deployment:

  • When you must run migrations or other data transformations before your new code starts.
  • When you do not support having new and old versions of your application code running at the same time.
  • When you want to use a RWO volume, which is not supported being shared between multiple replicas.

A Recreate deployment incurs downtime because, for a brief period, no instances of your application are running. However, your old code and new code do not run at the same time.

4.3.3. Custom strategy

The Custom strategy allows you to provide your own deployment behavior.

Example Custom strategy definition

strategy:
  type: Custom
  customParams:
    image: organization/strategy
    command: [ "command", "arg1" ]
    environment:
      - name: ENV_1
        value: VALUE_1

In the above example, the organization/strategy container image provides the deployment behavior. The optional command array overrides any CMD directive specified in the image’s Dockerfile. The optional environment variables provided are added to the execution environment of the strategy process.

Additionally, OpenShift Container Platform provides the following environment variables to the deployment process:

Environment variableDescription

OPENSHIFT_DEPLOYMENT_NAME

The name of the new deployment (a ReplicationController).

OPENSHIFT_DEPLOYMENT_NAMESPACE

The name space of the new deployment.

The replica count of the new deployment will initially be zero. The responsibility of the strategy is to make the new deployment active using the logic that best serves the needs of the user.

Alternatively, use customParams to inject the custom deployment logic into the existing deployment strategies. Provide a custom shell script logic and call the openshift-deploy binary. Users do not have to supply their custom deployer container image; in this case, the default OpenShift Container Platform deployer image is used instead:

strategy:
  type: Rolling
  customParams:
    command:
    - /bin/sh
    - -c
    - |
      set -e
      openshift-deploy --until=50%
      echo Halfway there
      openshift-deploy
      echo Complete

This results in following deployment:

Started deployment #2
--> Scaling up custom-deployment-2 from 0 to 2, scaling down custom-deployment-1 from 2 to 0 (keep 2 pods available, don't exceed 3 pods)
    Scaling custom-deployment-2 up to 1
--> Reached 50% (currently 50%)
Halfway there
--> Scaling up custom-deployment-2 from 1 to 2, scaling down custom-deployment-1 from 2 to 0 (keep 2 pods available, don't exceed 3 pods)
    Scaling custom-deployment-1 down to 1
    Scaling custom-deployment-2 up to 2
    Scaling custom-deployment-1 down to 0
--> Success
Complete

If the custom deployment strategy process requires access to the OpenShift Container Platform API or the Kubernetes API the container that executes the strategy can use the service account token available inside the container for authentication.

4.3.4. Lifecycle hooks

The Rolling and Recreate strategies support lifecycle hooks, or deployment hooks, which allow behavior to be injected into the deployment process at predefined points within the strategy:

Example pre lifecycle hook

pre:
  failurePolicy: Abort
  execNewPod: {} 1

1
execNewPod is a Pod-based lifecycle hook.

Every hook has a failurePolicy, which defines the action the strategy should take when a hook failure is encountered:

Abort

The deployment process will be considered a failure if the hook fails.

Retry

The hook execution should be retried until it succeeds.

Ignore

Any hook failure should be ignored and the deployment should proceed.

Hooks have a type-specific field that describes how to execute the hook. Currently, Pod-based hooks are the only supported hook type, specified by the execNewPod field.

Pod-based lifecycle hook

Pod-based lifecycle hooks execute hook code in a new Pod derived from the template in a DeploymentConfig.

The following simplified example DeploymentConfig uses the Rolling strategy. Triggers and some other minor details are omitted for brevity:

kind: DeploymentConfig
apiVersion: v1
metadata:
  name: frontend
spec:
  template:
    metadata:
      labels:
        name: frontend
    spec:
      containers:
        - name: helloworld
          image: openshift/origin-ruby-sample
  replicas: 5
  selector:
    name: frontend
  strategy:
    type: Rolling
    rollingParams:
      pre:
        failurePolicy: Abort
        execNewPod:
          containerName: helloworld 1
          command: [ "/usr/bin/command", "arg1", "arg2" ] 2
          env: 3
            - name: CUSTOM_VAR1
              value: custom_value1
          volumes:
            - data 4
1
The helloworld name refers to spec.template.spec.containers[0].name.
2
This command overrides any ENTRYPOINT defined by the openshift/origin-ruby-sample image.
3
env is an optional set of environment variables for the hook container.
4
volumes is an optional set of volume references for the hook container.

In this example, the pre hook will be executed in a new Pod using the openshift/origin-ruby-sample image from the helloworld container. The hook Pod has the following properties:

  • The hook command is /usr/bin/command arg1 arg2.
  • The hook container has the CUSTOM_VAR1=custom_value1 environment variable.
  • The hook failure policy is Abort, meaning the deployment process fails if the hook fails.
  • The hook Pod inherits the data volume from the DeploymentConfig Pod.

4.3.4.1. Setting lifecycle hooks

You can set lifecycle hooks, or deployment hooks, for a DeploymentConfig using the CLI.

Procedure

  1. Use the oc set deployment-hook command to set the type of hook you want: --pre, --mid, or --post. For example, to set a pre-deployment hook:

    $ oc set deployment-hook dc/frontend \
        --pre -c helloworld -e CUSTOM_VAR1=custom_value1 \
        -v data --failure-policy=abort -- /usr/bin/command arg1 arg2

4.4. Using route-based deployment strategies

Deployment strategies provide a way for the application to evolve. Some strategies use DeploymentConfigs to make changes that are seen by users of all routes that resolve to the application. Other advanced strategies, such as the ones described in this section, use router features in conjunction with DeploymentConfigs to impact specific routes.

The most common route-based strategy is to use a blue-green deployment. The new version (the blue version) is brought up for testing and evaluation, while the users still use the stable version (the green version). When ready, the users are switched to the blue version. If a problem arises, you can switch back to the green version.

A common alternative strategy is to use A/B versions that are both active at the same time and some users use one version, and some users use the other version. This can be used for experimenting with user interface changes and other features to get user feedback. It can also be used to verify proper operation in a production context where problems impact a limited number of users.

A canary deployment tests the new version but when a problem is detected it quickly falls back to the previous version. This can be done with both of the above strategies.

The route-based deployment strategies do not scale the number of Pods in the services. To maintain desired performance characteristics the deployment configurations might have to be scaled.

4.4.1. Proxy shards and traffic splitting

In production environments, you can precisely control the distribution of traffic that lands on a particular shard. When dealing with large numbers of instances, you can use the relative scale of individual shards to implement percentage based traffic. That combines well with a proxy shard, which forwards or splits the traffic it receives to a separate service or application running elsewhere.

In the simplest configuration, the proxy forwards requests unchanged. In more complex setups, you can duplicate the incoming requests and send to both a separate cluster as well as to a local instance of the application, and compare the result. Other patterns include keeping the caches of a DR installation warm, or sampling incoming traffic for analysis purposes.

Any TCP (or UDP) proxy could be run under the desired shard. Use the oc scale command to alter the relative number of instances serving requests under the proxy shard. For more complex traffic management, consider customizing the OpenShift Container Platform router with proportional balancing capabilities.

4.4.2. N-1 compatibility

Applications that have new code and old code running at the same time must be careful to ensure that data written by the new code can be read and handled (or gracefully ignored) by the old version of the code. This is sometimes called schema evolution and is a complex problem.

This can take many forms: data stored on disk, in a database, in a temporary cache, or that is part of a user’s browser session. While most web applications can support rolling deployments, it is important to test and design your application to handle it.

For some applications, the period of time that old code and new code is running side by side is short, so bugs or some failed user transactions are acceptable. For others, the failure pattern may result in the entire application becoming non-functional.

One way to validate N-1 compatibility is to use an A/B deployment: run the old code and new code at the same time in a controlled way in a test environment, and verify that traffic that flows to the new deployment does not cause failures in the old deployment.

4.4.3. Graceful termination

OpenShift Container Platform and Kubernetes give application instances time to shut down before removing them from load balancing rotations. However, applications must ensure they cleanly terminate user connections as well before they exit.

On shutdown, OpenShift Container Platform sends a TERM signal to the processes in the container. Application code, on receiving SIGTERM, stop accepting new connections. This ensures that load balancers route traffic to other active instances. The application code then waits until all open connections are closed (or gracefully terminate individual connections at the next opportunity) before exiting.

After the graceful termination period expires, a process that has not exited is sent the KILL signal, which immediately ends the process. The terminationGracePeriodSeconds attribute of a Pod or Pod template controls the graceful termination period (default 30 seconds) and may be customized per application as necessary.

4.4.4. Blue-green deployments

Blue-green deployments involve running two versions of an application at the same time and moving traffic from the in-production version (the green version) to the newer version (the blue version). You can use a Rolling strategy or switch services in a route.

Because many applications depend on persistent data, you must have an application that supports N-1 compatibility, which means it shares data and implements live migration between the database, store, or disk by creating two copies of the data layer.

Consider the data used in testing the new version. If it is the production data, a bug in the new version can break the production version.

4.4.4.1. Setting up a blue-green deployment

Blue-green deployments use two DeploymentConfigs. Both are running, and the one in production depends on the service the route specifies, with each DeploymentConfig exposed to a different service.

Note

Routes are intended for web (HTTP and HTTPS) traffic, so this technique is best suited for web applications.

You can create a new route to the new version and test it. When ready, change the service in the production route to point to the new service and the new (blue) version is live.

If necessary, you can roll back to the older (green) version by switching the service back to the previous version.

Procedure

  1. Create two copies of the example application:

    $ oc new-app openshift/deployment-example:v1 --name=example-green
    $ oc new-app openshift/deployment-example:v2 --name=example-blue

    This creates two independent application components: one running the v1 image under the example-green service, and one using the v2 image under the example-blue service.

  2. Create a route that points to the old service:

    $ oc expose svc/example-green --name=bluegreen-example
  3. Browse to the application at example-green.<project>.<router_domain> to verify you see the v1 image.
  4. Edit the route and change the service name to example-blue:

    $ oc patch route/bluegreen-example -p '{"spec":{"to":{"name":"example-blue"}}}'
  5. To verify that the route has changed, refresh the browser until you see the v2 image.

4.4.5. A/B deployments

The A/B deployment strategy lets you try a new version of the application in a limited way in the production environment. You can specify that the production version gets most of the user requests while a limited fraction of requests go to the new version.

Because you control the portion of requests to each version, as testing progresses you can increase the fraction of requests to the new version and ultimately stop using the previous version. As you adjust the request load on each version, the number of Pods in each service might have to be scaled as well to provide the expected performance.

In addition to upgrading software, you can use this feature to experiment with versions of the user interface. Since some users get the old version and some the new, you can evaluate the user’s reaction to the different versions to inform design decisions.

For this to be effective, both the old and new versions must be similar enough that both can run at the same time. This is common with bug fix releases and when new features do not interfere with the old. The versions require N-1 compatibility to properly work together.

OpenShift Container Platform supports N-1 compatibility through the web console as well as the CLI.

4.4.5.1. Load balancing for A/B testing

The user sets up a route with multiple services. Each service handles a version of the application.

Each service is assigned a weight and the portion of requests to each service is the service_weight divided by the sum_of_weights. The weight for each service is distributed to the service’s endpoints so that the sum of the endpoint weights is the service weight.

The route can have up to four services. The weight for the service can be between 0 and 256. When the weight is 0, the service does not participate in load-balancing but continues to serve existing persistent connections. When the service weight is not 0, each endpoint has a minimum weight of 1. Because of this, a service with a lot of endpoints can end up with higher weight than desired. In this case, reduce the number of Pods to get the desired load balance weight.

Procedure

To set up the A/B environment:

  1. Create the two applications and give them different names. Each creates a DeploymentConfig. The applications are versions of the same program; one is usually the current production version and the other the proposed new version:

    $ oc new-app openshift/deployment-example --name=ab-example-a
    $ oc new-app openshift/deployment-example --name=ab-example-b

    Both applications are deployed and services are created.

  2. Make the application available externally via a route. At this point, you can expose either. It can be convenient to expose the current production version first and later modify the route to add the new version.

    $ oc expose svc/ab-example-a

    Browse to the application at ab-example-<project>.<router_domain> to verify that you see the desired version.

  3. When you deploy the route, the router balances the traffic according to the weights specified for the services. At this point, there is a single service with default weight=1 so all requests go to it. Adding the other service as an alternateBackends and adjusting the weights brings the A/B setup to life. This can be done by the oc set route-backends command or by editing the route.

    Setting the oc set route-backend to 0 means the service does not participate in load-balancing, but continues to serve existing persistent connections.

    Note

    Changes to the route just change the portion of traffic to the various services. You might have to scale the DeploymentConfigs to adjust the number of Pods to handle the anticipated loads.

    To edit the route, run:

    $ oc edit route <route_name>
    ...
    metadata:
      name: route-alternate-service
      annotations:
        haproxy.router.openshift.io/balance: roundrobin
    spec:
      host: ab-example.my-project.my-domain
      to:
        kind: Service
        name: ab-example-a
        weight: 10
      alternateBackends:
      - kind: Service
        name: ab-example-b
        weight: 15
    ...
4.4.5.1.1. Managing weights using the web console

Procedure

  1. Navigate to the Route details page (Applications/Routes).
  2. Select Edit from the Actions menu.
  3. Check Split traffic across multiple services.
  4. The Service Weights slider sets the percentage of traffic sent to each service.

    For traffic split between more than two services, the relative weights are specified by integers between 0 and 256 for each service.

    Traffic weightings are shown on the Overview in the expanded rows of the applications between which traffic is split.

4.4.5.1.2. Managing weights using the CLI

Procedure

  1. To manage the services and corresponding weights load balanced by the route, use the oc set route-backends command:

    $ oc set route-backends ROUTENAME \
        [--zero|--equal] [--adjust] SERVICE=WEIGHT[%] [...] [options]

    For example, the following sets ab-example-a as the primary service with weight=198 and ab-example-b as the first alternate service with a weight=2:

    $ oc set route-backends ab-example ab-example-a=198 ab-example-b=2

    This means 99% of traffic is sent to service ab-example-a and 1% to service ab-example-b.

    This command does not scale the DeploymentConfigs. You might be required to do so to have enough Pods to handle the request load.

  2. Run the command with no flags to verify the current configuration:

    $ oc set route-backends ab-example
    NAME                    KIND     TO           WEIGHT
    routes/ab-example       Service  ab-example-a 198 (99%)
    routes/ab-example       Service  ab-example-b 2   (1%)
  3. To alter the weight of an individual service relative to itself or to the primary service, use the --adjust flag. Specifying a percentage adjusts the service relative to either the primary or the first alternate (if you specify the primary). If there are other backends, their weights are kept proportional to the changed.

    For example:

    $ oc set route-backends ab-example --adjust ab-example-a=200 ab-example-b=10
    $ oc set route-backends ab-example --adjust ab-example-b=5%
    $ oc set route-backends ab-example --adjust ab-example-b=+15%

    The --equal flag sets the weight of all services to 100:

    $ oc set route-backends ab-example --equal

    The --zero flag sets the weight of all services to 0. All requests then return with a 503 error.

    Note

    Not all routers may support multiple or weighted backends.

4.4.5.1.3. One service, multiple DeploymentConfigs

Procedure

  1. Create a new application, adding a label ab-example=true that will be common to all shards:

    $ oc new-app openshift/deployment-example --name=ab-example-a

    The application is deployed and a service is created. This is the first shard.

  2. Make the application available via a route (or use the service IP directly):

    $ oc expose svc/ab-example-a --name=ab-example
  3. Browse to the application at ab-example-<project>.<router_domain> to verify you see the v1 image.
  4. Create a second shard based on the same source image and label as the first shard, but with a different tagged version and unique environment variables:

    $ oc new-app openshift/deployment-example:v2 \
        --name=ab-example-b --labels=ab-example=true \
        SUBTITLE="shard B" COLOR="red"
  5. At this point, both sets of Pods are being served under the route. However, because both browsers (by leaving a connection open) and the router (by default, through a cookie) attempt to preserve your connection to a back-end server, you might not see both shards being returned to you.

    To force your browser to one or the other shard:

    1. Use the oc scale command to reduce replicas of ab-example-a to 0.

      $ oc scale dc/ab-example-a --replicas=0

      Refresh your browser to show v2 and shard B (in red).

    2. Scale ab-example-a to 1 replica and ab-example-b to 0:

      $ oc scale dc/ab-example-a --replicas=1; oc scale dc/ab-example-b --replicas=0

      Refresh your browser to show v1 and shard A (in blue).

  6. If you trigger a deployment on either shard, only the Pods in that shard are affected. You can trigger a deployment by changing the SUBTITLE environment variable in either DeploymentConfig:

    $ oc edit dc/ab-example-a

    or

    $ oc edit dc/ab-example-b

Chapter 5. CRDs

5.1. Extending the Kubernetes API with Custom Resource Definitions

This guide describes how cluster administrators can extend their OpenShift Container Platform cluster by creating and managing Custom Resource Definitions (CRDs).

5.1.1. Custom Resource Definitions

In the Kubernetes API, a resource is an endpoint that stores a collection of API objects of a certain kind. For example, the built-in Pods resource contains a collection of Pod objects.

A Custom Resource Definition (CRD) object defines a new, unique object Kind in the cluster and lets the Kubernetes API server handle its entire lifecycle.

Custom Resource (CR) objects are created from CRDs that have been added to the cluster by a cluster administrator, allowing all cluster users to add the new resource type into projects.

When a cluster administrator adds a new CRD to the cluster, the Kubernetes API server reacts by creating a new RESTful resource path that can be accessed by the entire cluster or a single project (namespace) and begins serving the specified CR.

Cluster administrators that want to grant access to the CRD to other users can use cluster role aggregation to grant access to users with the admin, edit, or view default cluster roles. Cluster role aggregation allows the insertion of custom policy rules into these cluster roles. This behavior integrates the new resource into the cluster’s RBAC policy as if it was a built-in resource.

Operators in particular make use of CRDs by packaging them with any required RBAC policy and other software-specific logic. Cluster administrators can also add CRDs manually to the cluster outside of an Operator’s lifecycle, making them available to all users.

Note

While only cluster administrators can create CRDs, developers can create the CR from an existing CRD if they have read and write permission to it.

5.1.2. Creating a Custom Resource Definition

To create Custom Resource (CR) objects, cluster administrators must first create a Custom Resource Definition (CRD).

Prerequisites

  • Access to an OpenShift Container Platform cluster with cluster-admin user privileges.

Procedure

To create a CRD:

  1. Create a YAML file that contains the following field types:

    Example YAML file for a CRD

    apiVersion: apiextensions.k8s.io/v1beta1 1
    kind: CustomResourceDefinition
    metadata:
      name: crontabs.stable.example.com 2
    spec:
      group: stable.example.com 3
      version: v1 4
      scope: Namespaced 5
      names:
        plural: crontabs 6
        singular: crontab 7
        kind: CronTab 8
        shortNames:
        - ct 9

    1
    Use the apiextensions.k8s.io/v1beta1 API.
    2
    Specify a name for the definition. This must be in the <plural-name>.<group> format using the values from the group and plural fields.
    3
    Specify a group name for the API. An API group is a collection of objects that are logically related. For example, all batch objects like Job or ScheduledJob could be in the batch API Group (such as batch.api.example.com). A good practice is to use a fully-qualified-domain name of your organization.
    4
    Specify a version name to be used in the URL. Each API Group can exist in multiple versions. For example: v1alpha, v1beta, v1.
    5
    Specify whether the custom objects are available to a project (Namespaced) or all projects in the cluster (Cluster).
    6
    Specify the plural name to use in the URL. The plural field is the same as a resource in an API URL.
    7
    Specify a singular name to use as an alias on the CLI and for display.
    8
    Specify the kind of objects that can be created. The type can be in CamelCase.
    9
    Specify a shorter string to match your resource on the CLI.
    Note

    By default, a CRD is cluster-scoped and available to all projects.

  2. Create the CRD object:

    $ oc create -f <file_name>.yaml

    A new RESTful API endpoint is created at:

    /apis/<spec:group>/<spec:version>/<scope>/*/<names-plural>/...

    For example, using the example file, the following endpoint is created:

    /apis/stable.example.com/v1/namespaces/*/crontabs/...

    You can now use this endpoint URL to create and manage CRs. The object Kind is based on the spec.kind field of the CRD object you created.

5.1.3. Creating cluster roles for Custom Resource Definitions

Cluster administrators can grant permissions to existing cluster-scoped Custom Resource Definitions (CRDs). If you use the admin, edit, and view default cluster roles, take advantage of cluster role aggregation for their rules.

Important

You must explicitly assign permissions to each of these roles. The roles with more permissions do not inherit rules from roles with fewer permissions. If you assign a rule to a role, you must also assign that verb to roles that have more permissions. For example, if you grant the get crontabs permission to the view role, you must also grant it to the edit and admin roles. The admin or edit role is usually assigned to the user that created a project through the project template.

Prerequisites

  • Create a CRD.

Procedure

  1. Create a cluster role definition file for the CRD. The cluster role definition is a YAML file that contains the rules that apply to each cluster role. The OpenShift Container Platform controller adds the rules that you specify to the default cluster roles.

    Example YAML file for a cluster role definition

    kind: ClusterRole
    apiVersion: rbac.authorization.k8s.io/v1 1
    metadata:
      name: aggregate-cron-tabs-admin-edit 2
      labels:
        rbac.authorization.k8s.io/aggregate-to-admin: "true" 3
        rbac.authorization.k8s.io/aggregate-to-edit: "true" 4
    rules:
    - apiGroups: ["stable.example.com"] 5
      resources: ["crontabs"] 6
      verbs: ["get", "list", "watch", "create", "update", "patch", "delete", "deletecollection"] 7
    ---
    kind: ClusterRole
    apiVersion: rbac.authorization.k8s.io/v1
    metadata:
      name: aggregate-cron-tabs-view 8
      labels:
        # Add these permissions to the "view" default role.
        rbac.authorization.k8s.io/aggregate-to-view: "true" 9
        rbac.authorization.k8s.io/aggregate-to-cluster-reader: "true" 10
    rules:
    - apiGroups: ["stable.example.com"] 11
      resources: ["crontabs"] 12
      verbs: ["get", "list", "watch"] 13

    1
    Use the rbac.authorization.k8s.io/v1 API.
    2 8
    Specify a name for the definition.
    3
    Specify this label to grant permissions to the admin default role.
    4
    Specify this label to grant permissions to the edit default role.
    5 11
    Specify the group name of the CRD.
    6 12
    Specify the plural name of the CRD that these rules apply to.
    7 13
    Specify the verbs that represent the permissions that are granted to the role. For example, apply read and write permissions to the admin and edit roles and only read permission to the view role.
    9
    Specify this label to grant permissions to the view default role.
    10
    Specify this label to grant permissions to the cluster-reader default role.
  2. Create the cluster role:

    $ oc create -f <file_name>.yaml

5.1.4. Creating Custom Resources from a file

After a Custom Resource Definition (CRD) has been added to the cluster, Custom Resources (CRs) can be created with the CLI from a file using the CR specification.

