Service Mesh

OpenShift Container Platform 4.4

Service Mesh installation, usage, and release notes

Red Hat OpenShift Documentation Team

Abstract

This document provides information on how to use Service Mesh in OpenShift Container Platform

Chapter 1. Service Mesh Release Notes

1.1. Red Hat OpenShift Service Mesh overview

Red Hat OpenShift Service Mesh is a platform that provides behavioral insight and operational control over the service mesh, providing a uniform way to connect, secure, and monitor microservice applications.

The term service mesh describes the network of microservices that make up applications in a distributed microservice architecture and the interactions between those microservices. As a service mesh grows in size and complexity, it can become harder to understand and manage.

Based on the open source Istio project, Red Hat OpenShift Service Mesh adds a transparent layer on existing distributed applications without requiring any changes to the service code. You add Red Hat OpenShift Service Mesh support to services by deploying a special sidecar proxy throughout your environment that intercepts all network communication between microservices. You configure and manage the service mesh using the control plane features.

Red Hat OpenShift Service Mesh provides an easy way to create a network of deployed services that provides discovery, load balancing, service-to-service authentication, failure recovery, metrics, and monitoring. A service mesh also provides more complex operational functionality, including A/B testing, canary releases, rate limiting, access control, and end-to-end authentication.

1.2. Getting support

If you experience difficulty with a procedure described in this documentation, visit the Red Hat Customer Portal. Through the Customer Portal, you can:

  • Search or browse through the Red Hat Knowledgebase of technical support articles about Red Hat products.
  • Submit a support case to Red Hat Support.

    Note

    When submitting a support case, it is recommended to provide the following information about your cluster to Red Hat Support to aid in troubleshooting:

    • Data gathered using the oc adm must-gather command
    • The unique cluster ID. Navigate to (?) HelpOpen Support Case to have the cluster ID autofilled when you submit the case.
  • Access other product documentation.

If you have a suggestion for improving this documentation or have found an error, please submit a Bugzilla report against the OpenShift Container Platform product for the Documentation component. Please provide specific details, such as the section name and OpenShift Container Platform version.

1.3. Red Hat OpenShift Service Mesh supported configurations

The following are the only supported configurations for the Red Hat OpenShift Service Mesh:

  • Red Hat OpenShift Container Platform version 4.x.
Note

OpenShift Online and OpenShift Dedicated are not supported for Red Hat OpenShift Service Mesh 1.1.2.

  • The deployment must be contained to a single OpenShift Container Platform cluster that is not federated.
  • This release of Red Hat OpenShift Service Mesh is only available on OpenShift Container Platform x86_64.
  • This release only supports configurations where all Service Mesh components are contained in the OpenShift cluster in which it operates. It does not support management of microservices that reside outside of the cluster, or in a multi-cluster scenario.
  • This release only supports configurations that do not integrate external services such as virtual machines.

1.3.1. Supported configurations for Kiali on Red Hat OpenShift Service Mesh

  • The Kiali observability console is only supported on the two most recent releases of the Chrome, Edge, Firefox, or Safari browsers.

1.3.2. Supported Mixer adapters

  • This release only supports the following Mixer adapter:

    • 3scale Istio Adapter

Red Hat OpenShift Service Mesh provides a number of key capabilities uniformly across a network of services:

  • Traffic Management - Control the flow of traffic and API calls between services, make calls more reliable, and make the network more robust in the face of adverse conditions.
  • Service Identity and Security - Provide services in the mesh with a verifiable identity and provide the ability to protect service traffic as it flows over networks of varying degrees of trustworthiness.
  • Policy Enforcement - Apply organizational policy to the interaction between services, ensure access policies are enforced and resources are fairly distributed among consumers. Policy changes are made by configuring the mesh, not by changing application code.
  • Telemetry - Gain understanding of the dependencies between services and the nature and flow of traffic between them, providing the ability to quickly identify issues.

1.3.3. Component versions included in Red Hat OpenShift Service Mesh version 1.1.2

ComponentVersion

Istio

1.4.6

Jaeger

1.17.1

Kiali

1.12.7

3scale Istio Adapter

1.0.0

1.3.4. New features Red Hat OpenShift Service Mesh 1.1.2

This release of Red Hat OpenShift Service Mesh addresses a security vulnerability.

1.3.5. New features Red Hat OpenShift Service Mesh 1.1.1

This release of Red Hat OpenShift Service Mesh adds support for a disconnected installation.

1.3.6. New features Red Hat OpenShift Service Mesh 1.1.0

This release of Red Hat OpenShift Service Mesh adds support for Istio 1.4.6 and Jaeger 1.17.1.

1.3.7. New features Red Hat OpenShift Service Mesh 1.0.10

This release of Red Hat OpenShift Service Mesh addresses Common Vulnerabilities and Exposures (CVEs).

