Applications

OpenShift Container Platform 4.6

Creating and managing applications on OpenShift Container Platform

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. This includes working with projects and 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.

Note

Projects starting with openshift- and kube- are default projects. These projects host cluster components that run as Pods and other infrastructure components. As such, OpenShift Container Platform does not allow you to create Projects starting with openshift- or kube- using the oc new-project command. Cluster administrators can create these Projects using the oc adm new-project command.

1.1.1. Creating a project using the web console

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

Note

Projects starting with openshift- and kube- are considered critical by OpenShift Container Platform. As such, OpenShift Container Platform does not allow you to create Projects starting with openshift- using the web console.

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 Developer perspective in the web console

You can use the Developer perspective in the OpenShift Container Platform web console to create a project in your cluster.

Note

Projects starting with openshift- and kube- are considered critical by OpenShift Container Platform. As such, OpenShift Container Platform does not allow you to create projects starting with openshift- or kube- using the Developer perspective. Cluster administrators can create these projects using the oc adm new-project command.

Prerequisites

  • Ensure that you have the appropriate roles and permissions to create projects, applications, and other workloads in OpenShift Container Platform.

Procedure

You can create a project using the Developer perspective, as follows:

  1. Click the Project drop-down menu to see a list of all available projects. Select Create Project.

    Figure 1.1. Create project

    odc create project
  2. In the Create Project dialog box, enter a unique name, such as myproject, in the Name field.
  3. Optional: Add the Display Name and Description details for the project.
  4. Click Create.
  5. Use the left navigation panel to navigate to the Project view and see the dashboard for your project.
  6. Optional:

    • Use the Project drop-down menu at the top of the screen and select all projects to list all of the projects in your cluster.
    • Use the Details tab to see the project details.
    • If you have adequate permissions for a project, you can use the Project Access tab to provide or revoke administrator, edit, and view privileges for the project.

1.1.3. Creating a project using the CLI

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

Note

Projects starting with openshift- and kube- are considered critical by OpenShift Container Platform. As such, OpenShift Container Platform does not allow you to create Projects starting with openshift- or kube- using the oc new-project command. Cluster administrators can create these Projects using the oc adm new-project command.

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.

1.1.4. Viewing a project using the web console

Procedure

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

    On this page, click the Workloads button to see workloads in the project.

1.1.5. 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>

1.1.6. Providing access permissions to your project using the Developer perspective

You can use the Project view in the Developer perspective to grant or revoke access permissions to your project.

Procedure

To add users to your project and provide Admin, Edit, or View access to them:

  1. In the Developer perspective, navigate to the Project view.
  2. In the Project page, select the Project Access tab.
  3. Click Add Access to add a new row of permissions to the default ones.

    Figure 1.2. Project permissions

    odc project permissions
  4. Enter the user name, click the Select a role drop-down list, and select an appropriate role.
  5. Click Save to add the new permissions.

You can also use:

  • The Select a role drop-down list, to modify the access permissions of an existing user.
  • The Remove Access icon, to completely remove the access permissions of an existing user to the project.
Note

Advanced role-based access control is managed in the Roles and Roles Binding views in the Administrator perspective.

1.1.7. Adding to a project

Procedure

  1. Select Developer from the context selector at the top of the web console navigation menu.
  2. Click +Add
  3. At the top of the page, select the name of the project that you want to add to.
  4. Click on a method for adding to your project, and then follow the workflow.

1.1.8. Checking project status using the web console

Procedure

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

1.1.9. 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.

1.1.10. Deleting a project using the web console

You can delete a project by using the OpenShift Container Platform web console.

Note

If you do not have permissions to delete the project, the Delete Project option is not available.

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 Options menu kebab .
  4. When the Delete Project pane opens, enter the name of the project that you want to delete in the field.
  5. Click Delete.

1.1.11. 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

You can configure a request to the OpenShift Container Platform API to act as though it originated from another user. For more information, see User impersonation in the Kubernetes documentation.

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

    Example output

    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

    Example output

    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. Application life cycle management

2.1. Creating applications using the Developer perspective

The Developer perspective in the web console provides you the following options from the Add view to create applications and associated services and deploy them on OpenShift Container Platform:

Figure 2.1. Add view

odc add view
  • From Git: Use this option to import an existing codebase in a Git repository to create, build, and deploy an application on OpenShift Container Platform.
  • Container Image: Use existing images from an image stream or registry to deploy it on to OpenShift Container Platform.
  • From Dockerfile: Import a dockerfile from your Git repository to build and deploy an application.
  • YAML: Use the editor to add YAML or JSON definitions to create and modify resources.
  • From Catalog: Explore the Developer Catalog to select the required applications, services, or source to image builders and add it to your project.
  • Database: See the Developer Catalog to select the required database service and add it to your application.
  • Operator Backed: Explore the Developer Catalog to select and deploy the required Operator-managed service.
  • Helm Chart: Explore the Developer Catalog to select the required Helm chart to simplify deployment of applications and services.

Note that certain options, such as Pipelines, Event Source, and Import Virtual Machines, are displayed only when the OpenShift Pipelines, OpenShift Serverless, and OpenShift Virtualization Operators are installed, respectively.

2.1.1. Prerequisites

To create applications using the Developer perspective ensure that:

To create serverless applications, in addition to the preceding prerequisites, ensure that:

2.1.2. Importing a codebase from Git to create an application

You can use the Developer perspective to create, build, and deploy an application on OpenShift Container Platform using an existing codebase in GitHub.

The following procedure walks you through the From Git option in the Developer perspective to create an application.

Procedure

  1. In the Add view, click From Git to see the Import from git form.
  2. In the Git section, enter the Git repository URL for the codebase you want to use to create an application. For example, enter the URL of this sample Node.js application https://github.com/sclorg/nodejs-ex. The URL is then validated.
  3. Optional: You can click Show Advanced Git Options to add details such as:

    • Git Reference to point to code in a specific branch, tag, or commit to be used to build the application.
    • Context Dir to specify the subdirectory for the application source code you want to use to build the application.
    • Source Secret to create a Secret Name with credentials for pulling your source code from a private repository.
  4. In the Builder section, after the URL is validated, an appropriate builder image is detected, indicated by a star, and automatically selected. For the https://github.com/sclorg/nodejs-ex Git URL, the Node.js builder image is selected by default. If a builder image is not auto-detected, select a builder image. If required, you can change the version using the Builder Image Version drop-down list.
  5. In the General section:

    1. In the Application field, enter a unique name for the application grouping, for example, myapp. Ensure that the application name is unique in a namespace.
    2. The Name field to identify the resources created for this application is automatically populated based on the Git repository URL if there are no existing applications. If there are existing applications, you can choose to deploy the component within an existing application, create a new application, or keep the component unassigned.

      Note

      The resource name must be unique in a namespace. Modify the resource name if you get an error.

  6. In the Resources section, select:

    • Deployment, to create an application in plain Kubernetes style.
    • Deployment Config, to create an OpenShift style application.
    • Knative Service, to create a microservice.
    Note

    The Knative Service option is displayed in the Import from git form only if the Serverless Operator is installed in your cluster. For further details refer to documentation on installing OpenShift Serverless.

  7. In the Pipelines section, select Add Pipeline, and then click Show Pipeline Visualization to see the pipeline for the application.
  8. In the Advanced Options section, the Create a route to the application is selected by default so that you can access your application using a publicly available URL. You can clear the check box if you do not want to expose your application on a public route.
  9. Optional: You can use the following advanced options to further customize your application:

    Routing

    Click the Routing link to:

    • Customize the hostname for the route.
    • Specify the path the router watches.
    • Select the target port for the traffic from the drop-down list.
    • Secure your route by selecting the Secure Route check box. Select the required TLS termination type and set a policy for insecure traffic from the respective drop-down lists.

      For serverless applications, the Knative Service manages all the routing options above. However, you can customize the target port for traffic, if required. If the target port is not specified, the default port of 8080 is used.

    Health Checks

    Click the Health Checks link to add Readiness, Liveness, and Startup probes to your application. All the probes have prepopulated default data; you can add the probes with the default data or customize it as required.

    To customize the health probes:

    • Click Add Readiness Probe, if required, modify the parameters to check if the container is ready to handle requests, and select the check mark to add the probe.
    • Click Add Liveness Probe, if required, modify the parameters to check if a container is still running, and select the check mark to add the probe.
    • Click Add Startup Probe, if required, modify the parameters to check if the application within the container has started, and select the check mark to add the probe.

      For each of the probes, you can specify the request type - HTTP GET, Container Command, or TCP Socket, from the drop-down list. The form changes as per the selected request type. You can then modify the default values for the other parameters, such as the success and failure thresholds for the probe, number of seconds before performing the first probe after the container starts, frequency of the probe, and the timeout value.