Prerequisites

  • CRD added to the cluster by a cluster administrator.

Procedure

  1. Create a YAML file for the CR. In the following example definition, the cronSpec and image custom fields are set in a CR of Kind: CronTab. The Kind comes from the spec.kind field of the CRD object.

    Example YAML file for a CR

    apiVersion: "stable.example.com/v1" 1
    kind: CronTab 2
    metadata:
      name: my-new-cron-object 3
      finalizers: 4
      - finalizer.stable.example.com
    spec: 5
      cronSpec: "* * * * /5"
      image: my-awesome-cron-image

    1
    Specify the group name and API version (name/version) from the Custom Resource Definition.
    2
    Specify the type in the CRD.
    3
    Specify a name for the object.
    4
    Specify the finalizers for the object, if any. Finalizers allow controllers to implement conditions that must be completed before the object can be deleted.
    5
    Specify conditions specific to the type of object.
  2. After you create the file, create the object:

    $ oc create -f <file_name>.yaml

5.1.5. Inspecting Custom Resources

You can inspect Custom Resource (CR) objects that exist in your cluster using the CLI.

Prerequisites

  • A CR object exists in a namespace to which you have access.

Procedure

  1. To get information on a specific Kind of a CR, run:

    $ oc get <kind>

    For example:

    $ oc get crontab
    
    NAME                 KIND
    my-new-cron-object   CronTab.v1.stable.example.com

    Resource names are not case-sensitive, and you can use either the singular or plural forms defined in the CRD, as well as any short name. For example:

    $ oc get crontabs
    $ oc get crontab
    $ oc get ct
  2. You can also view the raw YAML data for a CR:

    $ oc get <kind> -o yaml
    $ oc get ct -o yaml
    
    apiVersion: v1
    items:
    - apiVersion: stable.example.com/v1
      kind: CronTab
      metadata:
        clusterName: ""
        creationTimestamp: 2017-05-31T12:56:35Z
        deletionGracePeriodSeconds: null
        deletionTimestamp: null
        name: my-new-cron-object
        namespace: default
        resourceVersion: "285"
        selfLink: /apis/stable.example.com/v1/namespaces/default/crontabs/my-new-cron-object
        uid: 9423255b-4600-11e7-af6a-28d2447dc82b
      spec:
        cronSpec: '* * * * /5' 1
        image: my-awesome-cron-image 2
    1 2
    Custom data from the YAML that you used to create the object displays.

5.2. Managing resources from Custom Resource Definitions

This guide describes how developers can manage Custom Resources (CRs) that come from Custom Resource Definitions (CRDs).

5.2.1. Custom Resource Definitions

In the Kubernetes API, a resource is an endpoint that stores a collection of API objects of a certain kind. For example, the built-in Pods resource contains a collection of Pod objects.

A Custom Resource Definition (CRD) object defines a new, unique object Kind in the cluster and lets the Kubernetes API server handle its entire lifecycle.

Custom Resource (CR) objects are created from CRDs that have been added to the cluster by a cluster administrator, allowing all cluster users to add the new resource type into projects.

Operators in particular make use of CRDs by packaging them with any required RBAC policy and other software-specific logic. Cluster administrators can also add CRDs manually to the cluster outside of an Operator’s lifecycle, making them available to all users.

Note

While only cluster administrators can create CRDs, developers can create the CR from an existing CRD if they have read and write permission to it.

5.2.2. Creating Custom Resources from a file

After a Custom Resource Definition (CRD) has been added to the cluster, Custom Resources (CRs) can be created with the CLI from a file using the CR specification.

Prerequisites

  • CRD added to the cluster by a cluster administrator.

Procedure

  1. Create a YAML file for the CR. In the following example definition, the cronSpec and image custom fields are set in a CR of Kind: CronTab. The Kind comes from the spec.kind field of the CRD object.

    Example YAML file for a CR

    apiVersion: "stable.example.com/v1" 1
    kind: CronTab 2
    metadata:
      name: my-new-cron-object 3
      finalizers: 4
      - finalizer.stable.example.com
    spec: 5
      cronSpec: "* * * * /5"
      image: my-awesome-cron-image

    1
    Specify the group name and API version (name/version) from the Custom Resource Definition.
    2
    Specify the type in the CRD.
    3
    Specify a name for the object.
    4
    Specify the finalizers for the object, if any. Finalizers allow controllers to implement conditions that must be completed before the object can be deleted.
    5
    Specify conditions specific to the type of object.
  2. After you create the file, create the object:

    $ oc create -f <file_name>.yaml

5.2.3. Inspecting Custom Resources

You can inspect Custom Resource (CR) objects that exist in your cluster using the CLI.

Prerequisites

  • A CR object exists in a namespace to which you have access.

Procedure

  1. To get information on a specific Kind of a CR, run:

    $ oc get <kind>

    For example:

    $ oc get crontab
    
    NAME                 KIND
    my-new-cron-object   CronTab.v1.stable.example.com

    Resource names are not case-sensitive, and you can use either the singular or plural forms defined in the CRD, as well as any short name. For example:

    $ oc get crontabs
    $ oc get crontab
    $ oc get ct
  2. You can also view the raw YAML data for a CR:

    $ oc get <kind> -o yaml
    $ oc get ct -o yaml
    
    apiVersion: v1
    items:
    - apiVersion: stable.example.com/v1
      kind: CronTab
      metadata:
        clusterName: ""
        creationTimestamp: 2017-05-31T12:56:35Z
        deletionGracePeriodSeconds: null
        deletionTimestamp: null
        name: my-new-cron-object
        namespace: default
        resourceVersion: "285"
        selfLink: /apis/stable.example.com/v1/namespaces/default/crontabs/my-new-cron-object
        uid: 9423255b-4600-11e7-af6a-28d2447dc82b
      spec:
        cronSpec: '* * * * /5' 1
        image: my-awesome-cron-image 2
    1 2
    Custom data from the YAML that you used to create the object displays.

Chapter 6. Quotas

6.1. Resource quotas per project

A resource quota, defined by a ResourceQuota object, provides constraints that limit aggregate resource consumption per project. It can limit the quantity of objects that can be created in a project by type, as well as the total amount of compute resources and storage that may be consumed by resources in that project.

This guide describes how resource quotas work, how cluster administrators can set and manage resource quotas on a per project basis, and how developers and cluster administrators can view them.

6.1.1. Resources managed by quotas

The following describes the set of compute resources and object types that can be managed by a quota.

Note

A pod is in a terminal state if status.phase in (Failed, Succeeded) is true.

Table 6.1. Compute resources managed by quota

Resource NameDescription

cpu

The sum of CPU requests across all pods in a non-terminal state cannot exceed this value. cpu and requests.cpu are the same value and can be used interchangeably.

memory

The sum of memory requests across all pods in a non-terminal state cannot exceed this value. memory and requests.memory are the same value and can be used interchangeably.

ephemeral-storage

The sum of local ephemeral storage requests across all pods in a non-terminal state cannot exceed this value. ephemeral-storage and requests.ephemeral-storage are the same value and can be used interchangeably. This resource is available only if you enabled the ephemeral storage technology preview. This feature is disabled by default.

requests.cpu

The sum of CPU requests across all pods in a non-terminal state cannot exceed this value. cpu and requests.cpu are the same value and can be used interchangeably.

requests.memory

The sum of memory requests across all pods in a non-terminal state cannot exceed this value. memory and requests.memory are the same value and can be used interchangeably.

requests.ephemeral-storage

The sum of ephemeral storage requests across all pods in a non-terminal state cannot exceed this value. ephemeral-storage and requests.ephemeral-storage are the same value and can be used interchangeably. This resource is available only if you enabled the ephemeral storage technology preview. This feature is disabled by default.

limits.cpu

The sum of CPU limits across all pods in a non-terminal state cannot exceed this value.

limits.memory

The sum of memory limits across all pods in a non-terminal state cannot exceed this value.

limits.ephemeral-storage

The sum of ephemeral storage limits across all pods in a non-terminal state cannot exceed this value. This resource is available only if you enabled the ephemeral storage technology preview. This feature is disabled by default.

Table 6.2. Storage resources managed by quota

Resource NameDescription

requests.storage

The sum of storage requests across all persistent volume claims in any state cannot exceed this value.

persistentvolumeclaims

The total number of persistent volume claims that can exist in the project.

<storage-class-name>.storageclass.storage.k8s.io/requests.storage

The sum of storage requests across all persistent volume claims in any state that have a matching storage class, cannot exceed this value.

<storage-class-name>.storageclass.storage.k8s.io/persistentvolumeclaims

The total number of persistent volume claims with a matching storage class that can exist in the project.

Table 6.3. Object counts managed by quota

Resource NameDescription

pods

The total number of pods in a non-terminal state that can exist in the project.

replicationcontrollers

The total number of ReplicationControllers that can exist in the project.

resourcequotas

The total number of resource quotas that can exist in the project.

services

The total number of services that can exist in the project.

services.loadbalancers

The total number of services of type LoadBalancer that can exist in the project.

services.nodeports

The total number of services of type NodePort that can exist in the project.

secrets

The total number of secrets that can exist in the project.

configmaps

The total number of ConfigMap objects that can exist in the project.

persistentvolumeclaims

The total number of persistent volume claims that can exist in the project.

openshift.io/imagestreams

The total number of imagestreams that can exist in the project.

6.1.2. Quota scopes

Each quota can have an associated set of scopes. A quota only measures usage for a resource if it matches the intersection of enumerated scopes.

Adding a scope to a quota restricts the set of resources to which that quota can apply. Specifying a resource outside of the allowed set results in a validation error.

Scope

Description

Terminating

Match pods where spec.activeDeadlineSeconds >= 0.

NotTerminating

Match pods where spec.activeDeadlineSeconds is nil.

BestEffort

Match pods that have best effort quality of service for either cpu or memory.

NotBestEffort

Match pods that do not have best effort quality of service for cpu and memory.

A BestEffort scope restricts a quota to limiting the following resources:

  • pods

A Terminating, NotTerminating, and NotBestEffort scope restricts a quota to tracking the following resources:

  • pods
  • memory
  • requests.memory
  • limits.memory
  • cpu
  • requests.cpu
  • limits.cpu
  • ephemeral-storage
  • requests.ephemeral-storage
  • limits.ephemeral-storage
Note

Ephemeral storage requests and limits apply only if you enabled the ephemeral storage technology preview. This feature is disabled by default.

6.1.3. Quota enforcement

After a resource quota for a project is first created, the project restricts the ability to create any new resources that may violate a quota constraint until it has calculated updated usage statistics.

After a quota is created and usage statistics are updated, the project accepts the creation of new content. When you create or modify resources, your quota usage is incremented immediately upon the request to create or modify the resource.

When you delete a resource, your quota use is decremented during the next full recalculation of quota statistics for the project. A configurable amount of time determines how long it takes to reduce quota usage statistics to their current observed system value.

If project modifications exceed a quota usage limit, the server denies the action, and an appropriate error message is returned to the user explaining the quota constraint violated, and what their currently observed usage statistics are in the system.

6.1.4. Requests versus limits

When allocating compute resources, each container might specify a request and a limit value each for CPU, memory, and ephemeral storage. Quotas can restrict any of these values.

If the quota has a value specified for requests.cpu or requests.memory, then it requires that every incoming container make an explicit request for those resources. If the quota has a value specified for limits.cpu or limits.memory, then it requires that every incoming container specify an explicit limit for those resources.

6.1.5. Sample resource quota definitions

core-object-counts.yaml

apiVersion: v1
kind: ResourceQuota
metadata:
  name: core-object-counts
spec:
  hard:
    configmaps: "10" 1
    persistentvolumeclaims: "4" 2
    replicationcontrollers: "20" 3
    secrets: "10" 4
    services: "10" 5
    services.loadbalancers: "2" 6

1
The total number of ConfigMap objects that can exist in the project.
2
The total number of persistent volume claims (PVCs) that can exist in the project.
3
The total number of ReplicationControllers that can exist in the project.
4
The total number of secrets that can exist in the project.
5
The total number of services that can exist in the project.
6
The total number of services of type LoadBalancer that can exist in the project.

openshift-object-counts.yaml

apiVersion: v1
kind: ResourceQuota
metadata:
  name: openshift-object-counts
spec:
  hard:
    openshift.io/imagestreams: "10" 1

1
The total number of imagestreams that can exist in the project.

compute-resources.yaml

apiVersion: v1
kind: ResourceQuota
metadata:
  name: compute-resources
spec:
  hard:
    pods: "4" 1
    requests.cpu: "1" 2
    requests.memory: 1Gi 3
    requests.ephemeral-storage: 2Gi 4
    limits.cpu: "2" 5
    limits.memory: 2Gi 6
    limits.ephemeral-storage: 4Gi 7

1
The total number of pods in a non-terminal state that can exist in the project.
2
Across all pods in a non-terminal state, the sum of CPU requests cannot exceed 1 core.
3
Across all pods in a non-terminal state, the sum of memory requests cannot exceed 1Gi.
4
Across all pods in a non-terminal state, the sum of ephemeral storage requests cannot exceed 2Gi.
5
Across all pods in a non-terminal state, the sum of CPU limits cannot exceed 2 cores.
6
Across all pods in a non-terminal state, the sum of memory limits cannot exceed 2Gi.
7
Across all pods in a non-terminal state, the sum of ephemeral storage limits cannot exceed 4Gi.

besteffort.yaml

apiVersion: v1
kind: ResourceQuota
metadata:
  name: besteffort
spec:
  hard:
    pods: "1" 1
  scopes:
  - BestEffort 2

1
The total number of pods in a non-terminal state with BestEffort quality of service that can exist in the project.
2
Restricts the quota to only matching pods that have BestEffort quality of service for either memory or CPU.

compute-resources-long-running.yaml

apiVersion: v1
kind: ResourceQuota
metadata:
  name: compute-resources-long-running
spec:
  hard:
    pods: "4" 1
    limits.cpu: "4" 2
    limits.memory: "2Gi" 3
    limits.ephemeral-storage: "4Gi" 4
  scopes:
  - NotTerminating 5

1
The total number of pods in a non-terminal state.
2
Across all pods in a non-terminal state, the sum of CPU limits cannot exceed this value.
3
Across all pods in a non-terminal state, the sum of memory limits cannot exceed this value.
4
Across all pods in a non-terminal state, the sum of ephemeral storage limits cannot exceed this value.
5
Restricts the quota to only matching pods where spec.activeDeadlineSeconds is set to nil. Build pods will fall under NotTerminating unless the RestartNever policy is applied.

compute-resources-time-bound.yaml

apiVersion: v1
kind: ResourceQuota
metadata:
  name: compute-resources-time-bound
spec:
  hard:
    pods: "2" 1
    limits.cpu: "1" 2
    limits.memory: "1Gi" 3
    limits.ephemeral-storage: "1Gi" 4
  scopes:
  - Terminating 5

1
The total number of pods in a non-terminal state.
2
Across all pods in a non-terminal state, the sum of CPU limits cannot exceed this value.
3
Across all pods in a non-terminal state, the sum of memory limits cannot exceed this value.
4
Across all pods in a non-terminal state, the sum of ephemeral storage limits cannot exceed this value.
5
Restricts the quota to only matching pods where spec.activeDeadlineSeconds >=0. For example, this quota would charge for build or deployer pods, but not long running pods like a web server or database.

storage-consumption.yaml

apiVersion: v1
kind: ResourceQuota
metadata:
  name: storage-consumption
spec:
  hard:
    persistentvolumeclaims: "10" 1
    requests.storage: "50Gi" 2
    gold.storageclass.storage.k8s.io/requests.storage: "10Gi" 3
    silver.storageclass.storage.k8s.io/requests.storage: "20Gi" 4
    silver.storageclass.storage.k8s.io/persistentvolumeclaims: "5" 5
    bronze.storageclass.storage.k8s.io/requests.storage: "0" 6
    bronze.storageclass.storage.k8s.io/persistentvolumeclaims: "0" 7

1
The total number of persistent volume claims in a project
2
Across all persistent volume claims in a project, the sum of storage requested cannot exceed this value.
3
Across all persistent volume claims in a project, the sum of storage requested in the gold storage class cannot exceed this value.
4
Across all persistent volume claims in a project, the sum of storage requested in the silver storage class cannot exceed this value.
5
Across all persistent volume claims in a project, the total number of claims in the silver storage class cannot exceed this value.
6
Across all persistent volume claims in a project, the sum of storage requested in the bronze storage class cannot exceed this value. When this is set to 0, it means bronze storage class cannot request storage.
7
Across all persistent volume claims in a project, the sum of storage requested in the bronze storage class cannot exceed this value. When this is set to 0, it means bronze storage class cannot create claims.

6.1.6. Creating a quota

You can create a quota to constrain resource usage in a given project.

Procedure

  1. Define the quota in a file.
  2. Use the file to create the quota and apply it to a project:

    $ oc create -f <file> [-n <project_name>]

    For example:

    $ oc create -f core-object-counts.yaml -n demoproject

6.1.6.1. Creating object count quotas

You can create an object count quota for all OpenShift Container Platform standard namespaced resource types, such as BuildConfig, and DeploymentConfig. An object quota count places a defined quota on all standard namespaced resource types.

When using a resource quota, an object is charged against the quota if it exists in server storage. These types of quotas are useful to protect against exhaustion of storage resources.

Procedure

To configure an object count quota for a resource:

  1. Run the following command:

    $ oc create quota <name> \
        --hard=count/<resource>.<group>=<quota>,count/<resource>.<group>=<quota> 1
    1
    <resource> is the name of the resource, and <group> is the API group, if applicable. Use the oc api-resources command for a list of resources and their associated API groups.

    For example:

    $ oc create quota test \
        --hard=count/deployments.extensions=2,count/replicasets.extensions=4,count/pods=3,count/secrets=4
    resourcequota "test" created

    This example limits the listed resources to the hard limit in each project in the cluster.

  2. Verify that the quota was created:

    $ oc describe quota test
    Name:                         test
    Namespace:                    quota
    Resource                      Used  Hard
    --------                      ----  ----
    count/deployments.extensions  0     2
    count/pods                    0     3
    count/replicasets.extensions  0     4
    count/secrets                 0     4

6.1.6.2. Setting resource quota for extended resources

Overcommitment of resources is not allowed for extended resources, so you must specify requests and limits for the same extended resource in a quota. Currently, only quota items with the prefix requests. is allowed for extended resources. The following is an example scenario of how to set resource quota for the GPU resource nvidia.com/gpu.

Procedure

  1. Determine how many GPUs are available on a node in your cluster. For example:

    # oc describe node ip-172-31-27-209.us-west-2.compute.internal | egrep 'Capacity|Allocatable|gpu'
                        openshift.com/gpu-accelerator=true
    Capacity:
     nvidia.com/gpu:  2
    Allocatable:
     nvidia.com/gpu:  2
      nvidia.com/gpu  0           0

    In this example, 2 GPUs are available.

  2. Set a quota in the namespace nvidia. In this example, the quota is 1:

    # cat gpu-quota.yaml
    apiVersion: v1
    kind: ResourceQuota
    metadata:
      name: gpu-quota
      namespace: nvidia
    spec:
      hard:
        requests.nvidia.com/gpu: 1
  3. Create the quota:

    # oc create -f gpu-quota.yaml
    resourcequota/gpu-quota created
  4. Verify that the namespace has the correct quota set:

    # oc describe quota gpu-quota -n nvidia
    Name:                    gpu-quota
    Namespace:               nvidia
    Resource                 Used  Hard
    --------                 ----  ----
    requests.nvidia.com/gpu  0     1
  5. Run a pod that asks for a single GPU:

    # oc create -f gpu-pod.yaml
    apiVersion: v1
    kind: Pod
    metadata:
      generateName: gpu-pod-
      namespace: nvidia
    spec:
      restartPolicy: OnFailure
      containers:
      - name: rhel7-gpu-pod
        image: rhel7
        env:
          - name: NVIDIA_VISIBLE_DEVICES
            value: all
          - name: NVIDIA_DRIVER_CAPABILITIES
            value: "compute,utility"
          - name: NVIDIA_REQUIRE_CUDA
            value: "cuda>=5.0"
        command: ["sleep"]
        args: ["infinity"]
        resources:
          limits:
            nvidia.com/gpu: 1
  6. Verify that the pod is running:

    # oc get pods
    NAME              READY     STATUS      RESTARTS   AGE
    gpu-pod-s46h7     1/1       Running     0          1m
  7. Verify that the quota Used counter is correct:

    # oc describe quota gpu-quota -n nvidia
    Name:                    gpu-quota
    Namespace:               nvidia
    Resource                 Used  Hard
    --------                 ----  ----
    requests.nvidia.com/gpu  1     1
  8. Attempt to create a second GPU pod in the nvidia namespace. This is technically available on the node because it has 2 GPUs:

    # oc create -f gpu-pod.yaml
    Error from server (Forbidden): error when creating "gpu-pod.yaml": pods "gpu-pod-f7z2w" is forbidden: exceeded quota: gpu-quota, requested: requests.nvidia.com/gpu=1, used: requests.nvidia.com/gpu=1, limited: requests.nvidia.com/gpu=1

    This Forbidden error message is expected because you have a quota of 1 GPU and this pod tried to allocate a second GPU, which exceeds its quota.

6.1.7. Viewing a quota

You can view usage statistics related to any hard limits defined in a project’s quota by navigating in the web console to the project’s Quota page.

You can also use the CLI to view quota details.

Procedure

  1. Get the list of quotas defined in the project. For example, for a project called demoproject:

    $ oc get quota -n demoproject
    NAME                AGE
    besteffort          11m
    compute-resources   2m
    core-object-counts  29m
  2. Describe the quota you are interested in, for example the core-object-counts quota:

    $ oc describe quota core-object-counts -n demoproject
    Name:			core-object-counts
    Namespace:		demoproject
    Resource		Used	Hard
    --------		----	----
    configmaps		3	10
    persistentvolumeclaims	0	4
    replicationcontrollers	3	20
    secrets			9	10
    services		2	10

6.1.8. Configuring quota synchronization period

When a set of resources are deleted, but before quota usage is restored, a user might encounter problems when attempting to reuse the resources. The synchronization time frame of resources is determined by the resource-quota-sync-period setting, which can be configured by a cluster administrator.