1.3.8. New features Red Hat OpenShift Service Mesh 1.0.9

This release of Red Hat OpenShift Service Mesh addresses Common Vulnerabilities and Exposures (CVEs).

1.3.9. New features Red Hat OpenShift Service Mesh 1.0.8

This release of Red Hat OpenShift Service Mesh addresses compatibility issues with OpenShift Container Platform 4.4. You must upgrade Red Hat OpenShift Service Mesh to 1.0.8 before you upgrade from OpenShift Container Platform 4.3 to OpenShift Container Platform 4.4.

1.3.10. New features Red Hat OpenShift Service Mesh 1.0.7

This release of Red Hat OpenShift Service Mesh addresses Common Vulnerabilities and Exposures (CVEs).

1.3.11. New features Red Hat OpenShift Service Mesh 1.0.6

This release contains internal improvements.

1.3.12. New features Red Hat OpenShift Service Mesh 1.0.5

This release contains internal improvements.

1.3.13. New features Red Hat OpenShift Service Mesh 1.0.4

This release of Red Hat OpenShift Service Mesh adds support for Kiali 1.0.9, and addresses Common Vulnerabilities and Exposures (CVEs).

1.3.14. New features Red Hat OpenShift Service Mesh 1.0.3

This release of Red Hat OpenShift Service Mesh adds support for Kiali 1.0.8, and addresses Common Vulnerabilities and Exposures (CVEs).

1.3.15. New features Red Hat OpenShift Service Mesh 1.0.2

This release of Red Hat OpenShift Service Mesh adds support for Istio 1.1.17, Jaeger 1.13.1, Kiali 1.0.7, and the 3scale Istio Adapter 1.0 and OpenShift Container Platform 4.2.

1.3.16. New features Red Hat OpenShift Service Mesh 1.0.1

This release of Red Hat OpenShift Service Mesh adds support for Istio 1.1.11, Jaeger 1.13.1, Kiali 1.0.6, and the 3scale Istio Adapter 1.0 and OpenShift Container Platform 4.1.

1.3.17. New features Red Hat OpenShift Service Mesh 1.0

This release of Red Hat OpenShift Service Mesh adds support for Istio 1.1.11, Jaeger 1.13.1, Kiali 1.0.5, and the 3scale Istio Adapter 1.0 and OpenShift Container Platform 4.1.

Other notable changes in this release include the following:

  • The Kubernetes Container Network Interface (CNI) plug-in is always on.
  • The control plane is configured for multitenancy by default. Single tenant, cluster-wide control plane configurations are deprecated.
  • The Elasticsearch, Jaeger, Kiali, and Service Mesh Operators are installed from OperatorHub.
  • You can create and specify control plane templates.
  • Automatic route creation was removed from this release.

1.4. Known issues

These limitations exist in Red Hat OpenShift Service Mesh:

  • Red Hat OpenShift Service Mesh does not support IPv6, as it is not supported by the upstream Istio project, nor fully supported by OpenShift.
  • Graph layout - The layout for the Kiali graph can render differently, depending on your application architecture and the data to display (number of graph nodes and their interactions). Because it is difficult if not impossible to create a single layout that renders nicely for every situation, Kiali offers a choice of several different layouts. To choose a different layout, you can choose a different Layout Schema from the Graph Settings menu.

1.4.1. Service Mesh known issues

These are the known issues in Red Hat OpenShift Service Mesh:

  • Bug 1821432 Toggle controls in OpenShift Container Platform Control Resource details page do not update the CR correctly. UI Toggle controls in the Service Mesh Control Plane (SMCP) Overview page in the OpenShift Container Platform web console sometimes update the wrong field in the resource. To update a SMCP, edit the YAML content directly or update the resource from the command line instead of clicking the toggle controls.
  • Jaeger/Kiali Operator upgrade blocked with operator pending When upgrading the Jaeger or Kiali Operators with Service Mesh 1.0.x installed, the operator status shows as Pending. There is a solution in progress and a workaround. See the linked Knowledge Base article for more information.
  • Istio-14743 Due to limitations in the version of Istio that this release of Red Hat OpenShift Service Mesh is based on, there are several applications that are currently incompatible with Service Mesh. See the linked community issue for details.
  • MAISTRA-858 The following Envoy log messages describing deprecated options and configurations associated with Istio 1.1.x are expected:

    • [2019-06-03 07:03:28.943][19][warning][misc] [external/envoy/source/common/protobuf/utility.cc:129] Using deprecated option 'envoy.api.v2.listener.Filter.config'. This configuration will be removed from Envoy soon.
    • [2019-08-12 22:12:59.001][13][warning][misc] [external/envoy/source/common/protobuf/utility.cc:174] Using deprecated option 'envoy.api.v2.Listener.use_original_dst' from file lds.proto. This configuration will be removed from Envoy soon.
  • MAISTRA-681 and KIALI-2686 When the control plane has many namespaces, it can lead to performance issues.
  • MAISTRA-465 The Maistra operator fails to create a service for operator metrics.
  • MAISTRA-453 If you create a new project and deploy pods immediately, sidecar injection does not occur. The operator fails to add the maistra.io/member-of before the pods are created, therefore the pods must be deleted and recreated for sidecar injection to occur.
  • MAISTRA-193 Unexpected console info messages are visible when health checking is enabled for citadel.
  • MAISTRA-158 Applying multiple gateways referencing the same hostname will cause all gateways to stop functioning.
  • MAISTRA-806 Evicted Istio Operator Pod causes mesh and CNI not to deploy.