    Build Configuration and Deployment

    Click the Build Configuration and Deployment links to see the respective configuration options. Some options are selected by default; you can customize them further by adding the necessary triggers and environment variables.

    For serverless applications, the Deployment option is not displayed as the Knative configuration resource maintains the desired state for your deployment instead of a DeploymentConfig.

    Scaling

    Click the Scaling link to define the number of pods or instances of the application you want to deploy initially.

    For serverless applications, you can:

    • Set the upper and lower limit for the number of pods that can be set by the autoscaler. If the lower limit is not specified, it defaults to zero.
    • Define the soft limit for the required number of concurrent requests per instance of the application at a given time. It is the recommended configuration for autoscaling. If not specified, it takes the value specified in the cluster configuration.
    • Define the hard limit for the number of concurrent requests allowed per instance of the application at a given time. This is configured in the revision template. If not specified, it defaults to the value specified in the cluster configuration.
    Resource Limit
    Click the Resource Limit link to set the amount of CPU and Memory resources a container is guaranteed or allowed to use when running.
    Labels
    Click the Labels link to add custom labels to your application.
  10. Click Create to create the application and see its build status in the Topology view.

2.2. Creating applications from installed Operators

Operators are a method of packaging, deploying, and managing a Kubernetes application. You can create applications on OpenShift Container Platform using Operators that have been installed by a cluster administrator.

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

Additional resources

  • See the Operators guide for more on how Operators work and how the Operator Lifecycle Manager is integrated in OpenShift Container Platform.

2.2.1. Creating an etcd cluster using an Operator

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

Prerequisites

  • Access to an OpenShift Container Platform 4.6 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 Operators → 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.

    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.

    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.

2.3. Creating applications using the CLI

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.

2.3.1. 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.

2.3.1.1. 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.

2.3.1.2. 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

2.3.1.3. 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.

2.3.1.4. 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 2.1. 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.

2.3.2. 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-stream 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.

2.3.2.1. DockerHub MySQL image

Create an application from the DockerHub MySQL image, for example:

$ oc new-app mysql

2.3.2.2. 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

2.3.2.3. Existing imagestream and optional imagestreamtag

Create an application from an existing imagestream and optional imagestreamtag:

$ oc new-app my-stream:v1

2.3.3. 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.

Upload an application template to your current project’s template library. The following example uploads an application template from a file called examples/sample-app/application-template-stibuild.json:

$ oc create -f examples/sample-app/application-template-stibuild.json

Then create a new application by referencing the application template. In this example, the template name is ruby-helloworld-sample:

$ oc new-app ruby-helloworld-sample

To create a new application by referencing a template file 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

2.3.3.1. 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=-. The following is an example file called helloworld.params:

ADMIN_USERNAME=admin
ADMIN_PASSWORD=mypassword

Reference the parameters in the file when instantiating a template:

$ oc new-app ruby-helloworld-sample --param-file=helloworld.params

2.3.4. 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 2.2. 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.

2.3.4.1. 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. The following is an example file called postgresql.env:

POSTGRESQL_USER=user
POSTGRESQL_DATABASE=db
POSTGRESQL_PASSWORD=password

Read the variables from the file:

$ 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.

2.3.4.2. 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. The following is an example file called ruby.env:

HTTP_PROXY=http://myproxy.net:1337/
GEM_HOME=~/.gem

Read the variables from the file:

$ 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=-

2.3.4.3. 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

2.3.4.4. 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, run the following:

$ oc new-app https://github.com/openshift/ruby-hello-world \
    -o yaml > myapp.yaml

Edit the file:

$ vi myapp.yaml

Create a new application by referencing the file:

$ oc create -f myapp.yaml

2.3.4.5. 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

2.3.4.6. 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

2.3.4.7. 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.

2.3.4.8. 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

2.3.4.9. 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

2.4. Viewing application composition using the Topology view

The Topology view in the Developer perspective of the web console provides a visual representation of all the applications within a project, their build status, and the components and services associated with them.

2.4.1. Prerequisites

To view your applications in the Topology view and interact with them, ensure that:

2.4.2. Viewing the topology of your application

You can navigate to the Topology view using the left navigation panel in the Developer perspective. After you create an application, you are directed automatically to the Topology view where you can see the status of the application pods, quickly access the application on a public URL, access the source code to modify it, and see the status of your last build. You can zoom in and out to see more details for a particular application.

The status or phase of the Pod is indicated by different colors and tooltips as Running ( odc pod running ), Not Ready ( odc pod not ready ), Warning( odc pod warning ), Failed( odc pod failed ), Pending( odc pod pending ), Succeeded( odc pod succeeded ), Terminating( odc pod terminating ), or Unknown( odc pod unknown ). For more information about pod status, see the Kubernetes documentation.

After you create an application and an image is deployed, the status is shown as Pending. After the application is built, it is displayed as Running.

Figure 2.2. Application topology

odc application topology

The application resource name is appended with indicators for the different types of resource objects as follows:

  • CJ: CronJob
  • D: Deployment
  • DC: DeploymentConfig
  • DS: DaemonSet
  • J: Job
  • P: Pod
  • SS: StatefulSet
  • odc serverless app (Knative): A serverless application

    Note

    Serverless applications take some time to load and display on the Topology view. When you create a serverless application, it first creates a service resource and then a revision. After that, it is deployed and displayed on the Topology view. If it is the only workload, you might be redirected to the Add page. After the revision is deployed, the serverless application is displayed on the Topology view.

2.4.3. Interacting with the application and the components

The Topology view in the Developer perspective of the web console provides the following options to interact with the application and the components:

  • Click Open URL ( odc open url ) to see your application exposed by the route on a public URL.
  • Click Edit Source code to access your source code and modify it.

    Note

    This feature is available only when you create applications using the From Git, From Catalog, and the From Dockerfile options.

  • Hover your cursor over the lower left icon on the Pod to see the name of the latest build and its status. The status of the application build is indicated as New ( odc build new ), Pending ( odc build pending ), Running ( odc build running ), Completed ( odc build completed ), Failed ( odc build failed ), and Canceled ( odc build canceled ).
  • Use the Shortcuts menu listed on the upper-right of the screen to navigate components in the Topology view.
  • Use the List View icon to see a list of all your applications and use the Topology View icon to switch back to the Topology view.
  • Use the Find by name field to select the components with component names that match the query. Search results may appear outside of the visible area; click Fit to Screen from the lower-left toolbar to resize the Topology view to show all components.
  • Use the Display Options drop-down list to configure the Topology view of the various application groupings. The options are available depending on the types of components deployed in the project:

    • Pod Count: Select to show the number of pods of a component in the component icon.
    • Event Sources: Toggle to show or hide the event sources.
    • Virtual Machines: Toggle to show or hide the virtual machines.
    • Labels: Toggle to show or hide the component labels.
    • Application Groupings: Clear to condense the application groups into cards with an overview of an application group and alerts associated with it.
    • Helm Releases: Clear to condense the components deployed as Helm Release into cards with an overview of a given release.
    • Knative Services: Clear to condense the Knative Service components into cards with an overview of a given component.
    • Operator Groupings Clear to condense the components deployed with an Operator into cards with an overview of the given group.

2.4.4. Scaling application pods and checking builds and routes

The Topology view provides the details of the deployed components in the Overview panel. You can use the Overview and Resources tabs to scale the application pods, check build status, services, and routes as follows:

  • Click on the component node to see the Overview panel to the right. Use the Overview tab to:

    • Scale your pods using the up and down arrows to increase or decrease the number of instances of the application manually. For serverless applications, the pods are automatically scaled down to zero when idle and scaled up depending on the channel traffic.
    • Check the Labels, Annotations, and Status of the application.
  • Click the Resources tab to:

    • See the list of all the pods, view their status, access logs, and click on the pod to see the pod details.
    • See the builds, their status, access logs, and start a new build if needed.
    • See the services and routes used by the component.

    For serverless applications, the Resources tab provides information on the revision, routes, and the configurations used for that component.

2.4.5. Grouping multiple components within an application

You can use the Add page to add multiple components or services to your project and use the Topology page to group applications and resources within an application group. The following procedure adds a MongoDB database service to an existing application with a Node.js component.

Prerequisites

  • Ensure that you have created and deployed a Node.js application on OpenShift Container Platform using the Developer perspective.