Adjusting the regeneration time can be helpful for creating resources and determining resource usage when automation is used.

Note

The resource-quota-sync-period setting is designed to balance system performance. Reducing the sync period can result in a heavy load on the master.

Procedure

To configure the quota synchronization period:

  1. Edit the Kubernetes controller manager.

    $ oc edit kubecontrollermanager cluster
  2. Change the unsupportedconfigOverrides field to have the following settings, specifying the amount of time, in seconds, for the resource-quota-sync-period field:

      unsupportedConfigOverrides:
        extendedArguments:
          resource-quota-sync-period:
          - 60s

6.2. Resource quotas across multiple projects

A multi-project quota, defined by a ClusterResourceQuota object, allows quotas to be shared across multiple projects. Resources used in each selected project are aggregated and that aggregate is used to limit resources across all the selected projects.

This guide describes how cluster administrators can set and manage resource quotas across multiple projects.

6.2.1. Selecting multiple projects during quota creation

When creating quotas, you can select multiple projects based on annotation selection, label selection, or both.

Procedure

  1. To select projects based on annotations, run the following command:

    $ oc create clusterquota for-user \
         --project-annotation-selector openshift.io/requester=<user_name> \
         --hard pods=10 \
         --hard secrets=20

    This creates the following ClusterResourceQuota object:

    apiVersion: v1
    kind: ClusterResourceQuota
    metadata:
      name: for-user
    spec:
      quota: 1
        hard:
          pods: "10"
          secrets: "20"
      selector:
        annotations: 2
          openshift.io/requester: <user_name>
        labels: null 3
    status:
      namespaces: 4
      - namespace: ns-one
        status:
          hard:
            pods: "10"
            secrets: "20"
          used:
            pods: "1"
            secrets: "9"
      total: 5
        hard:
          pods: "10"
          secrets: "20"
        used:
          pods: "1"
          secrets: "9"
    1
    The ResourceQuotaSpec object that will be enforced over the selected projects.
    2
    A simple key-value selector for annotations.
    3
    A label selector that can be used to select projects.
    4
    A per-namespace map that describes current quota usage in each selected project.
    5
    The aggregate usage across all selected projects.

    This multi-project quota document controls all projects requested by <user_name> using the default project request endpoint. You are limited to 10 pods and 20 secrets.

  2. Similarly, to select projects based on labels, run this command:

    $  oc create clusterresourcequota for-name \ 1
        --project-label-selector=name=frontend \ 2
        --hard=pods=10 --hard=secrets=20
    1
    Both clusterresourcequota and clusterquota are aliases of the same command. for-name is the name of the ClusterResourceQuota object.
    2
    To select projects by label, provide a key-value pair by using the format --project-label-selector=key=value.

    This creates the following ClusterResourceQuota object definition:

    apiVersion: v1
    kind: ClusterResourceQuota
    metadata:
      creationTimestamp: null
      name: for-name
    spec:
      quota:
        hard:
          pods: "10"
          secrets: "20"
      selector:
        annotations: null
        labels:
          matchLabels:
            name: frontend

6.2.2. Viewing applicable ClusterResourceQuotas

A project administrator is not allowed to create or modify the multi-project quota that limits his or her project, but the administrator is allowed to view the multi-project quota documents that are applied to his or her project. The project administrator can do this via the AppliedClusterResourceQuota resource.

Procedure

  1. To view quotas applied to a project, run:

    $ oc describe AppliedClusterResourceQuota

    For example:

    Name:   for-user
    Namespace:  <none>
    Created:  19 hours ago
    Labels:   <none>
    Annotations:  <none>
    Label Selector: <null>
    AnnotationSelector: map[openshift.io/requester:<user-name>]
    Resource  Used  Hard
    --------  ----  ----
    pods        1     10
    secrets     9     20

6.2.3. Selection granularity

Because of the locking consideration when claiming quota allocations, the number of active projects selected by a multi-project quota is an important consideration. Selecting more than 100 projects under a single multi-project quota can have detrimental effects on API server responsiveness in those projects.

Chapter 7. Idling applications

Cluster administrators can idle applications to reduce resource consumption. This is useful when the cluster is deployed on a public cloud where cost is related to resource consumption.

If any scalable resources are not in use, OpenShift Container Platform discovers and idles them by scaling their replicas to 0. The next time network traffic is directed to the resources, the resources are unidled by scaling up the replicas, and normal operation continues.

Applications are made of services, as well as other scalable resources, such as DeploymentConfigs. The action of idling an application involves idling all associated resources.

7.1. Idling applications

Idling an application involves finding the scalable resources (deployment configurations, replication controllers, and others) associated with a service. Idling an application finds the service and marks it as idled, scaling down the resources to zero replicas.

You can use the oc idle command to idle a single service, or use the --resource-names-file option to idle multiple services.

7.1.1. Idling a single service

Procedure

  1. To idle a single service, run:

    $ oc idle <service>

7.1.2. Idling multiple services

Idling multiple services is helpful if an application spans across a set of services within a project, or when idling multiple services in conjunction with a script in order to idle multiple applications in bulk within the same project.

Procedure

  1. Create a file containing a list of the services, each on their own line.
  2. Idle the services using the --resource-names-file option:

    $ oc idle --resource-names-file <filename>
Note

The idle command is limited to a single project. For idling applications across a cluster, run the idle command for each project individually.

7.2. Unidling applications

Application services become active again when they receive network traffic and are scaled back up their previous state. This includes both traffic to the services and traffic passing through routes.

Applications can also be manually unidled by scaling up the resources.

Procedure

  1. To scale up a DeploymentConfig, run:

    $ oc scale --replicas=1 dc <dc_name>
Note

Automatic unidling by a router is currently only supported by the default HAProxy router.

Chapter 8. Pruning objects to reclaim resources

Over time, API objects created in OpenShift Container Platform can accumulate in the cluster’s etcd data store through normal user operations, such as when building and deploying applications.

Cluster administrators can periodically prune older versions of objects from the cluster that are no longer required. For example, by pruning images you can delete older images and layers that are no longer in use, but are still taking up disk space.

8.1. Basic pruning operations

The CLI groups prune operations under a common parent command:

$ oc adm prune <object_type> <options>

This specifies:

  • The <object_type> to perform the action on, such as groups, builds, deployments, or images.
  • The <options> supported to prune that object type.

8.2. Pruning groups

To prune groups records from an external provider, administrators can run the following command:

$ oc adm prune groups \
    --sync-config=path/to/sync/config [<options>]

Table 8.1. Prune groups CLI configuration options

OptionsDescription

--confirm

Indicate that pruning should occur, instead of performing a dry-run.

--blacklist

Path to the group blacklist file.

--whitelist

Path to the group whitelist file.

--sync-config

Path to the synchronization configuration file.

To see the groups that the prune command deletes:

$ oc adm prune groups --sync-file=ldap-sync-config.yaml

To perform the prune operation:

$ oc adm prune groups --sync-file=ldap-sync-config.yaml --confirm

8.3. Pruning deployments

In order to prune deployments that are no longer required by the system due to age and status, administrators can run the following command:

$ oc adm prune deployments [<options>]

Table 8.2. Prune deployments CLI configuration options

OptionDescription

--confirm

Indicate that pruning should occur, instead of performing a dry-run.

--orphans

Prune all deployments that no longer have a DeploymentConfig, has status is Complete or Failed, and has a replica count of zero.

--keep-complete=<N>

Per DeploymentConfig, keep the last N deployments that have a status of Complete and replica count of zero. (default 5)

--keep-failed=<N>

Per DeploymentConfig, keep the last N deployments that have a status of Failed and replica count of zero. (default 1)

--keep-younger-than=<duration>

Do not prune any object that is younger than <duration> relative to the current time. (default 60m) Valid units of measurement include nanoseconds (ns), microseconds (us), milliseconds (ms), seconds (s), minutes (m), and hours (h).

To see what a pruning operation would delete:

$ oc adm prune deployments --orphans --keep-complete=5 --keep-failed=1 \
    --keep-younger-than=60m

To actually perform the prune operation:

$ oc adm prune deployments --orphans --keep-complete=5 --keep-failed=1 \
    --keep-younger-than=60m --confirm

8.4. Pruning builds

In order to prune builds that are no longer required by the system due to age and status, administrators can run the following command:

$ oc adm prune builds [<options>]

Table 8.3. Prune builds CLI configuration options

OptionDescription

--confirm

Indicate that pruning should occur, instead of performing a dry-run.

--orphans

Prune all builds whose Build Configuration no longer exists, status is complete, failed, error, or canceled.

--keep-complete=<N>

Per Build Configuration, keep the last N builds whose status is complete (default 5).

--keep-failed=<N>

Per Build Configuration, keep the last N builds whose status is failed, error, or canceled (default 1).

--keep-younger-than=<duration>

Do not prune any object that is younger than <duration> relative to the current time (default 60m).

To see what a pruning operation would delete:

$ oc adm prune builds --orphans --keep-complete=5 --keep-failed=1 \
    --keep-younger-than=60m

To actually perform the prune operation:

$ oc adm prune builds --orphans --keep-complete=5 --keep-failed=1 \
    --keep-younger-than=60m --confirm
Note

Developers can enable automatic build pruning by modifying their Build Configuration.

8.5. Pruning images

In order to prune images that are no longer required by the system due to age, status, or exceed limits, administrators can run the following command:

$ oc adm prune images [<options>]

Currently, to prune images you must first log in to the CLI as a user with an access token. The user must also have the cluster role system:image-pruner or greater (for example, cluster-admin).

Pruning images removes data from the integrated registry unless --prune-registry=false is used. For this operation to work properly, the registry must be configured with storage:delete:enabled set to true.

Pruning images with the --namespace flag does not remove images, only image streams. Images are non-namespaced resources. Therefore, limiting pruning to a particular namespace makes it impossible to calculate their current usage.

By default, the integrated registry caches blobs metadata to reduce the number of requests to storage, and increase the speed of processing the request. Pruning does not update the integrated registry cache. Images pushed after pruning that contain pruned layers will be broken, because the pruned layers that have metadata in the cache will not be pushed. Therefore, it is necessary to clear the cache after pruning. This can be accomplished by redeploying the registry:

$ oc rollout latest dc/docker-registry

If the integrated registry uses a Redis cache, you must clean the database manually.

If redeploying the registry after pruning is not an option, then you must permanently disable the cache.

oc adm prune images operations require a route for your registry. Registry routes are not created by default. See Image Registry Operator in OpenShift Container Platform for information on how to create a registry route and see Exposing the registry for details on how to expose the registry service.

Table 8.4. Prune images CLI configuration options

OptionDescription

--all

Include images that were not pushed to the registry, but have been mirrored by pullthrough. This is on by default. To limit the pruning to images that were pushed to the integrated registry, pass --all=false.

--certificate-authority

The path to a certificate authority file to use when communicating with the OpenShift Container Platform-managed registries. Defaults to the certificate authority data from the current user’s configuration file. If provided, a secure connection is initiated.

--confirm

Indicate that pruning should occur, instead of performing a dry-run. This requires a valid route to the integrated container image registry. If this command is run outside of the cluster network, the route must be provided using --registry-url.

--force-insecure

Use caution with this option. Allow an insecure connection to the container registry that is hosted via HTTP or has an invalid HTTPS certificate.

--keep-tag-revisions=<N>

For each imagestream, keep up to at most N image revisions per tag (default 3).

--keep-younger-than=<duration>

Do not prune any image that is younger than <duration> relative to the current time. Do not prune any image that is referenced by any other object that is younger than <duration> relative to the current time (default 60m).

--prune-over-size-limit

Prune each image that exceeds the smallest limit defined in the same project. This flag cannot be combined with --keep-tag-revisions nor --keep-younger-than.

--registry-url

The address to use when contacting the registry. The command attempts to use a cluster-internal URL determined from managed images and imagestreams. In case it fails (the registry cannot be resolved or reached), an alternative route that works needs to be provided using this flag. The registry host name can be prefixed by https:// or http:// which enforces particular connection protocol.

--prune-registry

In conjunction with the conditions stipulated by the other options, this option controls whether the data in the registry corresponding to the OpenShift Container Platform image API object is pruned. By default, image pruning processes both the image API objects and corresponding data in the registry. This options is useful when you are only concerned with removing etcd content, possibly to reduce the number of image objects (but are not concerned with cleaning up registry storage) or intend to do that separately by hard pruning the registry, possibly during an appropriate maintenance window for the registry.

8.5.1. Image prune conditions

  • Remove any image "managed by OpenShift Container Platform" (images with the annotation openshift.io/image.managed) that was created at least --keep-younger-than minutes ago and is not currently referenced by:

    • any Pod created less than --keep-younger-than minutes ago.
    • any imagestream created less than --keep-younger-than minutes ago.
    • any running Pods.
    • any pending Pods.
    • any ReplicationControllers.
    • any DeploymentConfigs.
    • any Build Configurations.
    • any Builds.
    • the --keep-tag-revisions most recent items in stream.status.tags[].items.
  • Remove any image "managed by OpenShift Container Platform" (images with the annotation openshift.io/image.managed) that is exceeding the smallest limit defined in the same project and is not currently referenced by:

    • any running Pods.
    • any pending Pods.
    • any ReplicationControllers.
    • any DeploymentConfigs.
    • any Build Configurations.
    • any Builds.
  • There is no support for pruning from external registries.
  • When an image is pruned, all references to the image are removed from all imagestreams that have a reference to the image in status.tags.
  • Image layers that are no longer referenced by any images are removed.
Note

The --prune-over-size-limit flag cannot be combined with --keep-tag-revisions nor --keep-younger-than flags. Doing so returns information that this operation is not allowed.

Separating the removal of OpenShift Container Platform image API objects and image data from the Registry by using --prune-registry=false followed by hard pruning the registry narrows some timing windows and is safer when compared to trying to prune both through one command. However, timing windows are not completely removed.

For example, you can still create a Pod referencing an image as pruning identifies that image for pruning. You should still keep track of an API Object created during the pruning operations that might reference images, so you can mitigate any references to deleted content.

Also, keep in mind that re-doing the pruning without the --prune-registry option or with --prune-registry=true does not lead to pruning the associated storage in the image registry for images previously pruned by --prune-registry=false. Any images that were pruned with --prune-registry=false can only be deleted from registry storage by hard pruning the registry.

8.5.2. Running the image prune operation

Procedure

  1. To see what a pruning operation would delete:

    1. Keeping up to three tag revisions, and keeping resources (images, image streams and Pods) younger than sixty minutes:

      $ oc adm prune images --keep-tag-revisions=3 --keep-younger-than=60m
    2. Pruning every image that exceeds defined limits:

      $ oc adm prune images --prune-over-size-limit
  2. To actually perform the prune operation with the options from the previous step:

    $ oc adm prune images --keep-tag-revisions=3 --keep-younger-than=60m --confirm
    $ oc adm prune images --prune-over-size-limit --confirm

8.5.3. Using secure or insecure connections

The secure connection is the preferred and recommended approach. It is done over HTTPS protocol with a mandatory certificate verification. The prune command always attempts to use it if possible. If it is not possible, in some cases it can fall-back to insecure connection, which is dangerous. In this case, either certificate verification is skipped or plain HTTP protocol is used.

The fall-back to insecure connection is allowed in the following cases unless --certificate-authority is specified:

  1. The prune command is run with the --force-insecure option.
  2. The provided registry-url is prefixed with the http:// scheme.
  3. The provided registry-url is a local-link address or localhost.
  4. The configuration of the current user allows for an insecure connection. This can be caused by the user either logging in using --insecure-skip-tls-verify or choosing the insecure connection when prompted.
Important

If the registry is secured by a certificate authority different from the one used by OpenShift Container Platform, it must be specified using the --certificate-authority flag. Otherwise, the prune command fails with an error.

8.5.4. Image pruning problems

Images not being pruned

If your images keep accumulating and the prune command removes just a small portion of what you expect, ensure that you understand the image prune conditions that must apply for an image to be considered a candidate for pruning.

Ensure that images you want removed occur at higher positions in each tag history than your chosen tag revisions threshold. For example, consider an old and obsolete image named sha:abz. By running the following command in namespace N, where the image is tagged, the image is tagged three times in a single imagestream named myapp:

$ image_name="sha:abz"
$ oc get is -n N -o go-template='{{range $isi, $is := .items}}{{range $ti, $tag := $is.status.tags}}'\
  '{{range $ii, $item := $tag.items}}{{if eq $item.image "'"${image_name}"\
  $'"}}{{$is.metadata.name}}:{{$tag.tag}} at position {{$ii}} out of {{len $tag.items}}\n'\
  '{{end}}{{end}}{{end}}{{end}}'
myapp:v2 at position 4 out of 5
myapp:v2.1 at position 2 out of 2
myapp:v2.1-may-2016 at position 0 out of 1

When default options are used, the image is never pruned because it occurs at position 0 in a history of myapp:v2.1-may-2016 tag. For an image to be considered for pruning, the administrator must either:

  • Specify --keep-tag-revisions=0 with the oc adm prune images command.

    Caution

    This action effectively removes all the tags from all the namespaces with underlying images, unless they are younger or they are referenced by objects younger than the specified threshold.

  • Delete all the istags where the position is below the revision threshold, which means myapp:v2.1 and myapp:v2.1-may-2016.
  • Move the image further in the history, either by running new Builds pushing to the same istag, or by tagging other image. Unfortunately, this is not always desirable for old release tags.

Tags having a date or time of a particular image’s Build in their names should be avoided, unless the image must be preserved for an undefined amount of time. Such tags tend to have just one image in its history, which effectively prevents them from ever being pruned.

Using a secure connection against insecure registry

If you see a message similar to the following in the output of the oadm prune images command, then your registry is not secured and the oadm prune images client attempts to use a secure connection:

error: error communicating with registry: Get https://172.30.30.30:5000/healthz: http: server gave HTTP response to HTTPS client
  1. The recommend solution is to secure the registry. Otherwise, you can force the client to use an insecure connection by appending --force-insecure to the command, however this is not recommended.
Using an insecure connection against a secured registry

If you see one of the following errors in the output of the oadm prune images command, it means that your registry is secured using a certificate signed by a certificate authority other than the one used by oadm prune images client for connection verification:

error: error communicating with registry: Get http://172.30.30.30:5000/healthz: malformed HTTP response "\x15\x03\x01\x00\x02\x02"
error: error communicating with registry: [Get https://172.30.30.30:5000/healthz: x509: certificate signed by unknown authority, Get http://172.30.30.30:5000/healthz: malformed HTTP response "\x15\x03\x01\x00\x02\x02"]

By default, the certificate authority data stored in the user’s configuration file are used; the same is true for communication with the master API.

Use the --certificate-authority option to provide the right certificate authority for the container image registry server.

Using the wrong certificate authority

The following error means that the certificate authority used to sign the certificate of the secured container image registry is different than the authority used by the client:

error: error communicating with registry: Get https://172.30.30.30:5000/: x509: certificate signed by unknown authority

Make sure to provide the right one with the flag --certificate-authority.

As a workaround, the --force-insecure flag can be added instead. However, this is not recommended.

8.6. Hard pruning the registry

The OpenShift Container Registry can accumulate blobs that are not referenced by the OpenShift Container Platform cluster’s etcd. The basic pruning images procedure, therefore, is unable to operate on them. These are called orphaned blobs.

Orphaned blobs can occur from the following scenarios:

  • Manually deleting an image with oc delete image <sha256:image-id> command, which only removes the image from etcd, but not from the registry’s storage.
  • Pushing to the registry initiated by docker daemon failures, which causes some blobs to get uploaded, but the image manifest (which is uploaded as the very last component) does not. All unique image blobs become orphans.
  • OpenShift Container Platform refusing an image because of quota restrictions.
  • The standard image pruner deleting an image manifest, but is interrupted before it deletes the related blobs.
  • A bug in the registry pruner, which fails to remove the intended blobs, causing the image objects referencing them to be removed and the blobs becoming orphans.

Hard pruning the registry, a separate procedure from basic image pruning, allows cluster administrators to remove orphaned blobs. You should hard prune if you are running out of storage space in your OpenShift Container Registry and believe you have orphaned blobs.

This should be an infrequent operation and is necessary only when you have evidence that significant numbers of new orphans have been created. Otherwise, you can perform standard image pruning at regular intervals, for example, once a day (depending on the number of images being created).

Procedure

To hard prune orphaned blobs from the registry:

  1. Log in.

    Log in to the cluster with the CLI as a user with an access token.

  2. Run a basic image prune.

    Basic image pruning removes additional images that are no longer needed. The hard prune does not remove images on its own. It only removes blobs stored in the registry storage. Therefore, you should run this just before the hard prune.

  3. Switch the registry to read-only mode.

    If the registry is not running in read-only mode, any pushes happening at the same time as the prune will either:

    • fail and cause new orphans, or
    • succeed although the images cannot be pulled (because some of the referenced blobs were deleted).

    Pushes will not succeed until the registry is switched back to read-write mode. Therefore, the hard prune must be carefully scheduled.

    To switch the registry to read-only mode:

    1. Set the following environment variable:

      $ oc set env -n default \
          dc/docker-registry \
          'REGISTRY_STORAGE_MAINTENANCE_READONLY={"enabled":true}'
    2. By default, the registry automatically redeploys when the previous step completes; wait for the redeployment to complete before continuing. However, if you have disabled these triggers, you must manually redeploy the registry so that the new environment variables are picked up:

      $ oc rollout -n default \
          latest dc/docker-registry
  4. Add the system:image-pruner role.

    The service account used to run the registry instances requires additional permissions in order to list some resources.

    1. Get the service account name:

      $ service_account=$(oc get -n default \
          -o jsonpath=$'system:serviceaccount:{.metadata.namespace}:{.spec.template.spec.serviceAccountName}\n' \
          dc/docker-registry)
    2. Add the system:image-pruner cluster role to the service account:

      $ oc adm policy add-cluster-role-to-user \
          system:image-pruner \
          ${service_account}
  5. (Optional) Run the pruner in dry-run mode.