    If the istio-operator pod is evicted while deploying the control pane, delete the evicted istio-operator pod.

1.4.2. Kiali known issues

These are the known issues in Kiali:

  • KIALI-3262 In the Kiali console, when you click on Distributed Tracing in the navigation or on a Traces tab, you are asked to accept the certificate, and then asked to provide your OpenShift login credentials. This happens due to an issue with how the framework displays the Trace pages in the Console. The Workaround is to open the URL for the Jaeger console in another browser window and log in. Then you can view the embedded tracing pages in the Kiali console.
  • KIALI-3118 After changes to the ServiceMeshMemberRoll, for example adding or removing projects, the Kiali pod restarts and then displays errors on the Graph page while the Kiali pod is restarting.
  • KIALI-2206 When you are accessing the Kiali console for the first time, and there is no cached browser data for Kiali, the “View in Grafana” link on the Metrics tab of the Kiali Service Details page redirects to the wrong location. The only way you would encounter this issue is if you are accessing Kiali for the first time.
  • KIALI-507 Kiali does not support Internet Explorer 11. This is because the underlying frameworks do not support Internet Explorer. To access the Kiali console, use one of the two most recent versions of the Chrome, Edge, Firefox or Safari browser.

1.4.3. Jaeger known issues

These limitations exist in Jaeger:

  • While Kafka publisher is included as part of Jaeger, it is not supported.
  • Apache Spark is not supported.
  • Only self-provisioned Elasticsearch instances are supported. External Elasticsearch instances are not supported in this release.

These are the known issues in Jaeger:

  • TRACING-1166 It is not currently possible to use the Jaeger streaming strategy within a disconnected environment. When a Kafka cluster is being provisioned, it results in a error: Failed to pull image registry.redhat.io/amq7/amq-streams-kafka-24-rhel7@sha256:f9ceca004f1b7dccb3b82d9a8027961f9fe4104e0ed69752c0bdd8078b4a1076.
  • TRACING-809 Jaeger Ingester is incompatible with Kafka 2.3. When there are two or more instances of the Jaeger Ingester and enough traffic it will continuously generate rebalancing messages in the logs. This is due to a regression in Kafka 2.3 that was fixed in Kafka 2.3.1. For more information, see Jaegertracing-1819.

1.5. Fixed issues

The following issues been resolved in the current release:

1.5.1. Service Mesh fixed issues

  • OSSM-99 Workloads generated from direct Pod without labels may crash Kiali.
  • OSSM-93 IstioConfigList can’t filter by two or more names.
  • OSSM-92 Cancelling unsaved changes on the VS/DR YAML edit page does not cancel the changes.
  • OSSM-90 Traces not available on the service details page.
  • MAISTRA-1001 Closing HTTP/2 connections could lead to segmentation faults in istio-proxy.
  • MAISTRA-932 Added the requires metadata to add dependency relationship between Jaeger operator and Elasticsearch operator. Ensures that when the Jaeger operator is installed, it automatically deploys the Elasticsearch operator if it is not available.
  • MAISTRA-862 Galley dropped watches and stopped providing configuration to other components after many namespace deletions and re-creations.
  • MAISTRA-833 Pilot stopped delivering configuration after many namespace deletions and re-creations.
  • MAISTRA-684 The default Jaeger version in the istio-operator is 1.12.0, which does not match Jaeger version 1.13.1 that shipped in Red Hat OpenShift Service Mesh 0.12.TechPreview.
  • MAISTRA-622 In Maistra 0.12.0/TP12, permissive mode does not work. The user has the option to use Plain text mode or Mutual TLS mode, but not permissive.
  • MAISTRA-572 Jaeger cannot be used with Kiali. In this release Jaeger is configured to use the OAuth proxy, but is also only configured to work through a browser and does not allow service access. Kiali cannot properly communicate with the Jaeger endpoint and it considers Jaeger to be disabled. See also TRACING-591.
  • MAISTRA-357 In OpenShift 4 Beta on AWS, it is not possible, by default, to access a TCP or HTTPS service through the ingress gateway on a port other than port 80. The AWS load balancer has a health check that verifies if port 80 on the service endpoint is active. Without a service running on port 80, the load balancer health check fails.
  • MAISTRA-348 OpenShift 4 Beta on AWS does not support ingress gateway traffic on ports other than 80 or 443. If you configure your ingress gateway to handle TCP traffic with a port number other than 80 or 443, you have to use the service hostname provided by the AWS load balancer rather than the OpenShift router as a workaround.