Procedure

  1. Create and deploy the MongoDB service to your project as follows:

    1. In the Developer perspective, navigate to the Add view and select the Database option to see the Developer Catalog, which has multiple options that you can add as components or services to your application.
    2. Click on the MongoDB option to see the details for the service.
    3. Click Instantiate Template to see an automatically populated template with details for the MongoDB service, and click Create to create the service.
  2. On the left navigation panel, click Topology to see the MongoDB service deployed in your project.
  3. To add the MongoDB service to the existing application group, select the mongodb Pod and drag it to the application; the MongoDB service is added to the existing application group.
  4. Dragging a component and adding it to an application group automatically adds the required labels to the component. Click on the MongoDB service node to see the label app.kubernetes.io/part-of=myapp added to the Labels section in the Overview Panel.

    Figure 2.3. Application grouping

    odc app grouping label

Alternatively, you can also add the component to an application as follows:

  1. To add the MongoDB service to your application, click on the mongodb Pod to see the Overview panel to the right.
  2. Click the Actions drop-down menu on the upper right of the panel and select Edit Application Grouping.
  3. In the Edit Application Grouping dialog box, click the Select an Application drop-down list, and select the appropriate application group.
  4. Click Save to see the MongoDB service added to the application group.

You can remove a component from an application group by selecting the component and using Shift+ drag to drag it out of the application group.

2.4.6. Connecting components within an application and across applications

In addition to grouping multiple components within an application, you can also use the Topology view to connect components with each other. You can either use a binding connector or a visual one to connect components.

A binding connection between the components can be established only if the target node is an Operator-backed service. This is indicated by the Create a binding connector tool-tip which appears when you drag an arrow to such a target node. When an application is connected to a service using a binding connector a ServiceBindingRequest is created. The Service Binding Operator controller then uses an intermediate Secret to inject the necessary binding data into the application Deployment as environment variables. After the request is successful, the application is redeployed establishing an interaction between the connected components.

A visual connector establishes only a visual connection between the components, depicting an intent to connect. No interaction between the components is established. If the target node is not an Operator-backed service the Create a visual connector tool-tip is displayed when you drag an arrow to a target node.

2.4.6.1. Creating a visual connection between components

You can depict an intent to connect application components using the visual connector.

This procedure walks through an example of creating a visual connection between a MongoDB service and a Node.js application.

Prerequisites

  • Ensure that you have created and deployed a Node.js application using the Developer perspective.
  • Ensure that you have created and deployed a MongoDB service using the Developer perspective.

Procedure

  1. Hover over the MongoDB service to see a dangling arrow on the node.

    Figure 2.4. Connector

    odc connector
  2. Click and drag the arrow towards the Node.js component to connect the MongoDB service with it.
  3. Click on the MongoDB service to see the Overview Panel. In the Annotations section, click the edit icon to see the Key = app.openshift.io/connects-to and Value = [{"apiVersion":"apps.openshift.io/v1","kind":"DeploymentConfig","name":"nodejs-ex"}] annotation added to the service.

Similarly you can create other applications and components and establish connections between them.

Figure 2.5. Connecting multiple applications

odc connecting multiple applications

2.4.6.2. Creating a binding connection between components

Important

Service Binding is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.

For more information about the support scope of Red Hat Technology Preview features, see https://access.redhat.com/support/offerings/techpreview/.

Note

Currently, a few specific Operators like the etcd and the PostgresSQL Database Operator’s service instances are bindable.

You can establish a binding connection with Operator-backed components.

This procedure walks through an example of creating a binding connection between a PostgreSQL Database service and a Node.js application. To create a binding connection with a service that is backed by the PostgreSQL Database Operator, you must first add the Red Hat-provided PostgreSQL Database Operator to the OperatorHub using a backing OperatorSource, and then install the Operator.

Prerequisite

  • Ensure that you have created and deployed a Node.js application using the Developer perspective.
  • Ensure that you have installed the Service Binding Operator from OperatorHub.

Procedure

  1. Create a backing OperatorSource that adds the PostgresSQL Operator provided by Red Hat to the OperatorHub. A backing OperatorSource exposes the binding information in secrets, ConfigMaps, status, and spec attributes.

    1. In the Add view, click the YAML option to see the Import YAML screen.
    2. Add the following YAML file to apply the OperatorSource:

      apiVersion: operators.coreos.com/v1
      kind: OperatorSource
      metadata:
       name: db-operators
       namespace: openshift-marketplace
      spec:
       type: appregistry
       endpoint: https://quay.io/cnr
       registryNamespace: pmacik
    3. Click Create to create the OperatorSource in your cluster.
  2. Install the Red Hat-provided PostgreSQL Database Operator:

    1. In the Administrator perspective of the console, navigate to Operators → OperatorHub.
    2. In the Database category, select the PostgreSQL Database Operator and install it.
  3. Create a database (DB) instance for the application:

    1. Switch to the Developer perspective and ensure that you are in the appropriate project.
    2. In the Add view, click the YAML option to see the Import YAML screen.
    3. Add the service instance YAML in the editor and click Create to deploy the service. Following is an example of what the service YAML will look like:

      apiVersion: postgresql.baiju.dev/v1alpha1
      kind: Database
      metadata:
       name: db-demo
       namespace: test-project
      spec:
       image: docker.io/postgres
       imageName: postgres
       dbName: db-demo

      A DB instance is now deployed in the Topology view.

  4. In the Topology view, hover over the Node.js component to see a dangling arrow on the node.
  5. Click and drag the arrow towards the db-demo-postgresql service to make a binding connection with the Node.js application. A ServiceBindingRequest is created and the Service Binding Operator controller injects the DB connection information into the application Deployment as environment variables. After the request is successful, the application is redeployed and the connection is established.

    Figure 2.6. Binding connector

    odc binding connector

2.4.7. Labels and annotations used for the Topology view

The Topology view uses the following labels and annotations:

Icon displayed in the node
Icons in the node are defined by looking for matching icons using the app.openshift.io/runtime label, followed by the app.kubernetes.io/name label. This matching is done using a predefined set of icons.
Link to the source code editor or the source
The app.openshift.io/vcs-uri annotation is used to create links to the source code editor.
Node Connector
The app.openshift.io/connects-to annotation is used to connect the nodes.
App grouping
The app.kubernetes.io/part-of=<appname> label is used to group the applications, services, and components.

For detailed information on the labels and annotations OpenShift Container Platform applications must use, see Guidelines for labels and annotations for OpenShift applications.

2.5. Editing applications

You can edit the configuration and the source code of the application you create using the Topology view.

2.5.1. Prerequisites

2.5.2. Editing the source code of an application using the Developer perspective

You can use the Topology view in the Developer perspective to edit the source code of your application.

Procedure

  • In the Topology view, click the Edit Source code icon, displayed at the bottom-right of the deployed application, to access your source code and modify it.

    Note

    This feature is available only when you create applications using the From Git, From Catalog, and the From Dockerfile options.

    If the Eclipse Che Operator is installed in your cluster, a Che workspace ( odc che workspace ) is created and you are directed to the workspace to edit your source code. If it is not installed, you will be directed to the Git repository ( odc git repository ) your source code is hosted in.

2.5.3. Editing the application configuration using the Developer perspective

You can use the Topology view in the Developer perspective to edit the configuration of your application.

Note

Currently, only configurations of applications created by using the From Git, Container Image, From Catalog, or From Dockerfile options in the Add workflow of the Developer perspective can be edited. Configurations of applications created by using the CLI or the YAML option from the Add workflow cannot be edited.

Prerequisites

Ensure that you have created an application using the From Git, Container Image, From Catalog, or From Dockerfile options in the Add workflow.

Procedure

  1. After you have created an application and it is displayed in the Topology view, right-click the application to see the edit options available.

    Figure 2.7. Edit application

    odc edit app
  2. Click Edit application-name to see the Add workflow you used to create the application. The form is pre-populated with the values you had added while creating the application.
  3. Edit the necessary values for the application.

    Note

    You cannot edit the Name field in the General section, the CI/CD pipelines, or the Create a route to the application field in the Advanced Options section.

  4. Click Save to restart the build and deploy a new image.

    Figure 2.8. Edit and redeploy application

    odc edit redeploy

2.6. Working with Helm charts using the Developer perspective

2.6.1. Understanding Helm

Helm is a software package manager that simplifies deployment of applications and services to OpenShift Container Platform clusters.

Helm uses a packaging format called charts. A Helm chart is a collection of files that describes the OpenShift Container Platform resources.

A running instance of the chart in a cluster is called a release. A new release is created every time a chart is installed on the cluster.

Each time a chart is installed, or a release is upgraded or rolled back, an incremental revision is created.

2.6.1.1. Key features

Helm provides the ability to:

  • Search through a large collection of charts stored in the chart repository.
  • Modify existing charts.
  • Create your own charts with OpenShift Container Platform or Kubernetes resources.
  • Package and share your applications as charts.