    To see how many blobs would be removed, run the hard pruner in dry-run mode. No changes are actually made:

    $ oc -n default \
        exec -i -t "$(oc -n default get pods -l deploymentconfig=docker-registry \
        -o jsonpath=$'{.items[0].metadata.name}\n')" \
        -- /usr/bin/dockerregistry -prune=check

    Alternatively, to get the exact paths for the prune candidates, increase the logging level:

    $ oc -n default \
        exec "$(oc -n default get pods -l deploymentconfig=docker-registry \
          -o jsonpath=$'{.items[0].metadata.name}\n')" \
        -- /bin/sh \
        -c 'REGISTRY_LOG_LEVEL=info /usr/bin/dockerregistry -prune=check'

    Truncated sample output

    $ oc exec docker-registry-3-vhndw \
        -- /bin/sh -c 'REGISTRY_LOG_LEVEL=info /usr/bin/dockerregistry -prune=check'
    
    time="2017-06-22T11:50:25.066156047Z" level=info msg="start prune (dry-run mode)" distribution_version="v2.4.1+unknown" kubernetes_version=v1.6.1+$Format:%h$ openshift_version=unknown
    time="2017-06-22T11:50:25.092257421Z" level=info msg="Would delete blob: sha256:00043a2a5e384f6b59ab17e2c3d3a3d0a7de01b2cabeb606243e468acc663fa5" go.version=go1.7.5 instance.id=b097121c-a864-4e0c-ad6c-cc25f8fdf5a6
    time="2017-06-22T11:50:25.092395621Z" level=info msg="Would delete blob: sha256:0022d49612807cb348cabc562c072ef34d756adfe0100a61952cbcb87ee6578a" go.version=go1.7.5 instance.id=b097121c-a864-4e0c-ad6c-cc25f8fdf5a6
    time="2017-06-22T11:50:25.092492183Z" level=info msg="Would delete blob: sha256:0029dd4228961086707e53b881e25eba0564fa80033fbbb2e27847a28d16a37c" go.version=go1.7.5 instance.id=b097121c-a864-4e0c-ad6c-cc25f8fdf5a6
    time="2017-06-22T11:50:26.673946639Z" level=info msg="Would delete blob: sha256:ff7664dfc213d6cc60fd5c5f5bb00a7bf4a687e18e1df12d349a1d07b2cf7663" go.version=go1.7.5 instance.id=b097121c-a864-4e0c-ad6c-cc25f8fdf5a6
    time="2017-06-22T11:50:26.674024531Z" level=info msg="Would delete blob: sha256:ff7a933178ccd931f4b5f40f9f19a65be5eeeec207e4fad2a5bafd28afbef57e" go.version=go1.7.5 instance.id=b097121c-a864-4e0c-ad6c-cc25f8fdf5a6
    time="2017-06-22T11:50:26.674675469Z" level=info msg="Would delete blob: sha256:ff9b8956794b426cc80bb49a604a0b24a1553aae96b930c6919a6675db3d5e06" go.version=go1.7.5 instance.id=b097121c-a864-4e0c-ad6c-cc25f8fdf5a6
    ...
    Would delete 13374 blobs
    Would free up 2.835 GiB of disk space
    Use -prune=delete to actually delete the data

  6. Run the hard prune.

    Execute the following command inside one running instance of a docker-registry pod to run the hard prune:

    $ oc -n default \
        exec -i -t "$(oc -n default get pods -l deploymentconfig=docker-registry -o jsonpath=$'{.items[0].metadata.name}\n')" \
        -- /usr/bin/dockerregistry -prune=delete

    Sample output

    $ oc exec docker-registry-3-vhndw \
        -- /usr/bin/dockerregistry -prune=delete
    
    Deleted 13374 blobs
    Freed up 2.835 GiB of disk space

  7. Switch the registry back to read-write mode.

    After the prune is finished, the registry can be switched back to read-write mode by executing:

    $ oc set env -n default dc/docker-registry REGISTRY_STORAGE_MAINTENANCE_READONLY-

8.7. Pruning cron jobs

Cron jobs can perform pruning of successful jobs, but might not properly handle failed jobs. Therefore, the cluster administrator should perform regular cleanup of jobs manually. They should also restrict the access to cron jobs to a small group of trusted users and set appropriate quota to prevent the cron job from creating too many jobs and pods.

Chapter 9. Operator SDK

9.1. Getting started with the Operator SDK

This guide outlines the basics of the Operator SDK and walks Operator authors with cluster administrator access to a Kubernetes-based cluster (such as OpenShift Container Platform) through an example of building a simple Go-based Memcached Operator and managing its lifecycle from installation to upgrade.

This is accomplished using two centerpieces of the Operator Framework: the Operator SDK (the operator-sdk CLI tool and controller-runtime library API) and the Operator Lifecycle Manager (OLM).

Note

OpenShift Container Platform 4 supports Operator SDK v0.7.0 or later.

9.1.1. Architecture of the Operator SDK

The Operator Framework is an open source toolkit to manage Kubernetes native applications, called Operators, in an effective, automated, and scalable way. Operators take advantage of Kubernetes' extensibility to deliver the automation advantages of cloud services like provisioning, scaling, and backup and restore, while being able to run anywhere that Kubernetes can run.

Operators make it easy to manage complex, stateful applications on top of Kubernetes. However, writing an Operator today can be difficult because of challenges such as using low-level APIs, writing boilerplate, and a lack of modularity, which leads to duplication.

The Operator SDK is a framework designed to make writing Operators easier by providing:

  • High-level APIs and abstractions to write the operational logic more intuitively
  • Tools for scaffolding and code generation to quickly bootstrap a new project
  • Extensions to cover common Operator use cases

9.1.1.1. Workflow

The Operator SDK provides the following workflow to develop a new Operator:

  1. Create a new Operator project using the Operator SDK command line interface (CLI).
  2. Define new resource APIs by adding Custom Resource Definitions (CRDs).
  3. Specify resources to watch using the Operator SDK API.
  4. Define the Operator reconciling logic in a designated handler and use the Operator SDK API to interact with resources.
  5. Use the Operator SDK CLI to build and generate the Operator deployment manifests.

Figure 9.1. Operator SDK workflow

osdk workflow

At a high level, an Operator using the Operator SDK processes events for watched resources in an Operator author-defined handler and takes actions to reconcile the state of the application.

9.1.1.2. Manager file

The main program for the Operator is the manager file at cmd/manager/main.go. The manager automatically registers the scheme for all Custom Resources (CRs) defined under pkg/apis/ and runs all controllers under pkg/controller/.

The manager can restrict the namespace that all controllers watch for resources:

mgr, err := manager.New(cfg, manager.Options{Namespace: namespace})

By default, this is the namespace that the Operator is running in. To watch all namespaces, you can leave the namespace option empty:

mgr, err := manager.New(cfg, manager.Options{Namespace: ""})

9.1.1.3. Prometheus Operator support

Prometheus is an open-source systems monitoring and alerting toolkit. The Prometheus Operator creates, configures, and manages Prometheus clusters running on Kubernetes-based clusters, such as OpenShift Container Platform.

Helper functions exist in the Operator SDK by default to automatically set up metrics in any generated Go-based Operator for use on clusters where the Prometheus Operator is deployed.

9.1.2. Installing the Operator SDK CLI

The Operator SDK has a CLI tool that assists developers in creating, building, and deploying a new Operator project. You can install the SDK CLI on your workstation so you are prepared to start authoring your own Operators.

Note

This guide uses minikube v0.25.0+ as the local Kubernetes cluster and quay.io for the public registry.

9.1.2.1. Installing from GitHub release

You can download and install a pre-built release binary of the SDK CLI from the project on GitHub.

Prerequisites

  • docker v17.03+
  • OpenShift CLI (oc) v4.1+ installed
  • Access to a cluster based on Kubernetes v1.11.3+
  • Access to a container registry

Procedure

  1. Set the release version variable:

    RELEASE_VERSION=v0.8.0
  2. Download the release binary.

    • For Linux:

      $ curl -OJL https://github.com/operator-framework/operator-sdk/releases/download/${RELEASE_VERSION}/operator-sdk-${RELEASE_VERSION}-x86_64-linux-gnu
    • For macOS:

      $ curl -OJL https://github.com/operator-framework/operator-sdk/releases/download/${RELEASE_VERSION}/operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin
  3. Verify the downloaded release binary.

    1. Download the provided ASC file.

      • For Linux:

        $ curl -OJL https://github.com/operator-framework/operator-sdk/releases/download/${RELEASE_VERSION}/operator-sdk-${RELEASE_VERSION}-x86_64-linux-gnu.asc
      • For macOS:

        $ curl -OJL https://github.com/operator-framework/operator-sdk/releases/download/${RELEASE_VERSION}/operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin.asc
    2. Place the binary and corresponding ASC file into the same directory and run the following command to verify the binary:

      • For Linux:

        $ gpg --verify operator-sdk-${RELEASE_VERSION}-x86_64-linux-gnu.asc
      • For macOS:

        $ gpg --verify operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin.asc

      If you do not have the maintainer’s public key on your workstation, you will get the following error:

      $ gpg --verify operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin.asc
      $ gpg: assuming signed data in 'operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin'
      $ gpg: Signature made Fri Apr  5 20:03:22 2019 CEST
      $ gpg:                using RSA key <key_id> 1
      $ gpg: Can't check signature: No public key
      1
      RSA key string.

      To download the key, run the following command, replacing <key_id> with the RSA key string provided in the output of the previous command:

      $ gpg [--keyserver keys.gnupg.net] --recv-key "<key_id>" 1
      1
      If you do not have a key server configured, specify one with the --keyserver option.
  4. Install the release binary in your PATH:

    • For Linux:

      $ chmod +x operator-sdk-${RELEASE_VERSION}-x86_64-linux-gnu
      $ sudo cp operator-sdk-${RELEASE_VERSION}-x86_64-linux-gnu /usr/local/bin/operator-sdk
      $ rm operator-sdk-${RELEASE_VERSION}-x86_64-linux-gnu
    • For macOS:

      $ chmod +x operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin
      $ sudo cp operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin /usr/local/bin/operator-sdk
      $ rm operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin
  5. Verify that the CLI tool was installed correctly:

    $ operator-sdk version

9.1.2.2. Installing from Homebrew

You can install the SDK CLI using Homebrew.

Prerequisites

  • Homebrew
  • docker v17.03+
  • OpenShift CLI (oc) v4.1+ installed
  • Access to a cluster based on Kubernetes v1.11.3+
  • Access to a container registry

Procedure

  1. Install the SDK CLI using the brew command:

    $ brew install operator-sdk
  2. Verify that the CLI tool was installed correctly:

    $ operator-sdk version

9.1.2.3. Compiling and installing from source

You can obtain the Operator SDK source code to compile and install the SDK CLI.

Prerequisites

  • dep v0.5.0+
  • Git
  • Go v1.10+
  • docker v17.03+
  • OpenShift CLI (oc) v4.1+ installed
  • Access to a cluster based on Kubernetes v1.11.3+
  • Access to a container registry

Procedure

  1. Clone the operator-sdk repository:

    $ mkdir -p $GOPATH/src/github.com/operator-framework
    $ cd $GOPATH/src/github.com/operator-framework
    $ git clone https://github.com/operator-framework/operator-sdk
    $ cd operator-sdk
  2. Check out the desired release branch:

    $ git checkout master
  3. Compile and install the SDK CLI:

    $ make dep
    $ make install

    This installs the CLI binary operator-sdk at $GOPATH/bin.

  4. Verify that the CLI tool was installed correctly:

    $ operator-sdk version

9.1.3. Building a Go-based Memcached Operator using the Operator SDK

The Operator SDK makes it easier to build Kubernetes native applications, a process that can require deep, application-specific operational knowledge. The SDK not only lowers that barrier, but it also helps reduce the amount of boilerplate code needed for many common management capabilities, such as metering or monitoring.

This procedure walks through an example of building a simple Memcached Operator using tools and libraries provided by the SDK.

Prerequisites

  • Operator SDK CLI installed on the development workstation
  • Operator Lifecycle Manager (OLM) installed on a Kubernetes-based cluster (v1.8 or above to support the apps/v1beta2 API group), for example OpenShift Container Platform 4.1
  • Access to the cluster using an account with cluster-admin permissions
  • OpenShift CLI (oc) v4.1+ installed

Procedure

  1. Create a new project.

    Use the CLI to create a new memcached-operator project:

    $ mkdir -p $GOPATH/src/github.com/example-inc/
    $ cd $GOPATH/src/github.com/example-inc/
    $ operator-sdk new memcached-operator --dep-manager dep
    $ cd memcached-operator
  2. Add a new Custom Resource Definition (CRD).

    1. Use the CLI to add a new CRD API called Memcached, with APIVersion set to cache.example.com/v1apha1 and Kind set to Memcached:

      $ operator-sdk add api \
          --api-version=cache.example.com/v1alpha1 \
          --kind=Memcached

      This scaffolds the Memcached resource API under pkg/apis/cache/v1alpha1/.

    2. Modify the spec and status of the Memcached Custom Resource (CR) at the pkg/apis/cache/v1alpha1/memcached_types.go file:

      type MemcachedSpec struct {
      	// Size is the size of the memcached deployment
      	Size int32 `json:"size"`
      }
      type MemcachedStatus struct {
      	// Nodes are the names of the memcached pods
      	Nodes []string `json:"nodes"`
      }
    3. After modifying the *_types.go file, always run the following command to update the generated code for that resource type:

      $ operator-sdk generate k8s
  3. Add a new Controller.

    1. Add a new Controller to the project to watch and reconcile the Memcached resource:

      $ operator-sdk add controller \
          --api-version=cache.example.com/v1alpha1 \
          --kind=Memcached

      This scaffolds a new Controller implementation under pkg/controller/memcached/.

    2. For this example, replace the generated controller file pkg/controller/memcached/memcached_controller.go with the example implementation.

      The example controller executes the following reconciliation logic for each Memcached CR:

      • Create a Memcached Deployment if it does not exist.
      • Ensure that the Deployment size is the same as specified by the Memcached CR spec.
      • Update the Memcached CR status with the names of the Memcached Pods.

      The next two sub-steps inspect how the Controller watches resources and how the reconcile loop is triggered. You can skip these steps to go directly to building and running the Operator.

    3. Inspect the Controller implementation at the pkg/controller/memcached/memcached_controller.go file to see how the Controller watches resources.

      The first watch is for the Memcached type as the primary resource. For each Add, Update, or Delete event, the reconcile loop is sent a reconcile Request (a <namespace>:<name> key) for that Memcached object:

      err := c.Watch(
        &source.Kind{Type: &cachev1alpha1.Memcached{}}, &handler.EnqueueRequestForObject{})

      The next watch is for Deployments, but the event handler maps each event to a reconcile Request for the owner of the Deployment. In this case, this is the Memcached object for which the Deployment was created. This allows the controller to watch Deployments as a secondary resource:

      err := c.Watch(&source.Kind{Type: &appsv1.Deployment{}}, &handler.EnqueueRequestForOwner{
      		IsController: true,
      		OwnerType:    &cachev1alpha1.Memcached{},
      	})
    4. Every Controller has a Reconciler object with a Reconcile() method that implements the reconcile loop. The reconcile loop is passed the Request argument which is a <namespace>:<name> key used to lookup the primary resource object, Memcached, from the cache:

      func (r *ReconcileMemcached) Reconcile(request reconcile.Request) (reconcile.Result, error) {
        // Lookup the Memcached instance for this reconcile request
        memcached := &cachev1alpha1.Memcached{}
        err := r.client.Get(context.TODO(), request.NamespacedName, memcached)
        ...
      }

      Based on the return value of Reconcile() the reconcile Request may be requeued and the loop may be triggered again:

      // Reconcile successful - don't requeue
      return reconcile.Result{}, nil
      // Reconcile failed due to error - requeue
      return reconcile.Result{}, err
      // Requeue for any reason other than error
      return reconcile.Result{Requeue: true}, nil
  4. Build and run the Operator.

    1. Before running the Operator, the CRD must be registered with the Kubernetes API server:

      $ oc create \
          -f deploy/crds/cache_v1alpha1_memcached_crd.yaml
    2. After registering the CRD, there are two options for running the Operator:

      • As a Deployment inside a Kubernetes cluster
      • As Go program outside a cluster

      Choose one of the following methods.

      1. Option A: Running as a Deployment inside the cluster.

        1. Build the memcached-operator image and push it to a registry:

          $ operator-sdk build quay.io/example/memcached-operator:v0.0.1
        2. The Deployment manifest is generated at deploy/operator.yaml. Update the Deployment image as follows since the default is just a placeholder:

          $ sed -i 's|REPLACE_IMAGE|quay.io/example/memcached-operator:v0.0.1|g' deploy/operator.yaml
        3. Ensure you have an account on quay.io for the next step, or substitute your preferred container registry. On the registry, create a new public image repository named memcached-operator.
        4. Push the image to the registry:

          $ docker push quay.io/example/memcached-operator:v0.0.1
        5. Setup RBAC and deploy memcached-operator:

          $ oc create -f deploy/role.yaml
          $ oc create -f deploy/role_binding.yaml
          $ oc create -f deploy/service_account.yaml
          $ oc create -f deploy/operator.yaml
        6. Verify that memcached-operator is up and running:

          $ oc get deployment
          NAME                     DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
          memcached-operator       1         1         1            1           1m
      2. Option B: Running locally outside the cluster.

        This method is preferred during development cycle to deploy and test faster.

        Run the Operator locally with the default Kubernetes configuration file present at $HOME/.kube/config:

        $ operator-sdk up local --namespace=default

        You can use a specific kubeconfig using the flag --kubeconfig=<path/to/kubeconfig>.

  5. Verify that the Operator can deploy a Memcached application by creating a Memcached CR.

    1. Create the example Memcached CR that was generated at deploy/crds/cache_v1alpha1_memcached_cr.yaml:

      $ cat deploy/crds/cache_v1alpha1_memcached_cr.yaml
      apiVersion: "cache.example.com/v1alpha1"
      kind: "Memcached"
      metadata:
        name: "example-memcached"
      spec:
        size: 3
      
      $ oc apply -f deploy/crds/cache_v1alpha1_memcached_cr.yaml
    2. Ensure that memcached-operator creates the Deployment for the CR:

      $ oc get deployment
      NAME                     DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
      memcached-operator       1         1         1            1           2m
      example-memcached        3         3         3            3           1m
    3. Check the Pods and CR status to confirm the status is updated with the memcached Pod names:

      $ oc get pods
      NAME                                  READY     STATUS    RESTARTS   AGE
      example-memcached-6fd7c98d8-7dqdr     1/1       Running   0          1m
      example-memcached-6fd7c98d8-g5k7v     1/1       Running   0          1m
      example-memcached-6fd7c98d8-m7vn7     1/1       Running   0          1m
      memcached-operator-7cc7cfdf86-vvjqk   1/1       Running   0          2m
      
      $ oc get memcached/example-memcached -o yaml
      apiVersion: cache.example.com/v1alpha1
      kind: Memcached
      metadata:
        clusterName: ""
        creationTimestamp: 2018-03-31T22:51:08Z
        generation: 0
        name: example-memcached
        namespace: default
        resourceVersion: "245453"
        selfLink: /apis/cache.example.com/v1alpha1/namespaces/default/memcacheds/example-memcached
        uid: 0026cc97-3536-11e8-bd83-0800274106a1
      spec:
        size: 3
      status:
        nodes:
        - example-memcached-6fd7c98d8-7dqdr
        - example-memcached-6fd7c98d8-g5k7v
        - example-memcached-6fd7c98d8-m7vn7
  6. Verify that the Operator can manage a deployed Memcached application by updating the size of the deployment.

    1. Change the spec.size field in the memcached CR from 3 to 4:

      $ cat deploy/crds/cache_v1alpha1_memcached_cr.yaml
      apiVersion: "cache.example.com/v1alpha1"
      kind: "Memcached"
      metadata:
        name: "example-memcached"
      spec:
        size: 4
    2. Apply the change:

      $ oc apply -f deploy/crds/cache_v1alpha1_memcached_cr.yaml
    3. Confirm that the Operator changes the Deployment size:

      $ oc get deployment
      NAME                 DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
      example-memcached    4         4         4            4           5m
  7. Clean up the resources:

    $ oc delete -f deploy/crds/cache_v1alpha1_memcached_cr.yaml
    $ oc delete -f deploy/crds/cache_v1alpha1_memcached_crd.yaml
    $ oc delete -f deploy/operator.yaml
    $ oc delete -f deploy/role.yaml
    $ oc delete -f deploy/role_binding.yaml
    $ oc delete -f deploy/service_account.yaml

9.1.4. Managing a Memcached Operator using the Operator Lifecycle Manager

The previous section has covered manually running an Operator. In the next sections, we will explore using the Operator Lifecycle Manager (OLM), which is what enables a more robust deployment model for Operators being run in production environments.

The OLM helps you to install, update, and generally manage the lifecycle of all of the Operators (and their associated services) on a Kubernetes cluster. It runs as an Kubernetes extension and lets you use oc for all the lifecycle management functions without any additional tools.

Prerequisites

  • OLM installed on a Kubernetes-based cluster (v1.8 or above to support the apps/v1beta2 API group), for example OpenShift Container Platform 4.1 Preview OLM enabled
  • Memcached Operator built

Procedure

  1. Generate an Operator manifest.

    An Operator manifest describes how to display, create, and manage the application, in this case Memcached, as a whole. It is defined by a ClusterServiceVersion (CSV) object and is required for the OLM to function.

    You can use the following command to generate CSV manifests:

    $ operator-sdk olm-catalog gen-csv --csv-version 0.0.1
    Note

    This command is run from the memcached-operator/ directory that was created when you built the Memcached Operator.

    For the purpose of this guide, we will continue with this predefined manifest file for the next steps. You can alter the image field within this manifest to reflect the image you built in previous steps, but it is unnecessary.

    Note

    See Building a CSV for the Operator Framework for more information on manually defining a manifest file.

  2. Deploy the Operator.

    1. Create an OperatorGroup that specifies the namespaces that the Operator will target. Create the following OperatorGroup in the namespace where you will create the CSV. In this example, the default namespace is used:

      apiVersion: operators.coreos.com/v1
      kind: OperatorGroup
      metadata:
        name: memcached-operator-group
        namespace: default
      spec:
        targetNamespaces:
        - default
    2. Apply the Operator’s CSV manifest to the specified namespace in the cluster:

      $ curl -Lo memcachedoperator.0.0.1.csv.yaml https://raw.githubusercontent.com/operator-framework/getting-started/master/memcachedoperator.0.0.1.csv.yaml
      $ oc apply -f memcachedoperator.0.0.1.csv.yaml
      $ oc get csv memcachedoperator.v0.0.1 -n default -o json | jq '.status'

      When you apply this manifest, the cluster does not immediately update because it does not yet meet the requirements specified in the manifest.