1.5.2. Kiali fixed issues

  • KIALI-3239 If a Kiali Operator pod has failed with a status of “Evicted” it blocks the Kiali operator from deploying. The workaround is to delete the Evicted pod and redeploy the Kiali operator.
  • KIALI-3096 Runtime metrics fail in Service Mesh. There is an OAuth filter between the Service Mesh and Prometheus, requiring a bearer token to be passed to Prometheus before access will be granted. Kiali has been updated to use this token when communicating to the Prometheus server, but the application metrics are currently failing with 403 errors.
  • KIALI-3070 This bug only affects custom dashboards, not the default dashboards. When you select labels in metrics settings and refresh the page, your selections are retained in the menu but your selections are not displayed on the charts.

Chapter 2. Service Mesh architecture

2.1. Understanding Red Hat OpenShift Service Mesh

Red Hat OpenShift Service Mesh provides a platform for behavioral insight and operational control over your networked microservices in a service mesh. With Red Hat OpenShift Service Mesh, you can connect, secure, and monitor microservices in your OpenShift Container Platform environment.

2.1.1. Understanding service mesh

A service mesh is the network of microservices that make up applications in a distributed microservice architecture and the interactions between those microservices. When a Service Mesh grows in size and complexity, it can become harder to understand and manage.

Based on the open source Istio project, Red Hat OpenShift Service Mesh adds a transparent layer on existing distributed applications without requiring any changes to the service code. You add Red Hat OpenShift Service Mesh support to services by deploying a special sidecar proxy to relevant services in the mesh that intercepts all network communication between microservices. You configure and manage the Service Mesh using the control plane features.

Red Hat OpenShift Service Mesh gives you an easy way to create a network of deployed services that provide:

  • Discovery
  • Load balancing
  • Service-to-service authentication
  • Failure recovery
  • Metrics
  • Monitoring

Red Hat OpenShift Service Mesh also provides more complex operational functions including:

  • A/B testing
  • Canary releases
  • Rate limiting
  • Access control
  • End-to-end authentication

2.1.2. Red Hat OpenShift Service Mesh Architecture

Red Hat OpenShift Service Mesh is logically split into a data plane and a control plane:

The data plane is a set of intelligent proxies deployed as sidecars. These proxies intercept and control all inbound and outbound network communication between microservices in the service mesh. Sidecar proxies also communicate with Mixer, the general-purpose policy and telemetry hub.

  • Envoy proxy intercepts all inbound and outbound traffic for all services in the service mesh. Envoy is deployed as a sidecar to the relevant service in the same pod.

The control plane manages and configures proxies to route traffic, and configures Mixers to enforce policies and collect telemetry.

  • Mixer enforces access control and usage policies (such as authorization, rate limits, quotas, authentication, and request tracing) and collects telemetry data from the Envoy proxy and other services.
  • Pilot configures the proxies at runtime. Pilot provides service discovery for the Envoy sidecars, traffic management capabilities for intelligent routing (for example, A/B tests or canary deployments), and resiliency (timeouts, retries, and circuit breakers).
  • Citadel issues and rotates certificates. Citadel provides strong service-to-service and end-user authentication with built-in identity and credential management. You can use Citadel to upgrade unencrypted traffic in the service mesh. Operators can enforce policies based on service identity rather than on network controls using Citadel.
  • Galley ingests the service mesh configuration, then validates, processes, and distributes the configuration. Galley protects the other service mesh components from obtaining user configuration details from OpenShift Container Platform.

Red Hat OpenShift Service Mesh also uses the istio-operator to manage the installation of the control plane. An Operator is a piece of software that enables you to implement and automate common activities in your OpenShift cluster. It acts as a controller, allowing you to set or change the desired state of objects in your cluster.

2.1.3. Red Hat OpenShift Service Mesh control plane

Red Hat OpenShift Service Mesh installs a multi-tenant control plane by default. You specify the projects that can access the Service Mesh, and isolate the Service Mesh from other control plane instances.

2.1.4. Multi-tenancy in Red Hat OpenShift Service Mesh versus cluster-wide installations

The main difference between a multi-tenant installation and a cluster-wide installation is the scope of privileges used by the control plane deployments, for example, Galley and Pilot. The components no longer use cluster-scoped Role Based Access Control (RBAC) resource ClusterRoleBinding, but rely on project-scoped RoleBinding.

Every project in the members list will have a RoleBinding for each service account associated with a control plane deployment and each control plane deployment will only watch those member projects. Each member project has a maistra.io/member-of label added to it, where the member-of value is the project containing the control plane installation.