You can use the Developer perspective in the web console to select and install a chart from the Helm charts listed in the Developer Catalog. You can create a Helm release using these charts, upgrade, rollback, and uninstall the release.

2.6.2. Prerequisites

2.6.3. Installing Helm charts

You can use either the Developer perspective or the CLI to create Helm releases and see them in the Developer perspective of the web console.

Procedure

To create Helm releases from the Helm charts provided in the Developer Catalog:

  1. In the Developer perspective, navigate to the +Add view and select a project. Then click Helm Chart option to see all the Helm Charts in the Developer Catalog.
  2. Select a chart and read the description, README, and other details about the chart.
  3. Click Install Helm Chart.

    Figure 2.9. Helm charts in developer catalog

    odc helm chart devcatalog
  4. In the Install Helm Chart page:

    1. Enter a unique name for the release in the Release Name field.
    2. Select the required chart version from the Chart Version drop-down list.
    3. Configure your Helm chart by using the Form View or the YAML View.

      Note

      Where available, you can switch between the YAML View and Form View. The data is persisted when switching between the views.

    4. Click Install to create a Helm release. You will be redirected to the Topology view where the release is displayed. If the Helm chart has release notes, the chart is pre-selected and the right panel displays the release notes for that release.

You can upgrade, rollback, or uninstall a Helm release by using the Actions button on the side panel or by right-clicking a Helm release.

2.6.4. Upgrading a Helm release

You can upgrade a Helm release to upgrade to a new chart version or update your release configuration.

Procedure

  1. In the Topology view, select the Helm release to see the side panel.
  2. Click ActionsUpgrade Helm Release.
  3. In the Upgrade Helm Release page, select the Chart Version you want to upgrade to, and then click Upgrade to create another Helm release. The Helm Releases page displays the two revisions.

2.6.5. Rolling back a Helm release

If a release fails, you can rollback the Helm release to a previous version.

Procedure

To rollback a release using the Helm view:

  1. In the Developer perspective, navigate to the Helm view to see the Helm Releases in the namespace.
  2. Click the Options menu kebab adjoining the listed release, and select Rollback.
  3. In the Rollback Helm Release page, select the Revision you want to rollback to and click Rollback.
  4. In the Helm Releases page, click on the chart to see the details and resources for that release.
  5. Go to the Revision History tab to see all the revisions for the chart.

    Figure 2.10. Helm revision history

    odc helm revision history
  6. If required, you can further use the Options menu kebab adjoining a particular revision and select the revision to rollback to.

2.6.6. Uninstalling a Helm release

Procedure

  1. In the Topology view, right-click the Helm release and select Uninstall Helm Release.
  2. In the confirmation prompt, enter the name of the chart and click Uninstall.

2.7. Deleting applications

You can delete applications created in your project.

2.7.1. Deleting applications using the Developer perspective

You can delete an application and all of its associated components using the Topology view in the Developer perspective:

  1. Click the application you want to delete to see the side panel with the resource details of the application.
  2. Click the Actions drop-down menu displayed on the upper right of the panel, and select Delete Application to see a confirmation dialog box.
  3. Enter the name of the application and click Delete to delete it.

You can also right-click the application you want to delete and click Delete Application to delete it.

Chapter 3. Deployments

3.1. 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.

3.1.1. Building blocks of a deployment

Deployments and DeploymentConfigs are enabled by the use of native Kubernetes API objects ReplicaSets and ReplicationControllers, 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.

3.1.1.1. 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.

3.1.1.2. 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.

3.1.2. 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.

3.1.3. 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

3.1.4. 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.

3.1.4.1. 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.

3.1.4.2. 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.

3.1.4.3. 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 replica set.

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.

3.2. Managing deployment processes

3.2.1. 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.

3.2.1.1. 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.

3.2.1.2. 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>

3.2.1.3. 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.

3.2.1.4. 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.

3.2.1.5. 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

3.2.1.6. 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>

3.2.1.7. 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.

3.2.1.7.1. 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>

3.2.1.8. 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.

3.2.1.9. 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.

3.2.1.10. 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.

3.2.1.11. 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.

3.2.1.12. 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>

3.3. 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.

3.3.1. 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.

3.3.1.1. 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.

3.3.1.2. 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.

3.3.1.3. Starting a Rolling deployment using the Developer perspective

Prerequisites

  • Ensure that you are in the Developer perspective of the web console.
  • Ensure that you have created an application using the Add view and see it deployed in the Topology view.

Procedure

To start a rolling deployment to upgrade an application:

  1. In the Topology view of the Developer perspective, click on the application node to see the Overview tab in the side panel. Note that the Update Strategy is set to the default Rolling strategy.
  2. In the Actions drop-down menu, select Start Rollout to start a rolling update. The rolling deployment spins up the new version of the application and then terminates the old one.

    Figure 3.1. Rolling update

    odc rolling update

3.3.2. 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.

3.3.3. Starting a Recreate deployment using the Developer perspective

You can switch the deployment strategy from the default Rolling update to a Recreate update using the Developer perspective in the web console.

Prerequisites

  • Ensure that you are in the Developer perspective of the web console.
  • Ensure that you have created an application using the Add view and see it deployed in the Topology view.

Procedure

To switch to a Recreate update strategy and to upgrade an application:

  1. In the Actions drop-down menu, select Edit Deployment Config to see the deployment configuration details of the application.
  2. In the YAML editor, change the spec.strategy.type to Recreate and click Save.
  3. In the Topology view, select the node to see the Overview tab in the side panel. The Update Strategy is now set to Recreate.
  4. Use the Actions drop-down menu to select Start Rollout to start an update using the Recreate strategy. The Recreate strategy first terminates pods for the older version of the application and then spins up pods for the new version.

    Figure 3.2. Recreate update

    odc recreate update

3.3.4. 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.

3.3.5. 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.

3.3.5.1. 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 \
        --volumes data --failure-policy=abort -- /usr/bin/command arg1 arg2

3.4. 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.

3.4.1. 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.

3.4.2. 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.

3.4.3. 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.

3.4.4. 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.

3.4.4.1. 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 independent application components.

    1. Create a copy of the example application running the v1 image under the example-green service:

      $ oc new-app openshift/deployment-example:v1 --name=example-green
    2. Create a second copy that uses the v2 image under the example-blue service:

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

3.4.5. 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.

3.4.5.1. 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.

    1. Create the first application. The following example creates an application called ab-example-a:

      $ oc new-app openshift/deployment-example --name=ab-example-a
    2. Create the second application:

      $ 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>

    Example output

    ...
    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
    ...

3.4.5.1.1. Managing weights of an existing route using the web console

Procedure

  1. Navigate to the NetworkingRoutes page.
  2. Click the Actions menu kebab next to the Route you want to edit and select Edit Route.
  3. Edit the YAML file. Update the weight to be an integer between 0 and 256 that specifies the relative weight of the target against other target reference objects. The value 0 suppresses requests to this back end. The default is 100. Run oc explain routes.spec.alternateBackends for more information about the options.
  4. Click Save.
3.4.5.1.2. Managing weights of an new route using the web console
  1. Navigate to the NetworkingRoutes page.
  2. Click Create Route.
  3. Enter the route Name.
  4. Select the Service.
  5. Click Add Alternate Service.
  6. Enter a value for Weight and Alternate Service Weight. Enter a number between 0 and 255 that depicts relative weight compared with other targets. The default is 100.
  7. Select the Target Port.
  8. Click Create.
3.4.5.1.3. 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

    Example output

    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.

    The following example alters the weight of ab-example-a and ab-example-b services:

    $ oc set route-backends ab-example --adjust ab-example-a=200 ab-example-b=10

    Alternatively, alter the weight of a service by specifying a percentage:

    $ oc set route-backends ab-example --adjust ab-example-b=5%

    By specifying + before the percentage declaration, you can adjust a weighting relative to the current setting. For example:

    $ 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.

3.4.5.1.4. 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 4. Quotas

4.1. 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.

4.1.1. 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 4.1. 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 4.2. 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 4.3. 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.

4.1.2. 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.

4.1.3. 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.

4.1.4. 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.

4.1.5. 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.

4.1.6. 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

4.1.6.1. 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

    Example output

    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

    Example output

    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

4.1.6.2. 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'

    Example output

                        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

    Example output

    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

    Example output

    resourcequota/gpu-quota created

  4. Verify that the namespace has the correct quota set:

    # oc describe quota gpu-quota -n nvidia

    Example output

    Name:                    gpu-quota
    Namespace:               nvidia
    Resource                 Used  Hard
    --------                 ----  ----
    requests.nvidia.com/gpu  0     1

  5. Define a Pod that asks for a single GPU. The following example definition file is called 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. Create the Pod:

    # oc create -f gpu-pod.yaml
  7. Verify that the pod is running:

    # oc get pods

    Example output

    NAME              READY     STATUS      RESTARTS   AGE
    gpu-pod-s46h7     1/1       Running     0          1m

  8. Verify that the quota Used counter is correct:

    # oc describe quota gpu-quota -n nvidia

    Example output

    Name:                    gpu-quota
    Namespace:               nvidia
    Resource                 Used  Hard
    --------                 ----  ----
    requests.nvidia.com/gpu  1     1

  9. 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

    Example output

    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.