    3. Create the role, role binding, and service account to grant resource permissions to the Operator, and the Custom Resource Definition (CRD) to create the Memcached type that the Operator manages:

      $ oc create -f deploy/crds/cache_v1alpha1_memcached_crd.yaml
      $ oc create -f deploy/service_account.yaml
      $ oc create -f deploy/role.yaml
      $ oc create -f deploy/role_binding.yaml
      Note

      These files were generated into the deploy/ directory by the Operator SDK when you built the Memcached Operator.

      Because the OLM creates Operators in a particular namespace when a manifest is applied, administrators can leverage the native Kubernetes RBAC permission model to restrict which users are allowed to install Operators.

  3. Create an application instance.

    The Memcached Operator is now running in the default namespace. Users interact with Operators via instances of CustomResources; in this case, the resource has the kind Memcached. Native Kubernetes RBAC also applies to CustomResources, providing administrators control over who can interact with each Operator.

    Creating instances of Memcached in this namespace will now trigger the Memcached Operator to instantiate pods running the memcached server that are managed by the Operator. The more CustomResources you create, the more unique instances of Memcached are managed by the Memcached Operator running in this namespace.

    $ cat <<EOF | oc apply -f -
    apiVersion: "cache.example.com/v1alpha1"
    kind: "Memcached"
    metadata:
      name: "memcached-for-wordpress"
    spec:
      size: 1
    EOF
    
    $ cat <<EOF | oc apply -f -
    apiVersion: "cache.example.com/v1alpha1"
    kind: "Memcached"
    metadata:
      name: "memcached-for-drupal"
    spec:
      size: 1
    EOF
    
    $ oc get Memcached
    NAME                      AGE
    memcached-for-drupal      22s
    memcached-for-wordpress   27s
    
    $ oc get pods
    NAME                                       READY     STATUS    RESTARTS   AGE
    memcached-app-operator-66b5777b79-pnsfj    1/1       Running   0          14m
    memcached-for-drupal-5476487c46-qbd66      1/1       Running   0          3s
    memcached-for-wordpress-65b75fd8c9-7b9x7   1/1       Running   0          8s
  4. Update an application.

    Manually apply an update to the Operator by creating a new Operator manifest with a replaces field that references the old Operator manifest. The OLM ensures that all resources being managed by the old Operator have their ownership moved to the new Operator without fear of any programs stopping execution. It is up to the Operators themselves to execute any data migrations required to upgrade resources to run under a new version of the Operator.

    The following command demonstrates applying a new Operator manifest file using a new version of the Operator and shows that the pods remain executing:

    $ curl -Lo memcachedoperator.0.0.2.csv.yaml https://raw.githubusercontent.com/operator-framework/getting-started/master/memcachedoperator.0.0.2.csv.yaml
    $ oc apply -f memcachedoperator.0.0.2.csv.yaml
    $ oc get pods
    NAME                                       READY     STATUS    RESTARTS   AGE
    memcached-app-operator-66b5777b79-pnsfj    1/1       Running   0          3s
    memcached-for-drupal-5476487c46-qbd66      1/1       Running   0          14m
    memcached-for-wordpress-65b75fd8c9-7b9x7   1/1       Running   0          14m

9.1.5. Additional resources

9.2. Creating Ansible-based Operators

This guide outlines Ansible support in the Operator SDK and walks Operator authors through examples building and running Ansible-based Operators with the operator-sdk CLI tool that use Ansible playbooks and modules.

9.2.1. Ansible support in the Operator SDK

The Operator Framework is an open source toolkit to manage Kubernetes native applications, called Operators, in an effective, automated, and scalable way. This framework includes the Operator SDK, which assists developers in bootstrapping and building an Operator based on their expertise without requiring knowledge of Kubernetes API complexities.

One of the Operator SDK’s options for generating an Operator project includes leveraging existing Ansible playbooks and modules to deploy Kubernetes resources as a unified application, without having to write any Go code.

9.2.1.1. Custom Resource files

Operators use the Kubernetes' extension mechanism, Custom Resource Definitions (CRDs), so your Custom Resource (CR) looks and acts just like the built-in, native Kubernetes objects.

The CR file format is a Kubernetes resource file. The object has mandatory and optional fields:

Table 9.1. Custom Resource fields

FieldDescription

apiVersion

Version of the CR to be created.

kind

Kind of the CR to be created.

metadata

Kubernetes-specific metadata to be created.

spec (optional)

Key-value list of variables which are passed to Ansible. This field is empty by default.

status

Summarizes the current state of the object. For Ansible-based Operators, the status subresource is enabled for CRDs and managed by the k8s_status Ansible module by default, which includes condition information to the CR’s status.

annotations

Kubernetes-specific annotations to be appended to the CR.

The following list of CR annotations modify the behavior of the Operator:

Table 9.2. Ansible-based Operator annotations

AnnotationDescription

ansible.operator-sdk/reconcile-period

Specifies the reconciliation interval for the CR. This value is parsed using the standard Golang package time. Specifically, ParseDuration is used which applies the default suffix of s, giving the value in seconds.

Example Ansible-based Operator annotation

apiVersion: "foo.example.com/v1alpha1"
kind: "Foo"
metadata:
  name: "example"
annotations:
  ansible.operator-sdk/reconcile-period: "30s"

9.2.1.2. Watches file

The Watches file contains a list of mappings from Custom Resources (CRs), identified by its Group, Version, and Kind, to an Ansible role or playbook. The Operator expects this mapping file in a predefined location, /opt/ansible/watches.yaml.

Table 9.3. Watches file mappings

FieldDescription

group

Group of CR to watch.

version

Version of CR to watch.

kind

Kind of CR to watch

role (default)

Path to the Ansible role added to the container. For example, if your roles directory is at /opt/ansible/roles/ and your role is named busybox, this value would be /opt/ansible/roles/busybox. This field is mutually exclusive with the playbook field.

playbook

Path to the Ansible playbook added to the container. This playbook is expected to be simply a way to call roles. This field is mutually exclusive with the role field.

reconcilePeriod (optional)

The reconciliation interval, how often the role or playbook is run, for a given CR.

manageStatus (optional)

When set to true (default), the Operator manages the status of the CR generically. When set to false, the status of the CR is managed elsewhere, by the specified role or playbook or in a separate controller.

Example Watches file

- version: v1alpha1 1
  group: foo.example.com
  kind: Foo
  role: /opt/ansible/roles/Foo

- version: v1alpha1 2
  group: bar.example.com
  kind: Bar
  playbook: /opt/ansible/playbook.yml

- version: v1alpha1 3
  group: baz.example.com
  kind: Baz
  playbook: /opt/ansible/baz.yml
  reconcilePeriod: 0
  manageStatus: false

1
Simple example mapping Foo to the Foo role.
2
Simple example mapping Bar to a playbook.
3
More complex example for the Baz kind. Disables re-queuing and managing the CR status in the playbook.
9.2.1.2.1. Advanced options

Advanced features can be enabled by adding them to your Watches file per GVK (group, version, and kind). They can go below the group, version, kind and playbook or role fields.

Some features can be overridden per resource using an annotation on that Custom Resource (CR). The options that can be overridden have the annotation specified below.

Table 9.4. Advanced Watches file options

FeatureYAML keyDescriptionAnnotation for overrideDefault value

Reconcile period

reconcilePeriod

Time between reconcile runs for a particular CR.

ansbile.operator-sdk/reconcile-period

1m

Manage status

manageStatus

Allows the Operator to manage the conditions section of each CR’s status section.

 

true

Watch dependent resources

watchDependentResources

Allows the Operator to dynamically watch resources that are created by Ansible.

 

true

Watch cluster-scoped resources

watchClusterScopedResources

Allows the Operator to watch cluster-scoped resources that are created by Ansible.

 

false

Max runner artifacts

maxRunnerArtifacts

Manages the number of artifact directories that Ansible Runner keeps in the Operator container for each individual resource.

ansible.operator-sdk/max-runner-artifacts

20

Example Watches file with advanced options

- version: v1alpha1
  group: app.example.com
  kind: AppService
  playbook: /opt/ansible/playbook.yml
  maxRunnerArtifacts: 30
  reconcilePeriod: 5s
  manageStatus: False
  watchDependentResources: False

9.2.1.3. Extra variables sent to Ansible

Extra variables can be sent to Ansible, which are then managed by the Operator. The spec section of the Custom Resource (CR) passes along the key-value pairs as extra variables. This is equivalent to extra variables passed in to the ansible-playbook command.

The Operator also passes along additional variables under the meta field for the name of the CR and the namespace of the CR.

For the following CR example:

apiVersion: "app.example.com/v1alpha1"
kind: "Database"
metadata:
  name: "example"
spec:
  message:"Hello world 2"
  newParameter: "newParam"

The structure passed to Ansible as extra variables is:

{ "meta": {
        "name": "<cr_name>",
        "namespace": "<cr_namespace>",
  },
  "message": "Hello world 2",
  "new_parameter": "newParam",
  "_app_example_com_database": {
     <full_crd>
   },
}

The message and newParameter fields are set in the top level as extra variables, and meta provides the relevant metadata for the CR as defined in the Operator. The meta fields can be accessed using dot notation in Ansible, for example:

- debug:
    msg: "name: {{ meta.name }}, {{ meta.namespace }}"

9.2.1.4. Ansible Runner directory

Ansible Runner keeps information about Ansible runs in the container. This is located at /tmp/ansible-operator/runner/<group>/<version>/<kind>/<namespace>/<name>.

Additional resources

9.2.2. Installing the Operator SDK CLI

The Operator SDK has a CLI tool that assists developers in creating, building, and deploying a new Operator project. You can install the SDK CLI on your workstation so you are prepared to start authoring your own Operators.

Note

This guide uses minikube v0.25.0+ as the local Kubernetes cluster and quay.io for the public registry.

9.2.2.1. Installing from GitHub release

You can download and install a pre-built release binary of the SDK CLI from the project on GitHub.

Prerequisites

  • docker v17.03+
  • OpenShift CLI (oc) v4.1+ installed
  • Access to a cluster based on Kubernetes v1.11.3+
  • Access to a container registry

Procedure

  1. Set the release version variable:

    RELEASE_VERSION=v0.8.0
  2. Download the release binary.

    • For Linux:

      $ curl -OJL https://github.com/operator-framework/operator-sdk/releases/download/${RELEASE_VERSION}/operator-sdk-${RELEASE_VERSION}-x86_64-linux-gnu
    • For macOS:

      $ curl -OJL https://github.com/operator-framework/operator-sdk/releases/download/${RELEASE_VERSION}/operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin
  3. Verify the downloaded release binary.

    1. Download the provided ASC file.

      • For Linux:

        $ curl -OJL https://github.com/operator-framework/operator-sdk/releases/download/${RELEASE_VERSION}/operator-sdk-${RELEASE_VERSION}-x86_64-linux-gnu.asc
      • For macOS:

        $ curl -OJL https://github.com/operator-framework/operator-sdk/releases/download/${RELEASE_VERSION}/operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin.asc
    2. Place the binary and corresponding ASC file into the same directory and run the following command to verify the binary:

      • For Linux:

        $ gpg --verify operator-sdk-${RELEASE_VERSION}-x86_64-linux-gnu.asc
      • For macOS:

        $ gpg --verify operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin.asc

      If you do not have the maintainer’s public key on your workstation, you will get the following error:

      $ gpg --verify operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin.asc
      $ gpg: assuming signed data in 'operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin'
      $ gpg: Signature made Fri Apr  5 20:03:22 2019 CEST
      $ gpg:                using RSA key <key_id> 1
      $ gpg: Can't check signature: No public key
      1
      RSA key string.

      To download the key, run the following command, replacing <key_id> with the RSA key string provided in the output of the previous command:

      $ gpg [--keyserver keys.gnupg.net] --recv-key "<key_id>" 1
      1
      If you do not have a key server configured, specify one with the --keyserver option.
  4. Install the release binary in your PATH:

    • For Linux:

      $ chmod +x operator-sdk-${RELEASE_VERSION}-x86_64-linux-gnu
      $ sudo cp operator-sdk-${RELEASE_VERSION}-x86_64-linux-gnu /usr/local/bin/operator-sdk
      $ rm operator-sdk-${RELEASE_VERSION}-x86_64-linux-gnu
    • For macOS:

      $ chmod +x operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin
      $ sudo cp operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin /usr/local/bin/operator-sdk
      $ rm operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin
  5. Verify that the CLI tool was installed correctly:

    $ operator-sdk version

9.2.2.2. Installing from Homebrew

You can install the SDK CLI using Homebrew.

Prerequisites

  • Homebrew
  • docker v17.03+
  • OpenShift CLI (oc) v4.1+ installed
  • Access to a cluster based on Kubernetes v1.11.3+
  • Access to a container registry

Procedure

  1. Install the SDK CLI using the brew command:

    $ brew install operator-sdk
  2. Verify that the CLI tool was installed correctly:

    $ operator-sdk version

9.2.2.3. Compiling and installing from source

You can obtain the Operator SDK source code to compile and install the SDK CLI.

Prerequisites

  • dep v0.5.0+
  • Git
  • Go v1.10+
  • docker v17.03+
  • OpenShift CLI (oc) v4.1+ installed
  • Access to a cluster based on Kubernetes v1.11.3+
  • Access to a container registry

Procedure

  1. Clone the operator-sdk repository:

    $ mkdir -p $GOPATH/src/github.com/operator-framework
    $ cd $GOPATH/src/github.com/operator-framework
    $ git clone https://github.com/operator-framework/operator-sdk
    $ cd operator-sdk
  2. Check out the desired release branch:

    $ git checkout master
  3. Compile and install the SDK CLI:

    $ make dep
    $ make install

    This installs the CLI binary operator-sdk at $GOPATH/bin.

  4. Verify that the CLI tool was installed correctly:

    $ operator-sdk version

9.2.3. Building an Ansible-based Operator using the Operator SDK

This procedure walks through an example of building a simple Memcached Operator powered by Ansible playbooks and modules using tools and libraries provided by the Operator SDK.

Prerequisites

  • Operator SDK CLI installed on the development workstation
  • Access to a Kubernetes-based cluster v1.11.3+ (for example OpenShift Container Platform 4.1) using an account with cluster-admin permissions
  • OpenShift CLI (oc) v4.1+ installed
  • ansible v2.6.0+
  • ansible-runner v1.1.0+
  • ansible-runner-http v1.0.0+

Procedure

  1. Create a new Operator project, either namespace-scoped or cluster-scoped, using the operator-sdk new command. Choose one of the following:

    1. A namespace-scoped Operator (the default) watches and manages resources in a single namespace. Namespace-scoped operators are preferred because of their flexibility. They enable decoupled upgrades, namespace isolation for failures and monitoring, and differing API definitions.

      To create a new Ansible-based, namespace-scoped memcached-operator project and change to its directory, use the following commands:

      $ operator-sdk new memcached-operator \
          --api-version=cache.example.com/v1alpha1 \
          --kind=Memcached \
          --type=ansible
      $ cd memcached-operator

      This creates the memcached-operator project specifically for watching the Memcached resource with APIVersion example.com/v1apha1 and Kind Memcached.

    2. A cluster-scoped Operator watches and manages resources cluster-wide, which can be useful in certain cases. For example, the cert-manager operator is often deployed with cluster-scoped permissions and watches so that it can manage issuing certificates for an entire cluster.

      To create your memcached-operator project to be cluster-scoped and change to its directory, use the following commands:

      $ operator-sdk new memcached-operator \
          --cluster-scoped \
          --api-version=cache.example.com/v1alpha1 \
          --kind=Memcached \
          --type=ansible
      $ cd memcached-operator

      Using the --cluster-scoped flag scaffolds the new Operator with the following modifications:

      • deploy/operator.yaml: Set WATCH_NAMESPACE="" instead of setting it to the Pod’s namespace.
      • deploy/role.yaml: Use ClusterRole instead of Role.
      • deploy/role_binding.yaml:

        • Use ClusterRoleBinding instead of RoleBinding.
        • Set the subject namespace to REPLACE_NAMESPACE. This must be changed to the namespace in which the Operator is deployed.
  2. Customize the Operator logic.

    For this example, the memcached-operator executes the following reconciliation logic for each Memcached Custom Resource (CR):

    • Create a memcached Deployment if it does not exist.
    • Ensure that the Deployment size is the same as specified by the Memcached CR.

    By default, the memcached-operator watches Memcached resource events as shown in the watches.yaml file and executes the Ansible role Memcached:

    - version: v1alpha1
      group: cache.example.com
      kind: Memcached

    You can optionally customize the following logic in the watches.yaml file:

    1. Specifying a role option configures the Operator to use this specified path when launching ansible-runner with an Ansible role. By default, the new command fills in an absolute path to where your role should go:

      - version: v1alpha1
        group: cache.example.com
        kind: Memcached
        role: /opt/ansible/roles/memcached
    2. Specifying a playbook option in the watches.yaml file configures the Operator to use this specified path when launching ansible-runner with an Ansible playbook:

      - version: v1alpha1
        group: cache.example.com
        kind: Memcached
        playbook: /opt/ansible/playbook.yaml
  3. Build the Memcached Ansible role.

    Modify the generated Ansible role under the roles/memcached/ directory. This Ansible role controls the logic that is executed when a resource is modified.

    1. Define the Memcached spec.

      Defining the spec for an Ansible-based Operator can be done entirely in Ansible. The Ansible Operator passes all key-value pairs listed in the CR spec field along to Ansible as variables. The names of all variables in the spec field are converted to snake case (lowercase with an underscore) by the Operator before running Ansible. For example, serviceAccount in the spec becomes service_account in Ansible.

      Tip

      You should perform some type validation in Ansible on the variables to ensure that your application is receiving expected input.

      In case the user does not set the spec field, set a default by modifying the roles/memcached/defaults/main.yml file:

      size: 1
    2. Define the Memcached Deployment.

      With the Memcached spec now defined, you can define what Ansible is actually executed on resource changes. Because this is an Ansible role, the default behavior executes the tasks in the roles/memcached/tasks/main.yml file.

      The goal is for Ansible to create a Deployment if it does not exist, which runs the memcached:1.4.36-alpine image. Ansible 2.7+ supports the k8s Ansible module, which this example leverages to control the Deployment definition.

      Modify the roles/memcached/tasks/main.yml to match the following:

      - name: start memcached
        k8s:
          definition:
            kind: Deployment
            apiVersion: apps/v1
            metadata:
              name: '{{ meta.name }}-memcached'
              namespace: '{{ meta.namespace }}'
            spec:
              replicas: "{{size}}"
              selector:
                matchLabels:
                  app: memcached
              template:
                metadata:
                  labels:
                    app: memcached
                spec:
                  containers:
                  - name: memcached
                    command:
                    - memcached
                    - -m=64
                    - -o
                    - modern
                    - -v
                    image: "docker.io/memcached:1.4.36-alpine"
                    ports:
                      - containerPort: 11211
      Note

      This example used the size variable to control the number of replicas of the Memcached Deployment. This example sets the default to 1, but any user can create a CR that overwrites the default.

  4. Deploy the CRD.

    Before running the Operator, Kubernetes needs to know about the new Custom Resource Definition (CRD) the Operator will be watching. Deploy the Memcached CRD:

    $ oc create -f deploy/crds/cache_v1alpha1_memcached_crd.yaml
  5. Build and run the Operator.

    There are two ways to build and run the Operator:

    • As a Pod inside a Kubernetes cluster.
    • As a Go program outside the cluster using the operator-sdk up command.

    Choose one of the following methods:

    1. Run as a Pod inside a Kubernetes cluster. This is the preferred method for production use.

      1. Build the memcached-operator image and push it to a registry:

        $ operator-sdk build quay.io/example/memcached-operator:v0.0.1
        $ podman push quay.io/example/memcached-operator:v0.0.1
      2. Deployment manifests are generated in the deploy/operator.yaml file. The deployment image in this file needs to be modified from the placeholder REPLACE_IMAGE to the previous built image. To do this, run:

        $ sed -i 's|REPLACE_IMAGE|quay.io/example/memcached-operator:v0.0.1|g' deploy/operator.yaml
      3. If you created your Operator using the --cluster-scoped=true flag, update the service account namespace in the generated ClusterRoleBinding to match where you are deploying your Operator:

        $ export OPERATOR_NAMESPACE=$(oc config view --minify -o jsonpath='{.contexts[0].context.namespace}')
        $ sed -i "s|REPLACE_NAMESPACE|$OPERATOR_NAMESPACE|g" deploy/role_binding.yaml

        If you are performing these steps on OSX, use the following commands instead:

        $ sed -i "" 's|REPLACE_IMAGE|quay.io/example/memcached-operator:v0.0.1|g' deploy/operator.yaml
        $ sed -i "" "s|REPLACE_NAMESPACE|$OPERATOR_NAMESPACE|g" deploy/role_binding.yaml
      4. Deploy the memcached-operator:

        $ oc create -f deploy/service_account.yaml
        $ oc create -f deploy/role.yaml
        $ oc create -f deploy/role_binding.yaml
        $ oc create -f deploy/operator.yaml
      5. Verify that the memcached-operator is up and running:

        $ oc get deployment
        NAME                     DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
        memcached-operator       1         1         1            1           1m
    2. Run outside the cluster. This method is preferred during the development cycle to speed up deployment and testing.

      Ensure that Ansible Runner and Ansible Runner HTTP Plug-in are installed or else you will see unexpected errors from Ansible Runner when a CR is created.

      It is also important that the role path referenced in the watches.yaml file exists on your machine. Because normally a container is used where the role is put on disk, the role must be manually copied to the configured Ansible roles path (for example /etc/ansible/roles).

      1. To run the Operator locally with the default Kubernetes configuration file present at $HOME/.kube/config:

        $ operator-sdk up local

        To run the Operator locally with a provided Kubernetes configuration file:

        $ operator-sdk up local --kubeconfig=config
  6. Create a Memcached CR.