Red Hat OpenShift Service Mesh configures each member project to ensure network access between itself, the control plane, and other member projects. The exact configuration differs depending on how OpenShift software-defined networking (SDN) is configured. See About OpenShift SDN for additional details.

If the OpenShift Container Platform cluster is configured to use the SDN plug-in:

  • NetworkPolicy: Red Hat OpenShift Service Mesh creates a NetworkPolicy resource in each member project allowing ingress to all pods from the other members and the control plane. If you remove a member from Service Mesh, this NetworkPolicy resource is deleted from the project.

    Note

    This also restricts ingress to only member projects. If ingress from non-member projects is required, you need to create a NetworkPolicy to allow that traffic through.

  • Multitenant: Red Hat OpenShift Service Mesh joins the NetNamespace for each member project to the NetNamespace of the control plane project (the equivalent of running oc adm pod-network join-projects --to control-plane-project member-project). If you remove a member from the Service Mesh, its NetNamespace is isolated from the control plane (the equivalent of running oc adm pod-network isolate-projects member-project).
  • Subnet: No additional configuration is performed.

2.1.5. Automatic injection

The upstream Istio community installation automatically injects the sidecar into pods within the projects you have labeled.

Red Hat OpenShift Service Mesh does not automatically inject the sidecar to any pods, but requires you to specify the sidecar.istio.io/inject annotation as illustrated in the Automatic sidecar injection section.

2.1.6. Istio Role Based Access Control features

Istio Role Based Access Control (RBAC) provides a mechanism you can use to control access to a service. You can identify subjects by user name or by specifying a set of properties and apply access controls accordingly.

The upstream Istio community installation includes options to perform exact header matches, match wildcards in headers, or check for a header containing a specific prefix or suffix.

Red Hat OpenShift Service Mesh extends the ability to match request headers by using a regular expression. Specify a property key of request.regex.headers with a regular expression.

Upstream Istio community matching request headers example

apiVersion: "rbac.istio.io/v1alpha1"
kind: ServiceRoleBinding
metadata:
  name: httpbin-client-binding
  namespace: httpbin
spec:
  subjects:
  - user: "cluster.local/ns/istio-system/sa/istio-ingressgateway-service-account"
    properties:
      request.headers[<header>]: "value"

Red Hat OpenShift Service Mesh matching request headers by using regular expressions

apiVersion: "rbac.istio.io/v1alpha1"
kind: ServiceRoleBinding
metadata:
  name: httpbin-client-binding
  namespace: httpbin
spec:
  subjects:
  - user: "cluster.local/ns/istio-system/sa/istio-ingressgateway-service-account"
    properties:
      request.regex.headers[<header>]: "<regular expression>"

2.1.7. OpenSSL

Red Hat OpenShift Service Mesh replaces BoringSSL with OpenSSL. OpenSSL is a software library that contains an open source implementation of the Secure Sockets Layer (SSL) and Transport Layer Security (TLS) protocols. The Red Hat OpenShift Service Mesh Proxy binary dynamically links the OpenSSL libraries (libssl and libcrypto) from the underlying Red Hat Enterprise Linux operating system.

2.1.8. The Istio Container Network Interface (CNI) plug-in

Red Hat OpenShift Service Mesh includes CNI plug-in, which provides you with an alternate way to configure application pod networking. The CNI plug-in replaces the init-container network configuration eliminating the need to grant service accounts and projects access to Security Context Constraints (SCCs) with elevated privileges.

2.1.9. Envoy, Secret Discovery Service, and Certificates

  • Red Hat OpenShift Service Mesh does not support QUIC-based services.
  • Deployment of TLS certificates using the Secret Discovery Service (SDS) functionality of Istio is not currently supported in Red Hat OpenShift Service Mesh. The Istio implementation depends on a nodeagent container that uses hostPath mounts.

Next steps

2.2. Kiali overview

Kiali provides visibility into your service mesh by showing you the microservices in your service mesh, and how they are connected.

2.2.1. Kiali overview

Kiali provides observability into the Service Mesh running on OpenShift Container Platform. Kiali helps you define, validate, and observe your Istio service mesh. It helps you to understand the structure of your service mesh by inferring the topology, and also provides information about the health of your service mesh.

Kiali provides an interactive graph view of your namespace in real time that provides visibility into features like circuit breakers, request rates, latency, and even graphs of traffic flows. Kiali offers insights about components at different levels, from Applications to Services and Workloads, and can display the interactions with contextual information and charts on the selected graph node or edge. Kiali also provides the ability to validate your Istio configurations, such as gateways, destination rules, virtual services, mesh policies, and more. Kiali provides detailed metrics, and a basic Grafana integration is available for advanced queries. Distributed tracing is provided by integrating Jaeger into the Kiali console.

Kiali is installed by default as part of the Red Hat OpenShift Service Mesh.

2.2.2. Kiali architecture

Kiali is composed of two components: the Kiali application and the Kiali console.