4.1.7. 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

    Example output

    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

    Example output

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

4.1.8. Configuring explicit resource quotas

Configure explicit resource quotas in a project request template to apply specific resource quotas in new projects.

Prerequisites

  • Access to the cluster as a user with the cluster-admin role.
  • Install the OpenShift CLI (oc).

Procedure

  1. Add a resource quota definition to a project request template:

    • If a project request template does not exist in a cluster:

      1. Create a bootstrap project template and output it to a file called template.yaml:

        $ oc adm create-bootstrap-project-template -o yaml > template.yaml
      2. Add a resource quota definition to template.yaml. The following example defines a resource quota named 'storage-consumption'. The definition must be added before the parameters: section in the template:

        - 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 value is set to 0, the 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 value is set to 0, the bronze storage class cannot create claims.
      3. Create a project request template from the modified template.yaml file in the openshift-config namespace:

        $ oc create -f template.yaml -n openshift-config
        Note

        To include the configuration as a kubectl.kubernetes.io/last-applied-configuration annotation, add the --save-config option to the oc create command.

        By default, the template is called project-request.

    • If a project request template already exists within a cluster:

      Note

      If you declaratively or imperatively manage objects within your cluster by using configuration files, edit the existing project request template through those files instead.

      1. List templates in the openshift-config namespace:

        $ oc get templates -n openshift-config
      2. Edit an existing project request template:

        $ oc edit template <project_request_template> -n openshift-config
      3. Add a resource quota definition, such as the preceding 'storage-consumption' example, into the existing template. The definition must be added before the parameters: section in the template.
  2. If you created a project request template, reference it in the cluster’s project configuration resource:

    1. Access the project configuration resource for editing:

      • By 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.
      • By using the CLI:

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

          $ oc edit project.config.openshift.io/cluster
    2. Update the spec section of the project configuration resource to include the projectRequestTemplate and name parameters. The following example references the default project request template name project-request:

      apiVersion: config.openshift.io/v1
      kind: Project
      metadata:
        ...
      spec:
        projectRequestTemplate:
          name: project-request
  3. Verify that the resource quota is applied when projects are created:

    1. Create a project:

      $ oc new-project <project_name>
    2. List the project’s resource quotas:

      $ oc get resourcequotas
    3. Describe the resource quota in detail:

      $ oc describe resourcequotas <resource_quota_name>

4.2. 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.

4.2.1. 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

4.2.2. 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

    Example output

    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

4.2.3. 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 5. Monitoring project and application metrics using the Developer perspective

The Monitoring view in the Developer perspective provides options to monitor your project or application metrics, such as CPU, memory, and bandwidth usage, and network related information.

5.1. Prerequisites

5.2. Monitoring your project metrics

After you create applications in your project and deploy them, you can use the Developer perspective in the web console to see the metrics for your project.

Procedure

  1. On the left navigation panel of the Developer perspective, click Monitoring to see the Dashboard, Metrics, Alerts, and Events for your project.

    • Use the Dashboard tab to see graphs depicting the CPU, memory, and bandwidth consumption and network related information, such as the rate of transmitted and received packets and the rate of dropped packets.

      Figure 5.1. Monitoring dashboard

      odc project dashboard

      Use the following options to see further details:

      • Select a workload from the All Workloads list to see the filtered metrics for the selected workload.
      • Select an option from the Time Range list to determine the time frame for the data being captured.
      • Select an option from the Refresh Interval list to determine the time period after which the data is refreshed.
      • Hover your cursor over the graphs to see specific details for your pod.
      • Click on any of the graphs displayed to see the details for that particular metric in the Metrics page.
    • Use the Metrics tab to query for the required project metric.

      Figure 5.2. Monitoring metrics

      odc project metrics
      1. In the Select Query list, select an option to filter the required details for your project. The filtered metrics for all the application pods in your project are displayed in the graph. The pods in your project are also listed below.
      2. From the list of pods, clear the colored square boxes to remove the metrics for specific pods to further filter your query result.
      3. Click Show PromQL to see the Prometheus query. You can further modify this query with the help of prompts to customize the query and filter the metrics you want to see for that namespace.
      4. Use the drop-down list to set a time range for the data being displayed. You can click Reset Zoom to reset it to the default time range.
      5. Optionally, in the Select Query list, select Custom Query to create a custom Prometheus query and filter relevant metrics.
    • Use the Alerts tab to see the rules that trigger alerts for the applications in your project, identify the alerts firing in the project, and silence them if required.

      Figure 5.3. Monitoring alerts

      odc project alerts
      • Use the Filter list to filter the alerts by their Alert State and Severity.
      • Click on an alert to go to the details page for that alert. In the Alerts Details page, you can click the View Metrics button to see the metrics for the alert.
      • Use the Notifications toggle adjoining an alert rule to silence all the alerts for that rule, and then select the duration for which the alerts will be silenced from the Silence for list. You must have the permissions to edit alerts to see the Notifications toggle.
      • Use the Options menu kebab adjoining an alert rule to see the details of the alerting rule.
    • Use the Events tab to see the events for your project.

      Figure 5.4. Monitoring events

      odc project events

      You can filter the displayed events using the following options:

      • In the Resources list, select a resource to see events for that resource.
      • In the All Types list, select a type of event to see events relevant to that type.
      • Search for specific events using the Filter events by names or messages field.

5.3. Monitoring your application metrics

After you create applications in your project and deploy them, you can use the Topology view in the Developer perspective to see the alerts and metrics for your application. Critical and warning alerts for your application are indicated on the workload node in the Topology view.

Procedure

To see the alerts for your workload:

  1. In the Topology view, click the workload to see the workload details in the right panel.
  2. Click the Monitoring tab to see the critical and warning alerts for the application; graphs for metrics, such as CPU, memory, and bandwidth usage; and all the events for the application.

    Note

    Only critical and warning alerts in the Firing state are displayed in the Topology view. Alerts in the Silenced, Pending and Not Firing states are not displayed.

    Figure 5.5. Monitoring application metrics

    odc app metrics
    1. Click the alert listed in the right panel to see the alert details in the Alert Details page.
    2. Click any of the charts to go to the Metrics tab to see the detailed metrics for the application.
    3. Click View monitoring dashboard to see the monitoring dashboard for that application.

5.4. Additional Resources

Chapter 6. Monitoring application health by using health checks

In software systems, components can become unhealthy due to transient issues such as temporary connectivity loss, configuration errors, or problems with external dependencies. OpenShift Container Platform applications have a number of options to detect and handle unhealthy containers.

6.1. Understanding health checks

A health check periodically performs diagnostics on a running container using any combination of the readiness, liveness, and startup health checks.

You can include one or more probes in the specification for the pod that contains the container which you want to perform the health checks.

Note

If you want to add or edit health checks in an existing pod, you must edit the pod deployment configuration or use the Developer perspective in the web console. You cannot use the CLI to add or edit health checks for an existing pod.

Readiness probe

A readiness probe determines if a container is ready to accept service requests. If the readiness probe fails for a container, the kubelet removes the pod from the list of available service endpoints.

After a failure, the probe continues to examine the pod. If the pod becomes available, the kubelet adds the pod to the list of available service endpoints.

Liveness health check

A liveness probe determines if a container is still running. If the liveness probe fails due to a condition such as a deadlock, the kubelet kills the container. The pod then responds based on its restart policy.

For example, a liveness probe on a pod with a restartPolicy of Always or OnFailure kills and restarts the container.

Startup probe

A startup probe indicates whether the application within a container is started. All other probes are disabled until the startup succeeds. If the startup probe does not succeed within a specified time period, the kubelet kills the container, and the container is subject to the pod restartPolicy.

Some applications can require additional start-up time on their first initialization. You can use a startup probe with a liveness or readiness probe to delay that probe long enough to handle lengthy start-up time using the failureThreshold and periodSeconds parameters.

For example, you can add a startup probe, with a failureThreshold of 30 seconds and a periodSeconds of 10 seconds (30 * 10 = 300s) for a maximum of 5 minutes, to a liveness probe. After the startup probe succeeds the first time, the liveness probe takes over.