    1. Modify the deploy/crds/cache_v1alpha1_memcached_cr.yaml file as shown and create a Memcached CR:

      $ cat deploy/crds/cache_v1alpha1_memcached_cr.yaml
      apiVersion: "cache.example.com/v1alpha1"
      kind: "Memcached"
      metadata:
        name: "example-memcached"
      spec:
        size: 3
      
      $ oc apply -f deploy/crds/cache_v1alpha1_memcached_cr.yaml
    2. Ensure that the memcached-operator creates the Deployment for the CR:

      $ oc get deployment
      NAME                     DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
      memcached-operator       1         1         1            1           2m
      example-memcached        3         3         3            3           1m
    3. Check the Pods to confirm three replicas were created:

      $ oc get pods
      NAME                                  READY     STATUS    RESTARTS   AGE
      example-memcached-6fd7c98d8-7dqdr     1/1       Running   0          1m
      example-memcached-6fd7c98d8-g5k7v     1/1       Running   0          1m
      example-memcached-6fd7c98d8-m7vn7     1/1       Running   0          1m
      memcached-operator-7cc7cfdf86-vvjqk   1/1       Running   0          2m
  7. Update the size.

    1. Change the spec.size field in the memcached CR from 3 to 4 and apply the change:

      $ cat deploy/crds/cache_v1alpha1_memcached_cr.yaml
      apiVersion: "cache.example.com/v1alpha1"
      kind: "Memcached"
      metadata:
        name: "example-memcached"
      spec:
        size: 4
      
      $ oc apply -f deploy/crds/cache_v1alpha1_memcached_cr.yaml
    2. Confirm that the Operator changes the Deployment size:

      $ oc get deployment
      NAME                 DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
      example-memcached    4         4         4            4           5m
  8. Clean up the resources:

    $ oc delete -f deploy/crds/cache_v1alpha1_memcached_cr.yaml
    $ oc delete -f deploy/operator.yaml
    $ oc delete -f deploy/role_binding.yaml
    $ oc delete -f deploy/role.yaml
    $ oc delete -f deploy/service_account.yaml
    $ oc delete -f deploy/crds/cache_v1alpha1_memcached_crd.yaml

9.2.4. Managing application lifecycle using the k8s Ansible module

To manage the lifecycle of your application on Kubernetes using Ansible, you can use the k8s Ansible module. This Ansible module allows a developer to either leverage their existing Kubernetes resource files (written in YAML) or express the lifecycle management in native Ansible.

One of the biggest benefits of using Ansible in conjunction with existing Kubernetes resource files is the ability to use Jinja templating so that you can customize resources with the simplicity of a few variables in Ansible.

This section goes into detail on usage of the k8s Ansible module. To get started, install the module on your local workstation and test it using a playbook before moving on to using it within an Operator.

9.2.4.1. Installing the k8s Ansible module

To install the k8s Ansible module on your local workstation:

Procedure

  1. Install Ansible 2.6+:

    $ sudo yum install ansible
  2. Install the OpenShift python client package using pip:

    $ pip install openshift

9.2.4.2. Testing the k8s Ansible module locally

Sometimes, it is beneficial for a developer to run the Ansible code from their local machine as opposed to running and rebuilding the Operator each time.

Procedure

  1. Initialize a new Ansible-based Operator project:

    $ operator-sdk new --type ansible --kind Foo --api-version foo.example.com/v1alpha1 foo-operator
    Create foo-operator/tmp/init/galaxy-init.sh
    Create foo-operator/tmp/build/Dockerfile
    Create foo-operator/tmp/build/test-framework/Dockerfile
    Create foo-operator/tmp/build/go-test.sh
    Rendering Ansible Galaxy role [foo-operator/roles/Foo]...
    Cleaning up foo-operator/tmp/init
    Create foo-operator/watches.yaml
    Create foo-operator/deploy/rbac.yaml
    Create foo-operator/deploy/crd.yaml
    Create foo-operator/deploy/cr.yaml
    Create foo-operator/deploy/operator.yaml
    Run git init ...
    Initialized empty Git repository in /home/dymurray/go/src/github.com/dymurray/opsdk/foo-operator/.git/
    Run git init done
    $ cd foo-operator
  2. Modify the roles/Foo/tasks/main.yml file with the desired Ansible logic. This example creates and deletes a namespace with the switch of a variable.

    - name: set test namespace to {{ state }}
      k8s:
        api_version: v1
        kind: Namespace
        state: "{{ state }}"
      ignore_errors: true 1
    1
    Setting ignore_errors: true ensures that deleting a nonexistent project does not fail.
  3. Modify the roles/Foo/defaults/main.yml file to set state to present by default.

    state: present
  4. Create an Ansible playbook playbook.yml in the top-level directory, which includes the Foo role:

    - hosts: localhost
      roles:
        - Foo
  5. Run the playbook:

    $ ansible-playbook playbook.yml
     [WARNING]: provided hosts list is empty, only localhost is available. Note that the implicit localhost does not match 'all'
    
    PLAY [localhost] ***************************************************************************
    
    TASK [Gathering Facts] *********************************************************************
    ok: [localhost]
    
    Task [Foo : set test namespace to present]
    changed: [localhost]
    
    PLAY RECAP *********************************************************************************
    localhost                  : ok=2    changed=1    unreachable=0    failed=0
  6. Check that the namespace was created:

    $ oc get namespace
    NAME          STATUS    AGE
    default       Active    28d
    kube-public   Active    28d
    kube-system   Active    28d
    test          Active    3s
  7. Rerun the playbook setting state to absent:

    $ ansible-playbook playbook.yml --extra-vars state=absent
     [WARNING]: provided hosts list is empty, only localhost is available. Note that the implicit localhost does not match 'all'
    
    PLAY [localhost] ***************************************************************************
    
    TASK [Gathering Facts] *********************************************************************
    ok: [localhost]
    
    Task [Foo : set test namespace to absent]
    changed: [localhost]
    
    PLAY RECAP *********************************************************************************
    localhost                  : ok=2    changed=1    unreachable=0    failed=0
  8. Check that the namespace was deleted:

    $ oc get namespace
    NAME          STATUS    AGE
    default       Active    28d
    kube-public   Active    28d
    kube-system   Active    28d

9.2.4.3. Testing the k8s Ansible module inside an Operator

After you are familiar using the k8s Ansible module locally, you can trigger the same Ansible logic inside of an Operator when a Custom Resource (CR) changes. This example maps an Ansible role to a specific Kubernetes resource that the Operator watches. This mapping is done in the Watches file.

9.2.4.3.1. Testing an Ansible-based Operator locally

After getting comfortable testing Ansible workflows locally, you can test the logic inside of an Ansible-based Operator running locally.

To do so, use the operator-sdk up local command from the top-level directory of your Operator project. This command reads from the ./watches.yaml file and uses the ~/.kube/config file to communicate with a Kubernetes cluster just as the k8s Ansible module does.

Procedure

  1. Because the up local command reads from the ./watches.yaml file, there are options available to the Operator author. If role is left alone (by default, /opt/ansible/roles/<name>) you must copy the role over to the /opt/ansible/roles/ directory from the Operator directly.

    This is cumbersome because changes are not reflected from the current directory. Instead, change the role field to point to the current directory and comment out the existing line:

    - version: v1alpha1
      group: foo.example.com
      kind: Foo
      #  role: /opt/ansible/roles/Foo
      role: /home/user/foo-operator/Foo
  2. Create a Custom Resource Definiton (CRD) and proper role-based access control (RBAC) definitions for the Custom Resource (CR) Foo. The operator-sdk command autogenerates these files inside of the deploy/ directory:

    $ oc create -f deploy/crds/foo_v1alpha1_foo_crd.yaml
    $ oc create -f deploy/service_account.yaml
    $ oc create -f deploy/role.yaml
    $ oc create -f deploy/role_binding.yaml
  3. Run the up local command:

    $ operator-sdk up local
    [...]
    INFO[0000] Starting to serve on 127.0.0.1:8888
    INFO[0000] Watching foo.example.com/v1alpha1, Foo, default
  4. Now that the Operator is watching the resource Foo for events, the creation of a CR triggers your Ansible role to execute. View the deploy/cr.yaml file:

    apiVersion: "foo.example.com/v1alpha1"
    kind: "Foo"
    metadata:
      name: "example"

    Because the spec field is not set, Ansible is invoked with no extra variables. The next section covers how extra variables are passed from a CR to Ansible. This is why it is important to set sane defaults for the Operator.

  5. Create a CR instance of Foo with the default variable state set to present:

    $ oc create -f deploy/cr.yaml
  6. Check that the namespace test was created:

    $ oc get namespace
    NAME          STATUS    AGE
    default       Active    28d
    kube-public   Active    28d
    kube-system   Active    28d
    test          Active    3s
  7. Modify the deploy/cr.yaml file to set the state field to absent:

    apiVersion: "foo.example.com/v1alpha1"
    kind: "Foo"
    metadata:
      name: "example"
    spec:
      state: "absent"
  8. Apply the changes and confirm that the namespace is deleted:

    $ oc apply -f deploy/cr.yaml
    
    $ oc get namespace
    NAME          STATUS    AGE
    default       Active    28d
    kube-public   Active    28d
    kube-system   Active    28d
9.2.4.3.2. Testing an Ansible-based Operator on a cluster

After getting familiar running Ansible logic inside of an Ansible-based Operator locally, you can test the Operator inside of a Pod on a Kubernetes cluster, such as OpenShift Container Platform. Running as a Pod on a cluster is preferred for production use.

Procedure

  1. Build the foo-operator image and push it to a registry:

    $ operator-sdk build quay.io/example/foo-operator:v0.0.1
    $ podman push quay.io/example/foo-operator:v0.0.1
  2. Deployment manifests are generated in the deploy/operator.yaml file. The Deployment image in this file must be modified from the placeholder REPLACE_IMAGE to the previously-built image. To do so, run the following command:

    $ sed -i 's|REPLACE_IMAGE|quay.io/example/foo-operator:v0.0.1|g' deploy/operator.yaml

    If you are performing these steps on OSX, use the following command instead:

    $ sed -i "" 's|REPLACE_IMAGE|quay.io/example/foo-operator:v0.0.1|g' deploy/operator.yaml
  3. Deploy the foo-operator:

    $ oc create -f deploy/crds/foo_v1alpha1_foo_crd.yaml # if CRD doesn't exist already
    $ oc create -f deploy/service_account.yaml
    $ oc create -f deploy/role.yaml
    $ oc create -f deploy/role_binding.yaml
    $ oc create -f deploy/operator.yaml
  4. Verify that the foo-operator is up and running:

    $ oc get deployment
    NAME                     DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
    foo-operator       1         1         1            1           1m

9.2.5. Managing Custom Resource status using the k8s_status Ansible module

Ansible-based Operators automatically update Custom Resource (CR) status subresources with generic information about the previous Ansible run. This includes the number of successful and failed tasks and relevant error messages as shown:

status:
  conditions:
    - ansibleResult:
      changed: 3
      completion: 2018-12-03T13:45:57.13329
      failures: 1
      ok: 6
      skipped: 0
    lastTransitionTime: 2018-12-03T13:45:57Z
    message: 'Status code was -1 and not [200]: Request failed: <urlopen error [Errno
      113] No route to host>'
    reason: Failed
    status: "True"
    type: Failure
  - lastTransitionTime: 2018-12-03T13:46:13Z
    message: Running reconciliation
    reason: Running
    status: "True"
    type: Running

Ansible-based Operators also allow Operator authors to supply custom status values with the k8s_status Ansible module. This allows the author to update the status from within Ansible with any key-value pair as desired.

By default, Ansible-based Operators always include the generic Ansible run output as shown above. If you would prefer your application did not update the status with Ansible output, you can track the status manually from your application.

Procedure

  1. To track CR status manually from your application, update the Watches file with a manageStatus field set to false:

    - version: v1
      group: api.example.com
      kind: Foo
      role: /opt/ansible/roles/Foo
      manageStatus: false
  2. Then, use the k8s_status Ansible module to update the subresource. For example, to update with key foo and value bar, k8s_status can be used as shown:

    - k8s_status:
      api_version: app.example.com/v1
      kind: Foo
      name: "{{ meta.name }}"
      namespace: "{{ meta.namespace }}"
      status:
        foo: bar

Additional resources

9.2.5.1. Using the k8s_status Ansible module when testing locally

If your Operator takes advantage of the k8s_status Ansible module and you want to test the Operator locally with the operator-sdk up local command, you must install the module in a location that Ansible expects. This is done with the library configuration option for Ansible.

For this example, assume the user is placing third-party Ansible modules in the /usr/share/ansible/library/ directory.

Procedure

  1. To install the k8s_status module, set the ansible.cfg file to search in the /usr/share/ansible/library/ directory for installed Ansible modules:

    $ echo "library=/usr/share/ansible/library/" >> /etc/ansible/ansible.cfg
  2. Add the k8s_status.py file to the /usr/share/ansible/library/ directory:

    $ wget https://raw.githubusercontent.com/openshift/ocp-release-operator-sdk/master/library/k8s_status.py -O /usr/share/ansible/library/k8s_status.py

9.2.6. Additional resources

9.3. Creating Helm-based Operators

This guide outlines Helm chart support in the Operator SDK and walks Operator authors through an example of building and running an Nginx Operator with the operator-sdk CLI tool that uses an existing Helm chart.

9.3.1. Helm chart support in the Operator SDK

The Operator Framework is an open source toolkit to manage Kubernetes native applications, called Operators, in an effective, automated, and scalable way. This framework includes the Operator SDK, which assists developers in bootstrapping and building an Operator based on their expertise without requiring knowledge of Kubernetes API complexities.

One of the Operator SDK’s options for generating an Operator project includes leveraging an existing Helm chart to deploy Kubernetes resources as a unified application, without having to write any Go code. Such Helm-based Operators are designed to excel at stateless applications that require very little logic when rolled out, because changes should be applied to the Kubernetes objects that are generated as part of the chart. This may sound limiting, but can be sufficient for a surprising amount of use-cases as shown by the proliferation of Helm charts built by the Kubernetes community.

The main function of an Operator is to read from a custom object that represents your application instance and have its desired state match what is running. In the case of a Helm-based Operator, the object’s spec field is a list of configuration options that are typically described in Helm’s values.yaml file. Instead of setting these values with flags using the Helm CLI (for example, helm install -f values.yaml), you can express them within a Custom Resource (CR), which, as a native Kubernetes object, enables the benefits of RBAC applied to it and an audit trail.

For an example of a simple CR called Tomcat:

apiVersion: apache.org/v1alpha1
kind: Tomcat
metadata:
  name: example-app
spec:
  replicaCount: 2

The replicaCount value, 2 in this case, is propagated into the chart’s templates where following is used:

{{ .Values.replicaCount }}

After an Operator is built and deployed, you can deploy a new instance of an app by creating a new instance of a CR, or list the different instances running in all environments using the oc command:

$ oc get Tomcats --all-namespaces

There is no requirement use the Helm CLI or install Tiller; Helm-based Operators import code from the Helm project. All you have to do is have an instance of the Operator running and register the CR with a Custom Resource Definition (CRD). And because it obeys RBAC, you can more easily prevent production changes.

9.3.2. Installing the Operator SDK CLI

The Operator SDK has a CLI tool that assists developers in creating, building, and deploying a new Operator project. You can install the SDK CLI on your workstation so you are prepared to start authoring your own Operators.

Note

This guide uses minikube v0.25.0+ as the local Kubernetes cluster and quay.io for the public registry.

9.3.2.1. Installing from GitHub release

You can download and install a pre-built release binary of the SDK CLI from the project on GitHub.

Prerequisites

  • docker v17.03+
  • OpenShift CLI (oc) v4.1+ installed
  • Access to a cluster based on Kubernetes v1.11.3+
  • Access to a container registry

Procedure

  1. Set the release version variable:

    RELEASE_VERSION=v0.8.0
  2. Download the release binary.

    • For Linux:

      $ curl -OJL https://github.com/operator-framework/operator-sdk/releases/download/${RELEASE_VERSION}/operator-sdk-${RELEASE_VERSION}-x86_64-linux-gnu
    • For macOS:

      $ curl -OJL https://github.com/operator-framework/operator-sdk/releases/download/${RELEASE_VERSION}/operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin
  3. Verify the downloaded release binary.

    1. Download the provided ASC file.

      • For Linux:

        $ curl -OJL https://github.com/operator-framework/operator-sdk/releases/download/${RELEASE_VERSION}/operator-sdk-${RELEASE_VERSION}-x86_64-linux-gnu.asc
      • For macOS:

        $ curl -OJL https://github.com/operator-framework/operator-sdk/releases/download/${RELEASE_VERSION}/operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin.asc
    2. Place the binary and corresponding ASC file into the same directory and run the following command to verify the binary:

      • For Linux:

        $ gpg --verify operator-sdk-${RELEASE_VERSION}-x86_64-linux-gnu.asc
      • For macOS:

        $ gpg --verify operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin.asc

      If you do not have the maintainer’s public key on your workstation, you will get the following error:

      $ gpg --verify operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin.asc
      $ gpg: assuming signed data in 'operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin'
      $ gpg: Signature made Fri Apr  5 20:03:22 2019 CEST
      $ gpg:                using RSA key <key_id> 1
      $ gpg: Can't check signature: No public key
      1
      RSA key string.

      To download the key, run the following command, replacing <key_id> with the RSA key string provided in the output of the previous command:

      $ gpg [--keyserver keys.gnupg.net] --recv-key "<key_id>" 1
      1
      If you do not have a key server configured, specify one with the --keyserver option.
  4. Install the release binary in your PATH:

    • For Linux:

      $ chmod +x operator-sdk-${RELEASE_VERSION}-x86_64-linux-gnu
      $ sudo cp operator-sdk-${RELEASE_VERSION}-x86_64-linux-gnu /usr/local/bin/operator-sdk
      $ rm operator-sdk-${RELEASE_VERSION}-x86_64-linux-gnu
    • For macOS:

      $ chmod +x operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin
      $ sudo cp operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin /usr/local/bin/operator-sdk
      $ rm operator-sdk-${RELEASE_VERSION}-x86_64-apple-darwin
  5. Verify that the CLI tool was installed correctly:

    $ operator-sdk version

9.3.2.2. Installing from Homebrew

You can install the SDK CLI using Homebrew.

Prerequisites

  • Homebrew
  • docker v17.03+
  • OpenShift CLI (oc) v4.1+ installed
  • Access to a cluster based on Kubernetes v1.11.3+
  • Access to a container registry

Procedure

  1. Install the SDK CLI using the brew command:

    $ brew install operator-sdk
  2. Verify that the CLI tool was installed correctly:

    $ operator-sdk version

9.3.2.3. Compiling and installing from source

You can obtain the Operator SDK source code to compile and install the SDK CLI.

Prerequisites

  • dep v0.5.0+
  • Git
  • Go v1.10+
  • docker v17.03+
  • OpenShift CLI (oc) v4.1+ installed
  • Access to a cluster based on Kubernetes v1.11.3+
  • Access to a container registry

Procedure

  1. Clone the operator-sdk repository:

    $ mkdir -p $GOPATH/src/github.com/operator-framework
    $ cd $GOPATH/src/github.com/operator-framework
    $ git clone https://github.com/operator-framework/operator-sdk
    $ cd operator-sdk
  2. Check out the desired release branch:

    $ git checkout master
  3. Compile and install the SDK CLI:

    $ make dep
    $ make install

    This installs the CLI binary operator-sdk at $GOPATH/bin.

  4. Verify that the CLI tool was installed correctly:

    $ operator-sdk version

9.3.3. Building a Helm-based Operator using the Operator SDK

This procedure walks through an example of building a simple Nginx Operator powered by a Helm chart using tools and libraries provided by the Operator SDK.

Tip

It is best practice to build a new Operator for each chart. This can allow for more native-behaving Kubernetes APIs (for example, oc get Nginx) and flexibility if you ever want to write a fully-fledged Operator in Go, migrating away from a Helm-based Operator.

Prerequisites

  • Operator SDK CLI installed on the development workstation
  • Access to a Kubernetes-based cluster v1.11.3+ (for example OpenShift Container Platform 4.1) using an account with cluster-admin permissions
  • OpenShift CLI (oc) v4.1+ installed

Procedure

  1. Create a new Operator project, either namespace-scoped or cluster-scoped, using the operator-sdk new command. Choose one of the following:

    1. A namespace-scoped Operator (the default) watches and manages resources in a single namespace. Namespace-scoped operators are preferred because of their flexibility. They enable decoupled upgrades, namespace isolation for failures and monitoring, and differing API definitions.

      To create a new Helm-based, namespace-scoped nginx-operator project, use the following command:

      $ operator-sdk new nginx-operator \
        --api-version=example.com/v1alpha1 \
        --kind=Nginx \
        --type=helm
      $ cd nginx-operator

      This creates the nginx-operator project specifically for watching the Nginx resource with APIVersion example.com/v1apha1 and Kind Nginx.

    2. A cluster-scoped Operator watches and manages resources cluster-wide, which can be useful in certain cases. For example, the cert-manager operator is often deployed with cluster-scoped permissions and watches so that it can manage issuing certificates for an entire cluster.

      To create your nginx-operator project to be cluster-scoped, use the following command:

      $ operator-sdk new nginx-operator \
          --cluster-scoped \
          --api-version=example.com/v1alpha1 \
          --kind=Nginx \
          --type=helm

      Using the --cluster-scoped flag scaffolds the new Operator with the following modifications:

      • deploy/operator.yaml: Set WATCH_NAMESPACE="" instead of setting it to the Pod’s namespace.
      • deploy/role.yaml: Use ClusterRole instead of Role.
      • deploy/role_binding.yaml:

        • Use ClusterRoleBinding instead of RoleBinding.
        • Set the subject namespace to REPLACE_NAMESPACE. This must be changed to the namespace in which the Operator is deployed.
  2. Customize the Operator logic.

    For this example, the nginx-operator executes the following reconciliation logic for each Nginx Custom Resource (CR):

    • Create a Nginx Deployment if it does not exist.
    • Create a Nginx Service if it does not exist.
    • Create a Nginx Ingress if it is enabled and does not exist.
    • Ensure that the Deployment, Service, and optional Ingress match the desired configuration (for example, replica count, image, service type) as specified by the Nginx CR.

    By default, the nginx-operator watches Nginx resource events as shown in the watches.yaml file and executes Helm releases using the specified chart:

    - version: v1alpha1
      group: example.com
      kind: Nginx
      chart: /opt/helm/helm-charts/nginx
    1. Review the Nginx Helm chart.

      When a Helm Operator project is created, the Operator SDK creates an example Helm chart that contains a set of templates for a simple Nginx release.

      For this example, templates are available for Deployment, Service, and Ingress resources, along with a NOTES.txt template, which Helm chart developers use to convey helpful information about a release.