  • Kiali application (back end) – This component runs in the container application platform and communicates with the service mesh components, retrieves and processes data, and exposes this data to the console. The Kiali application does not need storage. When deploying the application to a cluster, configurations are set in ConfigMaps and secrets.
  • Kiali console (front end) – The Kiali console is a web application. The Kiali application serves the Kiali console, which then queries the back end for data in order to present it to the user.

In addition, Kiali depends on external services and components provided by the container application platform and Istio.

  • Red Hat Service Mesh (Istio) - Istio is a Kiali requirement. Istio is the component that provides and controls the service mesh. Although Kiali and Istio can be installed separately, Kiali depends on Istio and will not work if it is not present. Kiali needs to retrieve Istio data and configurations, which are exposed through Prometheus and the cluster API.
  • Prometheus - A dedicated Prometheus instance is included as part of the Red Hat OpenShift Service Mesh installation. When Istio telemetry is enabled, metrics data is stored in Prometheus. Kiali uses this Prometheus data to determine the mesh topology, display metrics, calculate health, show possible problems, and so on. Kiali communicates directly with Prometheus and assumes the data schema used by Istio Telemetery. Prometheus is an Istio dependency and a hard dependency for Kiali, and many of Kiali’s features will not work without Prometheus.
  • Cluster API - Kiali uses the API of the OpenShift Container Platform (cluster API) in order to fetch and resolve service mesh configurations. Kiali queries the cluster API to retrieve, for example, definitions for namespaces, services, deployments, pods, and other entities. Kiali also makes queries to resolve relationships between the different cluster entities. The cluster API is also queried to retrieve Istio configurations like virtual services, destination rules, route rules, gateways, quotas, and so on.
  • Jaeger - Jaeger is optional, but is installed by default as part of the Red Hat OpenShift Service Mesh installation. When you install Jaeger as part of the default Red Hat OpenShift Service Mesh installation, the Kiali console includes a tab to display Jaeger’s tracing data. Note that tracing data will not be available if you disable Istio’s distributed tracing feature. Also note that user must have access to the namespace where the control plane is installed in order to view Jaeger data.
  • Grafana - Grafana is optional, but is installed by default as part of the Red Hat OpenShift Service Mesh installation. When available, the metrics pages of Kiali display links to direct the user to the same metric in Grafana. Note that user must have access to the namespace where the control plane is installed in order to view links to the Grafana dashboard and view Grafana data.

2.2.3. Kiali features

The Kiali console is integrated with Red Hat Service Mesh and provides the following capabilities:

  • Health – Quickly identify issues with applications, services, or workloads.
  • Topology – Visualize how your applications, services, or workloads communicate via the Kiali graph.
  • Metrics – Predefined metrics dashboards let you chart service mesh and application performance for Go, Node.js. Quarkus, Spring Boot, Thorntail and Vert.x. You can also create your own custom dashboards.
  • Tracing – Integration with Jaeger lets you follow the path of a request through various microservices that make up an application.
  • Validations – Perform advanced validations on the most common Istio objects (Destination Rules, Service Entries, Virtual Services, and so on).
  • Configuration – Optional ability to create, update and delete Istio routing configuration using wizards or directly in the YAML editor in the Kiali Console.

2.3. Understanding Jaeger

Every time a user takes an action in an application, a request is executed by the architecture that may require dozens of different services to participate in order to produce a response. The path of this request is a distributed transaction. Jaeger lets you perform distributed tracing, which follows the path of a request through various microservices that make up an application.

Distributed tracing is a technique that is used to tie the information about different units of work together—usually executed in different processes or hosts—in order to understand a whole chain of events in a distributed transaction. Distributed tracing lets developers visualize call flows in large service oriented architectures. It can be invaluable in understanding serialization, parallelism, and sources of latency.

Jaeger records the execution of individual requests across the whole stack of microservices, and presents them as traces. A trace is a data/execution path through the system. An end-to-end trace is comprised of one or more spans.

A span represents a logical unit of work in Jaeger that has an operation name, the start time of the operation, and the duration. Spans may be nested and ordered to model causal relationships.

2.3.1. Jaeger overview

As a service owner, you can use Jaeger to instrument your services to gather insights into your service architecture. Jaeger is an open source distributed tracing platform that you can use for monitoring, network profiling, and troubleshooting the interaction between components in modern, cloud-native, microservices-based applications.

Using Jaeger lets you perform the following functions:

  • Monitor distributed transactions
  • Optimize performance and latency
  • Perform root cause analysis

Jaeger is based on the vendor-neutral OpenTracing APIs and instrumentation.

2.3.2. Jaeger architecture

Jaeger is made up of several components that work together to collect, store, and display tracing data.