You can configure liveness, readiness, and startup probes with any of the following types of tests:

  • HTTP GET: When using an HTTP GET test, the test determines the healthiness of the container by using a web hook. The test is successful if the HTTP response code is between 200 and 399.

    You can use an HTTP GET test with applications that return HTTP status codes when completely initialized.

  • Container Command: When using a container command test, the probe executes a command inside the container. The probe is successful if the test exits with a 0 status.
  • TCP socket: When using a TCP socket test, the probe attempts to open a socket to the container. The container is only considered healthy if the probe can establish a connection. You can use a TCP socket test with applications that do not start listening until initialization is complete.

You can configure several fields to control the behavior of a probe:

  • initialDelaySeconds: The time, in seconds, after the container starts before the probe can be scheduled. The defaults is 0.
  • periodSeconds: The delay, in seconds, between performing probes. The default is 10.
  • timeoutSeconds: The number of seconds of inactivity after which the probe times out and the container is assumed to have failed. The defaults is 1.
  • successThreshold: The number of times that the probe must report success after a failure in order to reset the container status to successful. The value must be 1 for a liveness probe. The default is 1.
  • failureThreshold: The number of times that the probe is allowed to fail. The default is 3. After the specified attempts:

    • for a liveness probe, the container is restarted
    • for a readiness probe, the pod is marked Unready
    • for a startup probe, the container is killed and is subject to the pod’s restartPolicy

      Note

      The timeoutSeconds parameter has no effect on the readiness and liveness probes for container command probes, as OpenShift Container Platform cannot time out on an exec call into the container. One way to implement a timeout in a container command probe is by using the exec-timeout command to run your liveness or readiness probes, as shown in the examples.

Example probes

The following are samples of different probes as they would appear in an object specification.

Sample readiness probe with a container command readiness probe in a pod spec

apiVersion: v1
kind: Pod
metadata:
  labels:
    test: health-check
  name: my-application
...
spec:
  containers:
  - name: goproxy-app 1
    args:
    image: k8s.gcr.io/goproxy:0.1 2
    readinessProbe: 3
      exec: 4
        command: 5
        - cat
        - /tmp/healthy
...

1
The container name.
2
The container image to deploy.
3
A readiness probe.
4
A container command test.
5
The commands to execute on the container.

Sample container command startup probe and liveness probe with container command tests in a pod spec

apiVersion: v1
kind: Pod
metadata:
  labels:
    test: health-check
  name: my-application
...
spec:
  containers:
  - name: goproxy-app 1
    args:
    image: k8s.gcr.io/goproxy:0.1 2
    livenessProbe: 3
      httpGet: 4
        scheme: HTTPS 5
        path: /healthz
        port: 8080 6
        httpHeaders:
        - name: X-Custom-Header
          value: Awesome
    startupProbe: 7
      httpGet: 8
        path: /healthz
        port: 8080 9
   failureThreshold: 30 10
   periodSeconds: 10 11
...

1
The container name.
2
Specify the container image to deploy.
3
A liveness probe.
4
An HTTP GET test.
5
The internet scheme: HTTP or HTTPS. The default value is HTTP.
6
The port on which the container is listening.
7
A startup probe.
8
An HTTP GET test.
9
The port on which the container is listening.
10
The number of times to try the probe after a failure.
11
The number of seconds to perform the probe.

Sample liveness probe with a container command test that uses a timeout in a pod spec

apiVersion: v1
kind: Pod
metadata:
  labels:
    test: health-check
  name: my-application
...
spec:
  containers:
  - name: goproxy-app 1
    args:
    image: k8s.gcr.io/goproxy:0.1 2
    livenessProbe: 3
      exec: 4
        command: 5
        - /bin/bash
        - '-c'
        - timeout 60 /opt/eap/bin/livenessProbe.sh
      periodSeconds: 10 6
      successThreshold: 1 7
      failureThreshold: 3 8
...

1
The container name.
2
Specify the container image to deploy.
3
The liveness probe.
4
The type of probe, here a container command probe.
5
The command line to execute inside the container.
6
How often in seconds to perform the probe.
7
The number of number of consecutive successes needed to show success after a failure.
8
The number of times to try the probe after a failure.

Sample readiness probe and liveness probe with a TCP socket test in a deployment

kind: Deployment
apiVersion: apps/v1
...
spec:
...
  template:
    spec:
      containers:
        - resources: {}
          readinessProbe: 1
            tcpSocket:
              port: 8080
            timeoutSeconds: 1
            periodSeconds: 10
            successThreshold: 1
            failureThreshold: 3
          terminationMessagePath: /dev/termination-log
          name: ruby-ex
          livenessProbe: 2
            tcpSocket:
              port: 8080
            initialDelaySeconds: 15
            timeoutSeconds: 1
            periodSeconds: 10
            successThreshold: 1
            failureThreshold: 3
...

1
The readiness probe.
2
The liveness probe.

6.2. Configuring health checks using the CLI

To configure readiness, liveness, and startup probes, add one or more probes to the specification for the pod that contains the container which you want to perform the health checks

Note

If you want to add or edit health checks in an existing pod, you must edit the pod deployment configuration or use the Developer perspective in the web console. You cannot use the CLI to add or edit health checks for an existing pod.

Procedure

To add probes for a container:

  1. Create a Pod object to add one or more probes:

    apiVersion: v1
    kind: Pod
    metadata:
      labels:
        test: health-check
      name: my-application
    spec:
      containers:
      - name: my-container 1
        args:
        image: k8s.gcr.io/goproxy:0.1 2
        livenessProbe: 3
          tcpSocket:  4
            port: 8080 5
          initialDelaySeconds: 15 6
          timeoutSeconds: 1 7
        readinessProbe: 8
          httpGet: 9
            host: my-host 10
            scheme: HTTPS 11
            path: /healthz
            port: 8080 12
        startupProbe: 13
          exec: 14
            command: 15
            - cat
            - /tmp/healthy
          failureThreshold: 30 16
          periodSeconds: 10 17
    1
    Specify the container name.
    2
    Specify the container image to deploy.
    3
    Optional: Create a Liveness probe.
    4
    Specify a test to perform, here a TCP Socket test.
    5
    Specify the port on which the container is listening.
    6
    Specify the number of seconds before performing the first probe after the container starts.
    7
    Specify the number of seconds between probes.
    8
    Optional: Create a Readiness probe.
    9
    Specify the type of test to perform, here an HTTP test.
    10
    Specify a host IP address. When host is not defined, the PodIP is used.
    11
    Specify HTTP or HTTPS. When scheme is not defined, the HTTP scheme is used.
    12
    Specify the port on which the container is listening.
    13
    Optional: Create a Startup probe.
    14
    Specify the type of test to perform, here an Container Execution probe.
    15
    Specify the commands to execute on the container.
    16
    Specify the number of times to try the probe after a failure.
    17
    Specify the number of seconds to perform the probe.
    Note

    If the initialDelaySeconds value is lower than the periodSeconds value, the first Readiness probe occurs at some point between the two periods due to an issue with timers.

  2. Create the Pod object:

    $ oc create -f <file-name>.yaml
  3. Verify the state of the health check pod:

    $ oc describe pod health-check

    Example output

    Events:
      Type    Reason     Age   From                                  Message
      ----    ------     ----  ----                                  -------
      Normal  Scheduled  9s    default-scheduler                     Successfully assigned openshift-logging/liveness-exec to ip-10-0-143-40.ec2.internal
      Normal  Pulling    2s    kubelet, ip-10-0-143-40.ec2.internal  pulling image "k8s.gcr.io/liveness"
      Normal  Pulled     1s    kubelet, ip-10-0-143-40.ec2.internal  Successfully pulled image "k8s.gcr.io/liveness"
      Normal  Created    1s    kubelet, ip-10-0-143-40.ec2.internal  Created container
      Normal  Started    1s    kubelet, ip-10-0-143-40.ec2.internal  Started container

    The following is the output of a failed probe that restarted a container:

    Sample Liveness check output with unhealthy container

    $ oc describe pod pod1

    Example output

    ....
    