      If you are not already familiar with Helm Charts, take a moment to review the Helm Chart developer documentation.

    2. Understand the Nginx CR spec.

      Helm uses a concept called values to provide customizations to a Helm chart’s defaults, which are defined in the Helm chart’s values.yaml file.

      Override these defaults by setting the desired values in the CR spec. You can use the number of replicas as an example:

      1. First, inspect the helm-charts/nginx/values.yaml file to find that the chart has a value called replicaCount and it is set to 1 by default. To have 2 Nginx instances in your deployment, your CR spec must contain replicaCount: 2.

        Update the deploy/crds/example_v1alpha1_nginx_cr.yaml file to look like the following:

        apiVersion: example.com/v1alpha1
        kind: Nginx
        metadata:
          name: example-nginx
        spec:
          replicaCount: 2
      2. Similarly, the default service port is set to 80. To instead use 8080, update the deploy/crds/example_v1alpha1_nginx_cr.yaml file again by adding the service port override:

        apiVersion: example.com/v1alpha1
        kind: Nginx
        metadata:
          name: example-nginx
        spec:
          replicaCount: 2
          service:
            port: 8080

        The Helm Operator applies the entire spec as if it was the contents of a values file, just like the helm install -f ./overrides.yaml command works.

  3. Deploy the CRD.

    Before running the Operator, Kubernetes needs to know about the new custom resource definition (CRD) the operator will be watching. Deploy the following CRD:

    $ oc create -f deploy/crds/example_v1alpha1_nginx_crd.yaml
  4. Build and run the Operator.

    There are two ways to build and run the Operator:

    • As a Pod inside a Kubernetes cluster.
    • As a Go program outside the cluster using the operator-sdk up command.

    Choose one of the following methods:

    1. Run as a Pod inside a Kubernetes cluster. This is the preferred method for production use.

      1. Build the nginx-operator image and push it to a registry:

        $ operator-sdk build quay.io/example/nginx-operator:v0.0.1
        $ docker push quay.io/example/nginx-operator:v0.0.1
      2. Deployment manifests are generated in the deploy/operator.yaml file. The deployment image in this file needs to be modified from the placeholder REPLACE_IMAGE to the previous built image. To do this, run:

        $ sed -i 's|REPLACE_IMAGE|quay.io/example/nginx-operator:v0.0.1|g' deploy/operator.yaml
      3. If you created your Operator using the --cluster-scoped=true flag, update the service account namespace in the generated ClusterRoleBinding to match where you are deploying your Operator:

        $ export OPERATOR_NAMESPACE=$(oc config view --minify -o jsonpath='{.contexts[0].context.namespace}')
        $ sed -i "s|REPLACE_NAMESPACE|$OPERATOR_NAMESPACE|g" deploy/role_binding.yaml

        If you are performing these steps on OSX, use the following commands instead:

        $ sed -i "" 's|REPLACE_IMAGE|quay.io/example/nginx-operator:v0.0.1|g' deploy/operator.yaml
        $ sed -i "" "s|REPLACE_NAMESPACE|$OPERATOR_NAMESPACE|g" deploy/role_binding.yaml
      4. Deploy the nginx-operator:

        $ oc create -f deploy/service_account.yaml
        $ oc create -f deploy/role.yaml
        $ oc create -f deploy/role_binding.yaml
        $ oc create -f deploy/operator.yaml
      5. Verify that the nginx-operator is up and running:

        $ oc get deployment
        NAME                 DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
        nginx-operator       1         1         1            1           1m
    2. Run outside the cluster. This method is preferred during the development cycle to speed up deployment and testing.

      It is important that the chart path referenced in the watches.yaml file exists on your machine. By default, the watches.yaml file is scaffolded to work with an Operator image built with the operator-sdk build command. When developing and testing your operator with the operator-sdk up local command, the SDK looks in your local file system for this path.

      1. Create a symlink at this location to point to your Helm chart’s path:

        $ sudo mkdir -p /opt/helm/helm-charts
        $ sudo ln -s $PWD/helm-charts/nginx /opt/helm/helm-charts/nginx
      2. To run the Operator locally with the default Kubernetes configuration file present at $HOME/.kube/config:

        $ operator-sdk up local

        To run the Operator locally with a provided Kubernetes configuration file:

        $ operator-sdk up local --kubeconfig=<path_to_config>
  5. Deploy the Nginx CR.

    Apply the Nginx CR that you modified earlier:

    $ oc apply -f deploy/crds/example_v1alpha1_nginx_cr.yaml

    Ensure that the nginx-operator creates the Deployment for the CR:

    $ oc get deployment
    NAME                                           DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
    example-nginx-b9phnoz9spckcrua7ihrbkrt1        2         2         2            2           1m

    Check the Pods to confirm two replicas were created:

    $ oc get pods
    NAME                                                      READY     STATUS    RESTARTS   AGE
    example-nginx-b9phnoz9spckcrua7ihrbkrt1-f8f9c875d-fjcr9   1/1       Running   0          1m
    example-nginx-b9phnoz9spckcrua7ihrbkrt1-f8f9c875d-ljbzl   1/1       Running   0          1m

    Check that the Service port is set to 8080:

    $ oc get service
    NAME                                      TYPE        CLUSTER-IP   EXTERNAL-IP   PORT(S)    AGE
    example-nginx-b9phnoz9spckcrua7ihrbkrt1   ClusterIP   10.96.26.3   <none>        8080/TCP   1m
  6. Update the replicaCount and remove the port.

    Change the spec.replicaCount field from 2 to 3, remove the spec.service field, and apply the change:

    $ cat deploy/crds/example_v1alpha1_nginx_cr.yaml
    apiVersion: "example.com/v1alpha1"
    kind: "Nginx"
    metadata:
      name: "example-nginx"
    spec:
      replicaCount: 3
    
    $ oc apply -f deploy/crds/example_v1alpha1_nginx_cr.yaml

    Confirm that the Operator changes the Deployment size:

    $ oc get deployment
    NAME                                           DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
    example-nginx-b9phnoz9spckcrua7ihrbkrt1        3         3         3            3           1m

    Check that the Service port is set to the default 80:

    $ oc get service
    NAME                                      TYPE        CLUSTER-IP   EXTERNAL-IP   PORT(S)  AGE
    example-nginx-b9phnoz9spckcrua7ihrbkrt1   ClusterIP   10.96.26.3   <none>        80/TCP   1m
  7. Clean up the resources:

    $ oc delete -f deploy/crds/example_v1alpha1_nginx_cr.yaml
    $ oc delete -f deploy/operator.yaml
    $ oc delete -f deploy/role_binding.yaml
    $ oc delete -f deploy/role.yaml
    $ oc delete -f deploy/service_account.yaml
    $ oc delete -f deploy/crds/example_v1alpha1_nginx_crd.yaml

9.3.4. Additional resources

9.4. Generating a ClusterServiceVersion (CSV)

A ClusterServiceVersion (CSV) is a YAML manifest created from Operator metadata that assists the Operator Lifecycle Manager (OLM) in running the Operator in a cluster. It is the metadata that accompanies an Operator container image, used to populate user interfaces with information like its logo, description, and version. It is also a source of technical information that is required to run the Operator, like the RBAC rules it requires and which Custom Resources (CRs) it manages or depends on.

The Operator SDK includes the olm-catalog gen-csv subcommand to generate a ClusterServiceVersion (CSV) for the current Operator project customized using information contained in manually-defined YAML manifests and Operator source files.

A CSV-generating command removes the responsibility of Operator authors having in-depth Operator Lifecycle Manager (OLM) knowledge in order for their Operator to interact with OLM or publish metadata to the Catalog Registry. Further, because the CSV spec will likely change over time as new Kubernetes and OLM features are implemented, the Operator SDK is equipped to easily extend its update system to handle new CSV features going forward.

The CSV version is the same as the Operator’s, and a new CSV is generated when upgrading Operator versions. Operator authors can use the --csv-version flag to have their Operators' state encapsulated in a CSV with the supplied semantic version:

$ operator-sdk olm-catalog gen-csv --csv-version <version>

This action is idempotent and only updates the CSV file when a new version is supplied, or a YAML manifest or source file is changed. Operator authors should not have to directly modify most fields in a CSV manifest. Those that require modification are defined in this guide. For example, the CSV version must be included in metadata.name.

9.4.1. How CSV generation works

An Operator project’s deploy/ directory is the standard location for all manifests required to deploy an Operator. The Operator SDK can use data from manifests in deploy/ to write a CSV. The following command:

$ operator-sdk olm-catalog gen-csv --csv-version <version>

writes a CSV YAML file to the deploy/olm-catalog/ directory by default.

Exactly three types of manifests are required to generate a CSV:

  • operator.yaml
  • *_{crd,cr}.yaml
  • RBAC role files, for example role.yaml

Operator authors may have different versioning requirements for these files and can configure which specific files are included in the deploy/olm-catalog/csv-config.yaml file.

Workflow

Depending on whether an existing CSV is detected, and assuming all configuration defaults are used, the olm-catalog gen-csv subcommand either:

  • Creates a new CSV, with the same location and naming convention as exists currently, using available data in YAML manifests and source files.

    1. The update mechanism checks for an existing CSV in deploy/. When one is not found, it creates a ClusterServiceVersion object, referred to here as a cache, and populates fields easily derived from Operator metadata, such as Kubernetes API ObjectMeta.
    2. The update mechanism searches deploy/ for manifests that contain data a CSV uses, such as a Deployment resource, and sets the appropriate CSV fields in the cache with this data.
    3. After the search completes, every cache field populated is written back to a CSV YAML file.

or:

  • Updates an existing CSV at the currently pre-defined location, using available data in YAML manifests and source files.

    1. The update mechanism checks for an existing CSV in deploy/. When one is found, the CSV YAML file contents are marshaled into a ClusterServiceVersion cache.
    2. The update mechanism searches deploy/ for manifests that contain data a CSV uses, such as a Deployment resource, and sets the appropriate CSV fields in the cache with this data.
    3. After the search completes, every cache field populated is written back to a CSV YAML file.
Note

Individual YAML fields are overwritten and not the entire file, as descriptions and other non-generated parts of a CSV should be preserved.

9.4.2. CSV composition configuration

Operator authors can configure CSV composition by populating several fields in the deploy/olm-catalog/csv-config.yaml file:

FieldDescription

operator-path (string)

The Operator resource manifest file path. Defaults to deploy/operator.yaml.

crd-cr-path-list (string(, string)*)

A list of CRD and CR manifest file paths. Defaults to [deploy/crds/*_{crd,cr}.yaml].

rbac-path-list (string(, string)*)

A list of RBAC role manifest file paths. Defaults to [deploy/role.yaml].

9.4.3. Manually-defined CSV fields

Many CSV fields cannot be populated using generated, non-SDK-specific manifests. These fields are mostly human-written, English metadata about the Operator and various Custom Resource Definitions (CRDs).

Operator authors must directly modify their CSV YAML file, adding personalized data to the following required fields. The Operator SDK gives a warning CSV generation when a lack of data in any of the required fields is detected.

Table 9.5. Required

FieldDescription

metadata.name

A unique name for this CSV. Operator version should be included in the name to ensure uniqueness, for example app-operator.v0.1.1.

spec.displayName

A public name to identify the Operator.

spec.description

A short description of the Operator’s functionality.

spec.keywords

Keywords describing the operator.

spec.maintainers

Human or organizational entities maintaining the Operator, with a name and email.

spec.provider

The Operators' provider (usually an organization), with a name.

spec.labels

Key-value pairs to be used by Operator internals.

spec.version

Semantic version of the Operator, for example 0.1.1.

spec.customresourcedefinitions

Any CRDs the Operator uses. This field is populated automatically by the Operator SDK if any CRD YAML files are present in deploy/. However, several fields not in the CRD manifest spec that require user input (more details in the CSV CRD spec section):

  • description: description of the CRD.
  • resources: any Kubernetes resources leveraged by the CRD, for example Pods and StatefulSets.
  • specDescriptors: UI hints for inputs and outputs of the Operator.

Table 9.6. Optional

FieldDescription

spec.replaces

The name of the CSV being replaced by this CSV.

spec.links

URLs (for example, websites and documentation) pertaining to the Operator or application being managed, each with a name and url.

spec.selector

Selectors by which the Operator can pair resources in a cluster.

spec.icon

A base64-encoded icon unique to the Operator, set in a base64data field with a mediatype.

spec.maturity

The Operator’s capability level according to the Operator maturity model, for example Seamless Upgrades.

Further details on what data each field above should hold are found in the CSV spec.

Note

Several YAML fields currently requiring user intervention can potentially be parsed from Operator code; such Operator SDK functionality will be addressed in a future design document.

Additional resources

9.4.4. Generating a CSV

Prerequisites

  • An Operator project generated using the Operator SDK

Procedure

  1. In your Operator project, configure your CSV composition by modifying the deploy/olm-catalog/csv-config.yaml file, if desired.
  2. Generate the CSV:

    $ operator-sdk olm-catalog gen-csv --csv-version <version>
  3. In the new CSV generated in the deploy/olm-catalog/ directory, ensure all required, manually-defined fields are set appropriately.

9.5. Configuring built-in monitoring with Prometheus

This guide describes the built-in monitoring support provided by the Operator SDK using the Prometheus Operator and details usage for Operator authors.

9.5.1. Prometheus Operator support

Prometheus is an open-source systems monitoring and alerting toolkit. The Prometheus Operator creates, configures, and manages Prometheus clusters running on Kubernetes-based clusters, such as OpenShift Container Platform.

Helper functions exist in the Operator SDK by default to automatically set up metrics in any generated Go-based Operator for use on clusters where the Prometheus Operator is deployed.

9.5.2. Metrics helper

In Go-based Operators generated using the Operator SDK, the following function exposes general metrics about the running program:

func ExposeMetricsPort(ctx context.Context, port int32) (*v1.Service, error)

These metrics are inherited from the controller-runtime library API. By default, the metrics are served on 0.0.0.0:8383/metrics.

A Service object is created with the metrics port exposed, which can be then accessed by Prometheus. The Service object is garbage collected when the leader Pod’s root owner is deleted.

The following example is present in the cmd/manager/main.go file in all Operators generated using the Operator SDK:

import(
    "github.com/operator-framework/operator-sdk/pkg/metrics"
    "machine.openshift.io/controller-runtime/pkg/manager"
)

var (
    // Change the below variables to serve metrics on a different host or port.
    metricsHost       = "0.0.0.0" 1
    metricsPort int32 = 8383 2
)
...
func main() {
    ...
    // Pass metrics address to controller-runtime manager
    mgr, err := manager.New(cfg, manager.Options{
        Namespace:          namespace,
        MetricsBindAddress: fmt.Sprintf("%s:%d", metricsHost, metricsPort),
    })

    ...
    // Create Service object to expose the metrics port.
    _, err = metrics.ExposeMetricsPort(ctx, metricsPort)
    if err != nil {
        // handle error
        log.Info(err.Error())
    }
    ...
}
1
The host that the metrics are exposed on.
2
The port that the metrics are exposed on.

9.5.2.1. Modifying the metrics port

Operator authors can modify the port that metrics are exposed on.

Prerequisites

  • Go-based Operator generated using the Operator SDK
  • Kubernetes-based cluster with the Prometheus Operator deployed

Procedure

  • In the generated Operator’s cmd/manager/main.go file, change the value of metricsPort in the line var metricsPort int32 = 8383.

9.5.3. ServiceMonitor resources

A ServiceMonitor is a Custom Resource Definition (CRD) provided by the Prometheus Operator that discovers the Endpoints in Service objects and configures Prometheus to monitor those Pods.

In Go-based Operators generated using the Operator SDK, the GenerateServiceMonitor() helper function can take a Service object and generate a ServiceMonitor Custom Resource (CR) based on it.

Additional resources

9.5.3.1. Creating ServiceMonitor resources

Operator authors can add Service target discovery of created monitoring Services using the metrics.CreateServiceMonitor() helper function, which accepts the newly created Service.

Prerequisites

  • Go-based Operator generated using the Operator SDK
  • Kubernetes-based cluster with the Prometheus Operator deployed

Procedure

  • Add the metrics.CreateServiceMonitor() helper function to your Operator code:

    import(
        "k8s.io/api/core/v1"
        "github.com/operator-framework/operator-sdk/pkg/metrics"
        "machine.openshift.io/controller-runtime/pkg/client/config"
    )
    func main() {
    
        ...
        // Populate below with the Service(s) for which you want to create ServiceMonitors.
        services := []*v1.Service{}
        // Create one ServiceMonitor per application per namespace.
        // Change the below value to name of the Namespace you want the ServiceMonitor to be created in.
        ns := "default"
        // restConfig is used for talking to the Kubernetes apiserver
        restConfig := config.GetConfig()
    
        // Pass the Service(s) to the helper function, which in turn returns the array of ServiceMonitor objects.
        serviceMonitors, err := metrics.CreateServiceMonitors(restConfig, ns, services)
        if err != nil {
            // Handle errors here.
        }
        ...
    }

9.6. Configuring leader election

During the lifecycle of an Operator, it is possible that there may be more than one instance running at any given time, for example when rolling out an upgrade for the Operator. In such a scenario, it is necessary to avoid contention between multiple Operator instances using leader election. This ensures only one leader instance handles the reconciliation while the other instances are inactive but ready to take over when the leader steps down.

There are two different leader election implementations to choose from, each with its own trade-off:

  • Leader-for-life: The leader Pod only gives up leadership (using garbage collection) when it is deleted. This implementation precludes the possibility of two instances mistakenly running as leaders (split brain). However, this method can be subject to a delay in electing a new leader. For example, when the leader Pod is on an unresponsive or partitioned node, the pod-eviction-timeout dictates how it takes for the leader Pod to be deleted from the node and step down (default 5m). See the Leader-for-life Go documentation for more.
  • Leader-with-lease: The leader Pod periodically renews the leader lease and gives up leadership when it cannot renew the lease. This implementation allows for a faster transition to a new leader when the existing leader is isolated, but there is a possibility of split brain in certain situations. See the Leader-with-lease Go documentation for more.

By default, the Operator SDK enables the Leader-for-life implementation. Consult the related Go documentation for both approaches to consider the trade-offs that make sense for your use case,

The following examples illustrate how to use the two options.

9.6.1. Using Leader-for-life election

With the Leader-for-life election implementation, a call to leader.Become() blocks the Operator as it retries until it can become the leader by creating the ConfigMap named memcached-operator-lock:

import (
  ...
  "github.com/operator-framework/operator-sdk/pkg/leader"
)

func main() {
  ...
  err = leader.Become(context.TODO(), "memcached-operator-lock")
  if err != nil {
    log.Error(err, "Failed to retry for leader lock")
    os.Exit(1)
  }
  ...
}

If the Operator is not running inside a cluster, leader.Become() simply returns without error to skip the leader election since it cannot detect the Operator’s namespace.

9.6.2. Using Leader-with-lease election

The Leader-with-lease implementation can be enabled using the Manager Options for leader election:

import (
  ...
  "sigs.k8s.io/controller-runtime/pkg/manager"
)

func main() {
  ...
  opts := manager.Options{
    ...
    LeaderElection: true,
    LeaderElectionID: "memcached-operator-lock"
  }
  mgr, err := manager.New(cfg, opts)
  ...
}

When the Operator is not running in a cluster, the Manager returns an error when starting since it cannot detect the Operator’s namespace in order to create the ConfigMap for leader election. You can override this namespace by setting the Manager’s LeaderElectionNamespace option.

9.7. Operator SDK CLI reference

This guide documents the Operator SDK CLI commands and their syntax:

$ operator-sdk <command> [<subcommand>] [<argument>] [<flags>]

9.7.1. build

The operator-sdk build command compiles the code and builds the executables. After build completes, the image is built locally in docker. It must then be pushed to a remote registry.

Table 9.7. build arguments

ArgumentDescription

<image>

The container image to be built, e.g., quay.io/example/operator:v0.0.1.

Table 9.8. build flags

FlagDescription

--enable-tests (bool)

Enable in-cluster testing by adding test binary to the image.

--namespaced-manifest (string)

Path of namespaced resources manifest for tests. Default: deploy/operator.yaml.

--test-location (string)

Location of tests. Default: ./test/e2e

-h, --help

Usage help output.

If --enable-tests is set, the build command also builds the testing binary, adds it to the container image, and generates a deploy/test-pod.yaml file that allows a user to run the tests as a Pod on a cluster.

Example output

$ operator-sdk build quay.io/example/operator:v0.0.1

building example-operator...

building container quay.io/example/operator:v0.0.1...
Sending build context to Docker daemon  163.9MB
Step 1/4 : FROM alpine:3.6
 ---> 77144d8c6bdc
Step 2/4 : ADD tmp/_output/bin/example-operator /usr/local/bin/example-operator
 ---> 2ada0d6ca93c
Step 3/4 : RUN adduser -D example-operator
 ---> Running in 34b4bb507c14
Removing intermediate container 34b4bb507c14
 ---> c671ec1cff03
Step 4/4 : USER example-operator
 ---> Running in bd336926317c
Removing intermediate container bd336926317c
 ---> d6b58a0fcb8c
Successfully built d6b58a0fcb8c
Successfully tagged quay.io/example/operator:v0.0.1

9.7.2. completion

The operator-sdk completion command generates shell completions to make issuing CLI commands quicker and easier.

Table 9.9. completion subcommands

SubcommandDescription

bash

Generate bash completions.

zsh

Generate zsh completions.

Table 9.10. completion flags

FlagDescription

-h, --help

Usage help output.

Example output

$ operator-sdk completion bash

# bash completion for operator-sdk                         -*- shell-script -*-
...
# ex: ts=4 sw=4 et filetype=sh

9.7.3. print-deps

The operator-sdk print-deps command prints the most recent Golang packages and versions required by Operators. It prints in columnar format by default.

Table 9.11. print-deps flags

FlagDescription

--as-file

Print packages and versions in Gopkg.toml format.

Example output

$ operator-sdk print-deps --as-file
required = [
  "k8s.io/code-generator/cmd/defaulter-gen",
  "k8s.io/code-generator/cmd/deepcopy-gen",
  "k8s.io/code-generator/cmd/conversion-gen",
  "k8s.io/code-generator/cmd/client-gen",
  "k8s.io/code-generator/cmd/lister-gen",
  "k8s.io/code-generator/cmd/informer-gen",
  "k8s.io/code-generator/cmd/openapi-gen",
  "k8s.io/gengo/args",
]

[[override]]
  name = "k8s.io/code-generator"
  revision = "6702109cc68eb6fe6350b83e14407c8d7309fd1a"
...