  • Jaeger Client (Tracer, Reporter, instrumented application, client libraries)- Jaeger clients are language specific implementations of the OpenTracing API. They can be used to instrument applications for distributed tracing either manually or with a variety of existing open source frameworks, such as Camel (Fuse), Spring Boot (RHOAR), MicroProfile (RHOAR/Thorntail), Wildfly (EAP), and many more, that are already integrated with OpenTracing.
  • Jaeger Agent (Server Queue, Processor Workers) - The Jaeger agent is a network daemon that listens for spans sent over User Datagram Protocol (UDP), which it batches and sends to the collector. The agent is meant to be placed on the same host as the instrumented application. This is typically accomplished by having a sidecar in container environments like Kubernetes.
  • Jaeger Collector (Queue, Workers) - Similar to the Agent, the Collector is able to receive spans and place them in an internal queue for processing. This allows the collector to return immediately to the client/agent instead of waiting for the span to make its way to the storage.
  • Storage (Data Store) - Collectors require a persistent storage backend. Jaeger has a pluggable mechanism for span storage. Note that for this release, the only supported storage is Elasticsearch.
  • Query (Query Service) - Query is a service that retrieves traces from storage.
  • Ingester (Ingester Service) - Jaeger can use Apache Kafka as a buffer between the collector and the actual backing storage (Elasticsearch). Ingester is a service that reads data from Kafka and writes to another storage backend (Elasticsearch).
  • Jaeger Console – Jaeger provides a user interface that lets you visualize your distributed tracing data. On the Search page, you can find traces and explore details of the spans that make up an individual trace.

2.3.3. Jaeger features

Jaeger tracing provides the following capabilities:

  • Integration with Kiali – When properly configured, you can view Jaeger data from the Kiali console.
  • High scalability – The Jaeger backend is designed to have no single points of failure and to scale with the business needs.
  • Distributed Context Propagation – Lets you connect data from different components together to create a complete end-to-end trace.
  • Backwards compatibility with Zipkin – Jaeger provides backwards compatibility with Zipkin by accepting spans in Zipkin formats (Thrift or JSON v1/v2) over HTTP.

2.4. Comparing Service Mesh and Istio

An installation of Red Hat OpenShift Service Mesh differs from upstream Istio community installations in multiple ways. The modifications to Red Hat OpenShift Service Mesh are sometimes necessary to resolve issues, provide additional features, or to handle differences when deploying on OpenShift Container Platform.

The current release of Red Hat OpenShift Service Mesh differs from the current upstream Istio community release in the following ways:

2.4.1. Red Hat OpenShift Service Mesh control plane

Red Hat OpenShift Service Mesh installs a multi-tenant control plane by default. You specify the projects that can access the Service Mesh, and isolate the Service Mesh from other control plane instances.

2.4.2. Multi-tenancy in Red Hat OpenShift Service Mesh versus cluster-wide installations

The main difference between a multi-tenant installation and a cluster-wide installation is the scope of privileges used by the control plane deployments, for example, Galley and Pilot. The components no longer use cluster-scoped Role Based Access Control (RBAC) resource ClusterRoleBinding, but rely on project-scoped RoleBinding.

Every project in the members list will have a RoleBinding for each service account associated with a control plane deployment and each control plane deployment will only watch those member projects. Each member project has a maistra.io/member-of label added to it, where the member-of value is the project containing the control plane installation.

Red Hat OpenShift Service Mesh configures each member project to ensure network access between itself, the control plane, and other member projects. The exact configuration differs depending on how OpenShift software-defined networking (SDN) is configured. See About OpenShift SDN for additional details.

If the OpenShift Container Platform cluster is configured to use the SDN plug-in:

  • NetworkPolicy: Red Hat OpenShift Service Mesh creates a NetworkPolicy resource in each member project allowing ingress to all pods from the other members and the control plane. If you remove a member from Service Mesh, this NetworkPolicy resource is deleted from the project.

    Note

    This also restricts ingress to only member projects. If ingress from non-member projects is required, you need to create a NetworkPolicy to allow that traffic through.

  • Multitenant: Red Hat OpenShift Service Mesh joins the NetNamespace for each member project to the NetNamespace of the control plane project (the equivalent of running oc adm pod-network join-projects --to control-plane-project member-project). If you remove a member from the Service Mesh, its NetNamespace is isolated from the control plane (the equivalent of running oc adm pod-network isolate-projects member-project).
  • Subnet: No additional configuration is performed.

2.4.3. Automatic injection

The upstream Istio community installation automatically injects the sidecar into pods within the projects you have labeled.

Red Hat OpenShift Service Mesh does not automatically inject the sidecar to any pods, but requires you to specify the sidecar.istio.io/inject annotation as illustrated in the Automatic sidecar injection section.

2.4.4. Istio Role Based Access Control features

Istio Role Based Access Control (RBAC) provides a mechanism you can use to control access to a service. You can identify subjects by user name or by specifying a set of properties and apply access controls accordingly.

The upstream Istio community installation includes options to perform exact header matches, match wildcards in headers, or check for a header containing a specific prefix or suffix.