    Events:
      Type     Reason          Age                From                                               Message
      ----     ------          ----               ----                                               -------
      Normal   Scheduled       <unknown>                                                             Successfully assigned aaa/liveness-http to ci-ln-37hz77b-f76d1-wdpjv-worker-b-snzrj
      Normal   AddedInterface  47s                multus                                             Add eth0 [10.129.2.11/23]
      Normal   Pulled          46s                kubelet, ci-ln-37hz77b-f76d1-wdpjv-worker-b-snzrj  Successfully pulled image "k8s.gcr.io/liveness" in 773.406244ms
      Normal   Pulled          28s                kubelet, ci-ln-37hz77b-f76d1-wdpjv-worker-b-snzrj  Successfully pulled image "k8s.gcr.io/liveness" in 233.328564ms
      Normal   Created         10s (x3 over 46s)  kubelet, ci-ln-37hz77b-f76d1-wdpjv-worker-b-snzrj  Created container liveness
      Normal   Started         10s (x3 over 46s)  kubelet, ci-ln-37hz77b-f76d1-wdpjv-worker-b-snzrj  Started container liveness
      Warning  Unhealthy       10s (x6 over 34s)  kubelet, ci-ln-37hz77b-f76d1-wdpjv-worker-b-snzrj  Liveness probe failed: HTTP probe failed with statuscode: 500
      Normal   Killing         10s (x2 over 28s)  kubelet, ci-ln-37hz77b-f76d1-wdpjv-worker-b-snzrj  Container liveness failed liveness probe, will be restarted
      Normal   Pulling         10s (x3 over 47s)  kubelet, ci-ln-37hz77b-f76d1-wdpjv-worker-b-snzrj  Pulling image "k8s.gcr.io/liveness"
      Normal   Pulled          10s                kubelet, ci-ln-37hz77b-f76d1-wdpjv-worker-b-snzrj  Successfully pulled image "k8s.gcr.io/liveness" in 244.116568ms

6.3. Monitoring application health using the Developer perspective

You can use the Developer perspective to add three types of health probes to your container to ensure that your application is healthy:

  • Use the Readiness probe to check if the container is ready to handle requests.
  • Use the Liveness probe to check if the container is running.
  • Use the Startup probe to check if the application within the container has started.

You can add health checks either while creating and deploying an application, or after you have deployed an application.

6.4. Adding health checks using the Developer perspective

You can use the Topology view to add health checks to your deployed application.

Prerequisites:

  • You have switched to the Developer perspective in the web console.
  • You have created and deployed an application on OpenShift Container Platform using the Developer perspective.

Procedure

  1. In the Topology view, click on the application node to see the side panel. If the container does not have health checks added to ensure the smooth running of your application, a Health Checks notification is displayed with a link to add health checks.
  2. In the displayed notification, click the Add Health Checks link.
  3. Alternatively, you can also click the Actions drop-down list and select Add Health Checks. Note that if the container already has health checks, you will see the Edit Health Checks option instead of the add option.
  4. In the Add Health Checks form, if you have deployed multiple containers, use the Container drop-down list to ensure that the appropriate container is selected.
  5. Click the required health probe links to add them to the container. Default data for the health checks is prepopulated. You can add the probes with the default data or further customize the values and then add them. For example, to add a Readiness probe that checks if your container is ready to handle requests:

    1. Click Add Readiness Probe, to see a form containing the parameters for the probe.
    2. Click the Type drop-down list to select the request type you want to add. For example, in this case, select Container Command to select the command that will be executed inside the container.
    3. In the Command field, add an argument cat, similarly, you can add multiple arguments for the check, for example, add another argument /tmp/healthy.
    4. Retain or modify the default values for the other parameters as required, and click the check mark at the bottom of the form. The Readiness Probe Added message is displayed.
  6. Click Add to add the health check. You are redirected to the Topology view and the container is restarted.
  7. In the side panel, verify that the probes have been added by clicking on the deployed Pod under the Pods section.
  8. In the Pod Details page, click the listed container in the Containers section.
  9. In the Container Details page, verify that the Readiness probe - Exec Command cat /tmp/healthy has been added to the container.

6.5. Editing health checks using the Developer perspective

You can use the Topology view to edit health checks added to your application, modify them, or add more health checks.

Prerequisites:

  • You have switched to the Developer perspective in the web console.
  • You have created and deployed an application on OpenShift Container Platform using the Developer perspective.
  • You have added health checks to your application.

Procedure

  1. In the Topology view, right-click your application and select Edit Health Checks. Alternatively, in the side panel, click the Actions drop-down list and select Edit Health Checks.
  2. In the Edit Health Checks page:

    • To remove a previously added health probe, click the minus sign adjoining it.
    • To edit the parameters of an existing probe:

      1. Click the Edit Probe link next to a previously added probe to see the parameters for the probe.
      2. Modify the parameters as required, and click the check mark to save your changes.
    • To add a new health probe, in addition to existing health checks, click the add probe links. For example, to add a Liveness probe that checks if your container is running:

      1. Click Add Liveness Probe, to see a form containing the parameters for the probe.
      2. Edit the probe parameters as required, and click the check mark at the bottom of the form. The Liveness Probe Added message is displayed.
  3. Click Save to save your modifications and add the additional probes to your container. You are redirected to the Topology view.
  4. In the side panel, verify that the probes have been added by clicking on the deployed Pod under the Pods section.
  5. In the Pod Details page, click the listed container in the Containers section.
  6. In the Container Details page, verify that the Liveness probe - HTTP Get 10.129.4.65:8080/ has been added to the container, in addition to the earlier existing probes.

6.6. Monitoring health check failures using the Developer perspective

In case an application health check fails, you can use the Topology view to monitor these health check violations.

Prerequisites:

  • You have switched to the Developer perspective in the web console.
  • You have created and deployed an application on OpenShift Container Platform using the Developer perspective.
  • You have added health checks to your application.

Procedure

  1. In the Topology view, click on the application node to see the side panel.
  2. Click the Monitoring tab to see the health check failures in the Events (Warning) section.
  3. Click the down arrow adjoining Events (Warning) to see the details of the health check failure.

Additional Resources

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-config=ldap-sync-config.yaml

To perform the prune operation:

$ oc adm prune groups --sync-config=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. Automatically pruning images

Images that are no longer required by the system due to age, status, or exceed limits are automatically pruned. Cluster administrators can configure the Pruning Custom Resource, or delete it to disable it.

Note

When the Pruning Custom Resource is deleted, the pruning CronJob and its related components should also be deleted.

Prerequisites

  • Cluster administrator permissions.
  • Install the oc CLI.

Procedure

  • Verify that the object named imagepruners.imageregistry.operator.openshift.io/cluster contains the following spec and status fields:
spec:
  schedule: "0 0 * * *" 1
  suspend: false 2
  keepTagRevisions: 3 3
  keepYoungerThan: 60m 4
  resources: {} 5
  affinity: {} 6
  nodeSelector: {} 7
  tolerations: {} 8
  startingDeadlineSeconds: 60 9
  successfulJobsHistoryLimit: 3 10
  failedJobsHistoryLimit: 3 11
  logLevel: Normal 12
status:
  observedGeneration: 2 13
  conditions: 14
  - type: Available
    status: "True"
    lastTransitionTime: 2019-10-09T03:13:45
    reason: Ready
    message: "Periodic image pruner has been created."
  - type: Scheduled
    status: "True"
    lastTransitionTime: 2019-10-09T03:13:45
    reason: Scheduled
    message: "Image pruner job has been scheduled."
  - type: Failed
    staus: "False"
    lastTransitionTime: 2019-10-09T03:13:45
    reason: Succeeded
    message: "Most recent image pruning job succeeded."
1
schedule: CronJob formatted schedule, defaults to daily at midnight for new clusters. This is a required field.
2
suspend: If set to true, the CronJob running pruning is suspended. This is an optional field, and it defaults to false.
3
keepTagRevisions: The number of revisions per tag to keep. This is an optional field, and it defaults to 3 if not set.
4
keepYoungerThan: Retain images younger than this duration. This is an optional field, and it defaults 60m if not set.
5
resources: Standard Pod resource requests and limits. This is an optional field.
6
affinity: Standard Pod affinity. This is an optional field.
7
nodeSelector: Standard Pod node selector for the image pruner pod. This is an optional field.
8
tolerations: Standard Pod tolerations. This is an optional field.
9
startingDeadlineSeconds: Start deadline for CronJob. This is an optional field.
10
successfulJobsHistoryLimit: The maximum number of successful jobs to retain. Must be >= 1 to ensure metrics are reported. Defaults to 3 if not set.
11
failedJobsHistoryLimit: The maximum number of failed jobs to retain. Must be >= 1 to ensure metrics are reported. Defaults to 3 if not set.
12
logLevel: Sets the log level for the pruner job. Defaults to Normal.
  • Normal
  • Debug
  • Trace
  • TraceAll
13
observedGeneration: The generation observed by the Operator.
14
conditions: The standard condition objects with the following types:
  • Available: Indicates if the pruning job has been created. Reasons can be Ready or Error.
  • Scheduled: Indicates if the next pruning job has been scheduled. Reasons can be Scheduled, Suspended, or Error.
  • Failed: Indicates if the most recent pruning job failed.
Important

The Image Registry Operator’s behavior for managing the pruner is orthogonal to the managementState specified on the Image Registry Operator’s ClusterOperator object. If the image registry Operator is not in the Managed state, the image pruner can still be configured and managed by the Pruning Custom Resource.