9.7.4. generate

The operator-sdk generate command invokes a specific generator to generate code as needed.

Table 9.12. generate subcommands

SubcommandDescription

k8s

Runs the Kubernetes code-generators for all CRD APIs under pkg/apis/. Currently, k8s only runs deepcopy-gen to generate the required DeepCopy() functions for all Custom Resource (CR) types.

Note

This command must be run every time the API (spec and status) for a custom resource type is updated.

Example output

$ tree pkg/apis/app/v1alpha1/
pkg/apis/app/v1alpha1/
├── appservice_types.go
├── doc.go
├── register.go

$ operator-sdk generate k8s
Running code-generation for Custom Resource (CR) group versions: [app:v1alpha1]
Generating deepcopy funcs

$ tree pkg/apis/app/v1alpha1/
pkg/apis/app/v1alpha1/
├── appservice_types.go
├── doc.go
├── register.go
└── zz_generated.deepcopy.go

9.7.5. olm-catalog

The operator-sdk olm-catalog is the parent command for all Operator Lifecycle Manager (OLM) Catalog-related commands.

9.7.5.1. gen-csv

The gen-csv subcommand writes a Cluster Service Version (CSV) manifest and optionally Custom Resource Definition (CRD) files to deploy/olm-catalog/<operator_name>/<csv_version>.

Table 9.13. olm-catalog gen-csv flags

FlagDescription

--csv-version (string)

Semantic version of the CSV manifest. Required.

--from-version (string)

Semantic version of CSV manifest to use as a base for a new version.

--csv-config (string)

Path to CSV configuration file. Default: deploy/olm-catalog/csv-config.yaml.

--update-crds

Updates CRD manifests in deploy/<operator_name>/<csv_version> using the latest CRD manifests.

Example output

$ operator-sdk olm-catalog gen-csv --csv-version 0.1.0 --update-crds
INFO[0000] Generating CSV manifest version 0.1.0
INFO[0000] Fill in the following required fields in file deploy/olm-catalog/operator-name/0.1.0/operator-name.v0.1.0.clusterserviceversion.yaml:
	spec.keywords
	spec.maintainers
	spec.provider
	spec.labels
INFO[0000] Created deploy/olm-catalog/operator-name/0.1.0/operator-name.v0.1.0.clusterserviceversion.yaml

9.7.6. new

The operator-sdk new command creates a new Operator application and generates (or scaffolds) a default project directory layout based on the input <project_name>.

Table 9.14. new arguments

ArgumentDescription

<project_name>

Name of the new project.

Table 9.15. new flags

FlagDescription

--api-version

CRD APIVersion in the format $GROUP_NAME/$VERSION, for example app.example.com/v1alpha1. Used with ansible or helm types.

--dep-manager [dep|modules]

Dependency manager the new project will use. Used with go type. (Default: modules)

--generate-playbook

Generate an Ansible playbook skeleton. Used with ansible type.

--header-file <string>

Path to file containing headers for generated Go files. Copied to hack/boilerplate.go.txt.

--helm-chart <string>

Initialize Helm operator with existing Helm chart: <url>, <repo>/<name>, or local path.

--helm-chart-repo <string>

Chart repository URL for the requested Helm chart.

--helm-chart-version <string>

Specific version of the Helm chart. (Default: latest version)

--help, -h

Usage and help output.

--kind <string>

CRD Kind, for example AppService. Used with ansible or helm types.

--skip-git-init

Do not initialize the directory as a Git repository.

--type

Type of Operator to initialize: go, ansible or helm. (Default: go)

Example usage for Go project

$ mkdir $GOPATH/src/github.com/example.com/
$ cd $GOPATH/src/github.com/example.com/
$ operator-sdk new app-operator

Example usage for Ansible project

$ operator-sdk new app-operator \
    --type=ansible \
    --api-version=app.example.com/v1alpha1 \
    --kind=AppService

9.7.7. add

The operator-sdk add command adds a controller or resource to the project. The command must be run from the Operator project root directory.

Table 9.16. add subcommands

SubcommandDescription

api

Adds a new API definition for a new Custom Resource (CR) under pkg/apis and generates the Customer Resource Definition (CRD) and Custom Resource (CR) files under deploy/crds/. If the API already exists at pkg/apis/<group>/<version>, then the command does not overwrite and returns an error.

controller

Adds a new controller under pkg/controller/<kind>/. The controller expects to use the CR type that should already be defined under pkg/apis/<group>/<version> via the operator-sdk add api --kind=<kind> --api-version=<group/version> command. If the controller package for that Kind already exists at pkg/controller/<kind>, then the command does not overwrite and returns an error.

crd

Adds a CRD and the CR files. The <project-name>/deploy path must already exist. The --api-version and --kind flags are required to generate the new Operator application.

  • Generated CRD filename: <project-name>/deploy/crds/<group>_<version>_<kind>_crd.yaml
  • Generated CR filename: <project-name>/deploy/crds/<group>_<version>_<kind>_cr.yaml

Table 9.17. add api flags

FlagDescription

--api-version (string)

CRD APIVersion in the format $GROUP_NAME/$VERSION (e.g., app.example.com/v1alpha1).

--kind (string)

CRD Kind (e.g., AppService).

Example add api output

$ operator-sdk add api --api-version app.example.com/v1alpha1 --kind AppService
Create pkg/apis/app/v1alpha1/appservice_types.go
Create pkg/apis/addtoscheme_app_v1alpha1.go
Create pkg/apis/app/v1alpha1/register.go
Create pkg/apis/app/v1alpha1/doc.go
Create deploy/crds/app_v1alpha1_appservice_cr.yaml
Create deploy/crds/app_v1alpha1_appservice_crd.yaml
Running code-generation for Custom Resource (CR) group versions: [app:v1alpha1]
Generating deepcopy funcs

$ tree pkg/apis
pkg/apis/
├── addtoscheme_app_appservice.go
├── apis.go
└── app
	└── v1alpha1
		├── doc.go
		├── register.go
		├── types.go

Example add controller output

$ operator-sdk add controller --api-version app.example.com/v1alpha1 --kind AppService
Create pkg/controller/appservice/appservice_controller.go
Create pkg/controller/add_appservice.go

$ tree pkg/controller
pkg/controller/
├── add_appservice.go
├── appservice
│   └── appservice_controller.go
└── controller.go

Example add crd output

$ operator-sdk add crd --api-version app.example.com/v1alpha1 --kind AppService
Generating Custom Resource Definition (CRD) files
Create deploy/crds/app_v1alpha1_appservice_crd.yaml
Create deploy/crds/app_v1alpha1_appservice_cr.yaml

9.7.8. test

The operator-sdk test command can test the Operator locally.

9.7.8.1. local

The local subcommand runs Go tests built using the Operator SDK’s test framework locally.

Table 9.18. test local arguments

ArgumentsDescription

<test_location> (string)

Location of e2e test files (e.g., ./test/e2e/).

Table 9.19. test local flags

FlagsDescription

--kubeconfig (string)

Location of kubeconfig for a cluster. Default: ~/.kube/config.

--global-manifest (string)

Path to manifest for global resources. Default: deploy/crd.yaml.

--namespaced-manifest (string)

Path to manifest for per-test, namespaced resources. Default: combines deploy/service_account.yaml, deploy/rbac.yaml, and deploy/operator.yaml.

--namespace (string)

If non-empty, a single namespace to run tests in (e.g., operator-test). Default: ""

--go-test-flags (string)

Extra arguments to pass to go test (e.g., -f "-v -parallel=2").

--up-local

Enable running the Operator locally with go run instead of as an image in the cluster.

--no-setup

Disable test resource creation.

--image (string)

Use a different Operator image from the one specified in the namespaced manifest.

-h, --help

Usage help output.

Example output

$ operator-sdk test local ./test/e2e/

# Output:
ok  	github.com/operator-framework/operator-sdk-samples/memcached-operator/test/e2e	20.410s

9.7.9. up

The operator-sdk up command has subcommands that can launch the Operator in various ways.

9.7.9.1. local

The local subcommand launches the Operator on the local machine by building the Operator binary with the ability to access a Kubernetes cluster using a kubeconfig file.

Table 9.20. up local arguments

ArgumentsDescription

--kubeconfig (string)

The file path to a Kubernetes configuration file. Defaults: $HOME/.kube/config

--namespace (string)

The namespace where the Operator watches for changes. Default: default

--operator-flags

Flags that the local Operator may need. Example: --flag1 value1 --flag2=value2

-h, --help

Usage help output.

Example output

$ operator-sdk up local \
  --kubeconfig "mycluster.kubecfg" \
  --namespace "default" \
  --operator-flags "--flag1 value1 --flag2=value2"

The following example uses the default kubeconfig, the default namespace environment variable, and passes in flags for the Operator. To use the Operator flags, your Operator must know how to handle the option. For example, for an Operator that understands the resync-interval flag:

$ operator-sdk up local --operator-flags "--resync-interval 10"

If you are planning on using a different namespace than the default, use the --namespace flag to change where the Operator is watching for Custom Resources (CRs) to be created:

$ operator-sdk up local --namespace "testing"

For this to work, your Operator must handle the WATCH_NAMESPACE environment variable. This can be accomplished using the utility functionk8sutil.GetWatchNamespace in your Operator.

9.8. Appendices

9.8.1. Operator project scaffolding layout

The operator-sdk CLI generates a number of packages for each Operator project. The following sections describes a basic rundown of each generated file and directory.

9.8.1.1. Go-based projects

Go-based Operator projects (the default type) generated using the operator-sdk new command contain the following directories and files:

File/foldersPurpose

cmd/

Contains manager/main.go file, which is the main program of the Operator. This instantiates a new manager which registers all Custom Resource Definitions under pkg/apis/ and starts all controllers under pkg/controllers/.

pkg/apis/

Contains the directory tree that defines the APIs of the Custom Resource Definitions (CRDs). Users are expected to edit the pkg/apis/<group>/<version>/<kind>_types.go files to define the API for each resource type and import these packages in their controllers to watch for these resource types.

pkg/controller

This pkg contains the controller implementations. Users are expected to edit the pkg/controller/<kind>/<kind>_controller.go files to define the controller’s reconcile logic for handling a resource type of the specified kind.

build/

Contains the Dockerfile and build scripts used to build the Operator.

deploy/

Contains various YAML manifests for registering CRDs, setting up RBAC, and deploying the Operator as a Deployment.

Gopkg.toml
Gopkg.lock

The Go Dep manifests that describe the external dependencies of this Operator.

vendor/

The golang vendor folder that contains the local copies of the external dependencies that satisfy the imports of this project. Go Dep manages the vendor directly.

9.8.1.2. Helm-based projects

Helm-based Operator projects generated using the operator-sdk new --type helm command contain the following directories and files:

File/foldersPurpose

deploy/

Contains various YAML manifests for registering CRDs, setting up RBAC, and deploying the Operator as a Deployment.

helm-charts/<kind>

Contains a Helm chart initialized using the equivalent of the helm create command.

build/

Contains the Dockerfile and build scripts used to build the Operator.

watches.yaml

Contains Group, Version, Kind, and Helm chart location.

Chapter 10. Application life cycle management

10.1. Creating applications

You can create an OpenShift Container Platform application from components that include source or binary code, images, and templates by using the OpenShift Container Platform CLI.

The set of objects created by new-app depends on the artifacts passed as input: source repositories, images, or templates.

10.1.1. Creating an application by using the CLI

10.1.1.1. Creating an application from source code

With the new-app command you can create applications from source code in a local or remote Git repository.

The new-app command creates a build configuration, which itself creates a new application image from your source code. The new-app command typically also creates a deployment configuration to deploy the new image, and a service to provide load-balanced access to the deployment running your image.

OpenShift Container Platform automatically detects whether the Pipeline or Source build strategy should be used, and in the case of Source builds, detects an appropriate language builder image.

10.1.1.1.1. Local

To create an application from a Git repository in a local directory:

$ oc new-app /<path to source code>
Note

If you use a local Git repository, the repository must have a remote named origin that points to a URL that is accessible by the OpenShift Container Platform cluster. If there is no recognized remote, running the new-app command will create a binary build.

10.1.1.1.2. Remote

To create an application from a remote Git repository:

$ oc new-app https://github.com/sclorg/cakephp-ex

To create an application from a private remote Git repository:

$ oc new-app https://github.com/youruser/yourprivaterepo --source-secret=yoursecret
Note

If you use a private remote Git repository, you can use the --source-secret flag to specify an existing source clone secret that will get injected into your BuildConfig to access the repository.

You can use a subdirectory of your source code repository by specifying a --context-dir flag. To create an application from a remote Git repository and a context subdirectory:

$ oc new-app https://github.com/sclorg/s2i-ruby-container.git \
    --context-dir=2.0/test/puma-test-app

Also, when specifying a remote URL, you can specify a Git branch to use by appending #<branch_name> to the end of the URL:

$ oc new-app https://github.com/openshift/ruby-hello-world.git#beta4
10.1.1.1.3. Build strategy detection

If a Jenkinsfile exists in the root or specified context directory of the source repository when creating a new application, OpenShift Container Platform generates a Pipeline build strategy.

Otherwise, it generates a Source build strategy.

Override the build strategy by setting the --strategy flag to either pipeline or source.

$ oc new-app /home/user/code/myapp --strategy=docker
Note

The oc command requires that files containing build sources are available in a remote Git repository. For all source builds, you must use git remote -v.

10.1.1.1.4. Language Detection

If you use the Source build strategy, new-app attempts to determine the language builder to use by the presence of certain files in the root or specified context directory of the repository:

Table 10.1. Languages Detected by new-app

LanguageFiles

dotnet

project.json, *.csproj

jee

pom.xml

nodejs

app.json, package.json

perl

cpanfile, index.pl

php

composer.json, index.php

python

requirements.txt, setup.py

ruby

Gemfile, Rakefile, config.ru

scala

build.sbt

golang

Godeps, main.go

After a language is detected, new-app searches the OpenShift Container Platform server for imagestreamtags that have a supports annotation matching the detected language, or an imagestream that matches the name of the detected language. If a match is not found, new-app searches the Docker Hub registry for an image that matches the detected language based on name.

You can override the image the builder uses for a particular source repository by specifying the image, either an imagestream or container specification, and the repository with a ~ as a separator. Note that if this is done, build strategy detection and language detection are not carried out.

For example, to use the myproject/my-ruby imagestream with the source in a remote repository:

$ oc new-app myproject/my-ruby~https://github.com/openshift/ruby-hello-world.git

To use the `openshift/ruby-20-centos7:latest `container imagestream with the source in a local repository:

$ oc new-app openshift/ruby-20-centos7:latest~/home/user/code/my-ruby-app
Note

Language detection requires the Git client to be locally installed so that your repository can be cloned and inspected. If Git is not available, you can avoid the language detection step by specifying the builder image to use with your repository with the <image>~<repository> syntax.

The -i <image> <repository> invocation requires that new-app attempt to clone repository in order to determine what type of artifact it is, so this will fail if Git is not available.

The -i <image> --code <repository> invocation requires new-app clone repository in order to determine whether image should be used as a builder for the source code, or deployed separately, as in the case of a database image.

10.1.1.2. Creating an application from an image

You can deploy an application from an existing image. Images can come from imagestreams in the OpenShift Container Platform server, images in a specific registry, or images in the local Docker server.

The new-app command attempts to determine the type of image specified in the arguments passed to it. However, you can explicitly tell new-app whether the image is a container image using the --docker-image argument or an imagestream using the -i|--image argument.

Note

If you specify an image from your local Docker repository, you must ensure that the same image is available to the OpenShift Container Platform cluster nodes.

10.1.1.2.1. DockerHub MySQL image

Create an application from the DockerHub MySQL image, for example:

$ oc new-app mysql
10.1.1.2.2. Image in a private registry

Create an application using an image in a private registry, specify the full container image specification:

$ oc new-app myregistry:5000/example/myimage
10.1.1.2.3. Existing imagestream and optional imagestreamtag

Create an application from an existing imagestream and optional imagestreamtag:

$ oc new-app my-stream:v1

10.1.1.3. Creating an application from a template

You can create an application from a previously stored template or from a template file, by specifying the name of the template as an argument. For example, you can store a sample application template and use it to create an application.

Create an application from a stored template, for example:

$ oc create -f examples/sample-app/application-template-stibuild.json
$ oc new-app ruby-helloworld-sample

To directly use a template in your local file system, without first storing it in OpenShift Container Platform, use the -f|--file argument. For example:

$ oc new-app -f examples/sample-app/application-template-stibuild.json
10.1.1.3.1. Template Parameters

When creating an application based on a template, use the -p|--param argument to set parameter values that are defined by the template:

$ oc new-app ruby-helloworld-sample \
    -p ADMIN_USERNAME=admin -p ADMIN_PASSWORD=mypassword

You can store your parameters in a file, then use that file with --param-file when instantiating a template. If you want to read the parameters from standard input, use --param-file=-:

$ cat helloworld.params
ADMIN_USERNAME=admin
ADMIN_PASSWORD=mypassword
$ oc new-app ruby-helloworld-sample --param-file=helloworld.params
$ cat helloworld.params | oc new-app ruby-helloworld-sample --param-file=-

10.1.1.4. Modifying application creation

The new-app command generates OpenShift Container Platform objects that build, deploy, and run the application that is created. Normally, these objects are created in the current project and assigned names that are derived from the input source repositories or the input images. However, with new-app you can modify this behavior.

Table 10.2. new-app output objects

ObjectDescription

BuildConfig

A BuildConfig is created for each source repository that is specified in the command line. The BuildConfig specifies the strategy to use, the source location, and the build output location.

ImageStreams

For BuildConfig, two ImageStreams are usually created. One represents the input image. With Source builds, this is the builder image. With Docker builds, this is the FROM image. The second one represents the output image. If a container image was specified as input to new-app, then an imagestream is created for that image as well.

DeploymentConfig

A DeploymentConfig is created either to deploy the output of a build, or a specified image. The new-app command creates emptyDir volumes for all Docker volumes that are specified in containers included in the resulting DeploymentConfig.

Service

The new-app command attempts to detect exposed ports in input images. It uses the lowest numeric exposed port to generate a service that exposes that port. In order to expose a different port, after new-app has completed, simply use the oc expose command to generate additional services.

Other

Other objects can be generated when instantiating templates, according to the template.

10.1.1.4.1. Specifying environment variables

When generating applications from a template, source, or an image, you can use the -e|--env argument to pass environment variables to the application container at run time:

$ oc new-app openshift/postgresql-92-centos7 \
    -e POSTGRESQL_USER=user \
    -e POSTGRESQL_DATABASE=db \
    -e POSTGRESQL_PASSWORD=password

The variables can also be read from file using the --env-file argument:

$ cat postgresql.env
POSTGRESQL_USER=user
POSTGRESQL_DATABASE=db
POSTGRESQL_PASSWORD=password
$ oc new-app openshift/postgresql-92-centos7 --env-file=postgresql.env

Additionally, environment variables can be given on standard input by using --env-file=-:

$ cat postgresql.env | oc new-app openshift/postgresql-92-centos7 --env-file=-
Note

Any BuildConfig objects created as part of new-app processing are not updated with environment variables passed with the -e|--env or --env-file argument.

10.1.1.4.2. Specifying build environment variables

When generating applications from a template, source, or an image, you can use the --build-env argument to pass environment variables to the build container at run time:

$ oc new-app openshift/ruby-23-centos7 \
    --build-env HTTP_PROXY=http://myproxy.net:1337/ \
    --build-env GEM_HOME=~/.gem

The variables can also be read from a file using the --build-env-file argument:

$ cat ruby.env
HTTP_PROXY=http://myproxy.net:1337/
GEM_HOME=~/.gem
$ oc new-app openshift/ruby-23-centos7 --build-env-file=ruby.env

Additionally, environment variables can be given on standard input by using --build-env-file=-:

$ cat ruby.env | oc new-app openshift/ruby-23-centos7 --build-env-file=-
10.1.1.4.3. Specifying labels

When generating applications from source, images, or templates, you can use the -l|--label argument to add labels to the created objects. Labels make it easy to collectively select, configure, and delete objects associated with the application.

$ oc new-app https://github.com/openshift/ruby-hello-world -l name=hello-world
10.1.1.4.4. Viewing the output without creation

To see a dry-run of running the new-app command, you can use the -o|--output argument with a yaml or json value. You can then use the output to preview the objects that are created or redirect it to a file that you can edit. After you are satisfied, you can use oc create to create the OpenShift Container Platform objects.

To output new-app artifacts to a file, edit them, then create them:

$ oc new-app https://github.com/openshift/ruby-hello-world \
    -o yaml > myapp.yaml
$ vi myapp.yaml
$ oc create -f myapp.yaml
10.1.1.4.5. Creating objects with different names

Objects created by new-app are normally named after the source repository, or the image used to generate them. You can set the name of the objects produced by adding a --name flag to the command:

$ oc new-app https://github.com/openshift/ruby-hello-world --name=myapp
10.1.1.4.6. Creating objects in a different project

Normally, new-app creates objects in the current project. However, you can create objects in a different project by using the -n|--namespace argument:

$ oc new-app https://github.com/openshift/ruby-hello-world -n myproject
10.1.1.4.7. Creating multiple objects

The new-app command allows creating multiple applications specifying multiple parameters to new-app. Labels specified in the command line apply to all objects created by the single command. Environment variables apply to all components created from source or images.

To create an application from a source repository and a Docker Hub image:

$ oc new-app https://github.com/openshift/ruby-hello-world mysql
Note

If a source code repository and a builder image are specified as separate arguments, new-app uses the builder image as the builder for the source code repository. If this is not the intent, specify the required builder image for the source using the ~ separator.

10.1.1.4.8. Grouping images and source in a single Pod

The new-app command allows deploying multiple images together in a single Pod. In order to specify which images to group together, use the + separator. The --group command line argument can also be used to specify the images that should be grouped together. To group the image built from a source repository with other images, specify its builder image in the group:

$ oc new-app ruby+mysql

To deploy an image built from source and an external image together:

$ oc new-app \
    ruby~https://github.com/openshift/ruby-hello-world \
    mysql \
    --group=ruby+mysql
10.1.1.4.9. Searching for images, templates, and other inputs

To search for images, templates, and other inputs for the oc new-app command, add the --search and --list flags. For example, to find all of the images or templates that include PHP:

$ oc new-app --search php

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