However, the managementState of the Image Registry Operator alters the behavior of the deployed image pruner job:

  • Managed: the --prune-registry flag for the image pruner is set to true.
  • Removed: the --prune-registry flag for the image pruner is set to false, meaning it only prunes image metatdata in etcd.
  • Unmanaged: the --prune-registry flag for the image pruner is set to false.

8.6. Manually pruning images

The Pruning Custom Resource enables automatic image pruning. However, administrators can manually prune images that are no longer required by the system due to age, status, or exceed limits. There are two methods to manually prune images:

  • Running image pruning as a Job or CronJob on the cluster.
  • Running the oc adm prune images command.

Prerequisites

  • To prune images, you must first log in to the CLI as a user with an access token. The user must also have the system:image-pruner cluster role or greater (for example, cluster-admin).
  • Expose the image registry.

Procedure

To manually prune images that are no longer required by the system due to age, status, or exceed limits, use one of the following methods:

  • Run image pruning as a Job or CronJob on the cluster by creating a YAML file for the pruner service account, for example:

    $ oc create -f <filename>.yaml

    Example output

    kind: List
    apiVersion: v1
    items:
    - apiVersion: v1
      kind: ServiceAccount
      metadata:
        name: pruner
        namespace: openshift-image-registry
    - apiVersion: rbac.authorization.k8s.io/v1
      kind: ClusterRoleBinding
      metadata:
        name: openshift-image-registry-pruner
      roleRef:
        apiGroup: rbac.authorization.k8s.io
        kind: ClusterRole
        name: system:image-pruner
      subjects:
      - kind: ServiceAccount
        name: pruner
        namespace: openshift-image-registry
    - apiVersion: batch/v1beta1
      kind: CronJob
      metadata:
        name: image-pruner
        namespace: openshift-image-registry
      spec:
        schedule: "0 0 * * *"
        concurrencyPolicy: Forbid
        successfulJobsHistoryLimit: 1
        failedJobsHistoryLimit: 3
        jobTemplate:
          spec:
            template:
              spec:
                restartPolicy: OnFailure
                containers:
                - image: "quay.io/openshift/origin-cli:4.1"
                  resources:
                    requests:
                      cpu: 1
                      memory: 1Gi
                  terminationMessagePolicy: FallbackToLogsOnError
                  command:
                  - oc
                  args:
                  - adm
                  - prune
                  - images
                  - --certificate-authority=/var/run/secrets/kubernetes.io/serviceaccount/service-ca.crt
                  - --keep-tag-revisions=5
                  - --keep-younger-than=96h
                  - --confirm=true
                  name: image-pruner
                serviceAccountName: pruner

  • Run the oc adm prune images [<options>] command:

    $ oc adm prune images [<options>]

    Pruning images removes data from the integrated registry unless --prune-registry=false is used.

    Pruning images with the --namespace flag does not remove images, only imagestreams. Images are non-namespaced resources. Therefore, limiting pruning to a particular namespace makes it impossible to calculate its current usage.

    By default, the integrated registry caches metadata of blobs to reduce the number of requests to storage, and to increase the request-processing speed. Pruning does not update the integrated registry cache. Images that still contain pruned layers after pruning will be broken because the pruned layers that have metadata in the cache will not be pushed. Therefore, you must redeploy the registry to clear the cache after pruning:

    $ oc rollout restart deployment/image-registry -n openshift-image-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.

    The Prune images CLI configuration options table describes the options you can use with the oc adm prune images <options> command.

    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 test-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. Alternately, 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 option is useful when you are only concerned with removing etcd content, to reduce the number of image objects but are not concerned with cleaning up registry storage, or if you intend to do that separately by hard pruning the registry during an appropriate maintenance window for the registry.

8.6.1. Image prune conditions

You can apply conditions to your manually pruned images.

  • To remove any image managed by OpenShift Container Platform, or images with the annotation openshift.io/image.managed:

    • Created at least --keep-younger-than minutes ago and are not currently referenced by any:

      • Pods created less than --keep-younger-than minutes ago
      • Imagestreams created less than --keep-younger-than minutes ago
      • Running pods
      • Pending pods
      • ReplicationControllers
      • Deployments
      • DeploymentConfigs
      • ReplicaSets
      • Build Configurations
      • Builds
      • --keep-tag-revisions most recent items in stream.status.tags[].items
    • That are exceeding the smallest limit defined in the same project and are not currently referenced by any:

      • Running pods
      • Pending pods
      • ReplicationControllers
      • Deployments
      • DeploymentConfigs
      • ReplicaSets
      • Build Configurations
      • 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 the --keep-tag-revisions flag nor the --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, can narrow 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 that you can mitigate any references to deleted content.

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.

8.6.2. 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, imagestreams, and pods) younger than 60 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 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

8.6.3. 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.

8.6.4. 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:

$ 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 "'"sha:abz"\
  $'"}}{{$is.metadata.name}}:{{$tag.tag}} at position {{$ii}} out of {{len $tag.items}}\n'\
  '{{end}}{{end}}{{end}}{{end}}'

Example output

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.

    Warning

    This action 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. 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 their history, which 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 oc adm prune images command, then your registry is not secured and the oc adm 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
  • The recommended 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 oc adm prune images command, it means that your registry is secured using a certificate signed by a certificate authority other than the one used by oc adm 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 files is 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 from 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.

Additional resources

8.7. 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 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 kubeadmin or another privileged user that has access to the openshift-image-registry namespace.

  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. In configs.imageregistry.operator.openshift.io/cluster, set spec.readOnly to true:

      $ oc patch configs.imageregistry.operator.openshift.io/cluster -p '{"spec":{"readOnly":true}}' --type=merge
  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 openshift-image-registry \
          -o jsonpath='{.spec.template.spec.serviceAccountName}' deploy/image-registry)
    2. Add the system:image-pruner cluster role to the service account:

      $ oc adm policy add-cluster-role-to-user \
          system:image-pruner -z \
          ${service_account} -n openshift-image-registry
  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. The following example references an image registry Pod called image-registry-3-vhndw:

    $ oc -n openshift-image-registry exec pod/image-registry-3-vhndw -- /bin/sh -c '/usr/bin/dockerregistry -prune=check'

    Alternatively, to get the exact paths for the prune candidates, increase the logging level:

    $ oc -n openshift-image-registry exec pod/image-registry-3-vhndw -- /bin/sh -c 'REGISTRY_LOG_LEVEL=info /usr/bin/dockerregistry -prune=check'

    Example output

    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 image-registry Pod to run the hard prune. The following example references an image registry Pod called image-registry-3-vhndw:

    $ oc -n openshift-image-registry exec pod/image-registry-3-vhndw -- /bin/sh -c '/usr/bin/dockerregistry -prune=delete'

    Example output

    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. In configs.imageregistry.operator.openshift.io/cluster, set spec.readOnly to false:

    $ oc patch configs.imageregistry.operator.openshift.io/cluster -p '{"spec":{"readOnly":false}}' --type=merge

8.8. 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. Using the Red Hat Marketplace

The Red Hat Marketplace is an open cloud marketplace that makes it easy to discover and access certified software for container-based environments that run on public clouds and on-premises.

9.1. Red Hat Marketplace features

Cluster administrators can use the Red Hat Marketplace to manage software on OpenShift Container Platform, give developers self-service access to deploy application instances, and correlate application usage against a quota.

9.1.1. Connect OpenShift Container Platform clusters to the Marketplace

Cluster administrators can install a common set of applications on OpenShift Container Platform clusters that connect to the Marketplace. They can also use the Marketplace to track cluster usage against subscriptions or quotas. Users that they add by using the Marketplace have their product usage tracked and billed to their organization.

During the cluster connection process, a Marketplace Operator is installed that updates the image registry secret, manages the catalog, and reports application usage.

9.1.2. Install applications

Cluster administrators can install Marketplace applications from within OperatorHub in OpenShift Container Platform, or from the Marketplace web application.

You can access installed applications from the web console by clicking Operators > Installed Operators.

9.1.3. Deploy applications from different perspectives

You can deploy Marketplace applications from the web console’s Administrator and Developer perspectives.

The Developer perspective

Developers can access newly installed capabilities by using the Developer perspective.

For example, after a database Operator is installed, a developer can create an instance from the catalog within their project. Database usage is aggregated and reported to the cluster administrator.

This perspective does not include Operator installation and application usage tracking.

The Administrator perspective

Cluster administrators can access Operator installation and application usage information from the Administrator perspective.

They can also launch application instances by browsing custom resource definitions (CRDs) in the Installed Operators list.

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