Red Hat OpenShift Service Mesh extends the ability to match request headers by using a regular expression. Specify a property key of request.regex.headers with a regular expression.

Upstream Istio community matching request headers example

apiVersion: "rbac.istio.io/v1alpha1"
kind: ServiceRoleBinding
metadata:
  name: httpbin-client-binding
  namespace: httpbin
spec:
  subjects:
  - user: "cluster.local/ns/istio-system/sa/istio-ingressgateway-service-account"
    properties:
      request.headers[<header>]: "value"

Red Hat OpenShift Service Mesh matching request headers by using regular expressions

apiVersion: "rbac.istio.io/v1alpha1"
kind: ServiceRoleBinding
metadata:
  name: httpbin-client-binding
  namespace: httpbin
spec:
  subjects:
  - user: "cluster.local/ns/istio-system/sa/istio-ingressgateway-service-account"
    properties:
      request.regex.headers[<header>]: "<regular expression>"

2.4.5. OpenSSL

Red Hat OpenShift Service Mesh replaces BoringSSL with OpenSSL. OpenSSL is a software library that contains an open source implementation of the Secure Sockets Layer (SSL) and Transport Layer Security (TLS) protocols. The Red Hat OpenShift Service Mesh Proxy binary dynamically links the OpenSSL libraries (libssl and libcrypto) from the underlying Red Hat Enterprise Linux operating system.

2.4.6. The Istio Container Network Interface (CNI) plug-in

Red Hat OpenShift Service Mesh includes CNI plug-in, which provides you with an alternate way to configure application pod networking. The CNI plug-in replaces the init-container network configuration eliminating the need to grant service accounts and projects access to Security Context Constraints (SCCs) with elevated privileges.

2.4.7. Envoy, Secret Discovery Service, and Certificates

  • Red Hat OpenShift Service Mesh does not support QUIC-based services.
  • Deployment of TLS certificates using the Secret Discovery Service (SDS) functionality of Istio is not currently supported in Red Hat OpenShift Service Mesh. The Istio implementation depends on a nodeagent container that uses hostPath mounts.

2.4.8. Kiali and service mesh

Installing Kiali via the Service Mesh on OpenShift Container Platform differs from community Kiali installations in multiple ways. These modifications are sometimes necessary to resolve issues, provide additional features, or to handle differences when deploying on OpenShift Container Platform.

  • Kiali has been enabled by default.
  • Ingress has been enabled by default.
  • Updates have been made to the Kiali ConfigMap.
  • Updates have been made to the ClusterRole settings for Kiali.
  • Users should not manually edit the ConfigMap or the Kiali custom resource files as those changes might be overwritten by the Service Mesh or Kiali operators. All configuration for Kiali running on Red Hat OpenShift Service Mesh is done in the ServiceMeshControlPlane custom resource file and there are limited configuration options. Updating the operator files should be restricted to those users with cluster-admin privileges.

2.4.9. Jaeger and service mesh

Installing Jaeger with the Service Mesh on OpenShift Container Platform differs from community Jaeger installations in multiple ways. These modifications are sometimes necessary to resolve issues, provide additional features, or to handle differences when deploying on OpenShift Container Platform.

  • Jaeger has been enabled by default for Service Mesh.
  • Ingress has been enabled by default for Service Mesh.
  • The name for the Zipkin port name has changed to jaeger-collector-zipkin (from http)
  • Jaeger uses Elasticsearch for storage by default.
  • The community version of Istio provides a generic "tracing" route. Red Hat OpenShift Service Mesh uses a "jaeger" route that is installed by the Jaeger operator and is already protected by OAuth.
  • Red Hat OpenShift Service Mesh uses a sidecar for the Envoy proxy, and Jaeger also uses a sidecar, for the Jaeger agent. These two sidecars are configured separately and should not be confused with each other. The proxy sidecar creates spans related to the pod’s ingress and egress traffic. The agent sidecar receives the spans emitted by the application and sends them to the Jaeger Collector.

Chapter 3. Service Mesh installation

3.1. Preparing to install Red Hat OpenShift Service Mesh

Before you can install Red Hat OpenShift Service Mesh, review the installation activities, ensure that you meet the prerequisites:

Prerequisites

3.1.1. Red Hat OpenShift Service Mesh supported configurations

The following are the only supported configurations for the Red Hat OpenShift Service Mesh:

  • Red Hat OpenShift Container Platform version 4.x.
Note

OpenShift Online and OpenShift Dedicated are not supported for Red Hat OpenShift Service Mesh 1.1.2.

  • The deployment must be contained to a single OpenShift Container Platform cluster that is not federated.
  • This release of Red Hat OpenShift Service Mesh is only available on OpenShift Container Platform x86_64.
  • This release only supports configurations where all Service Mesh components are contained in the OpenShift cluster in which it operates. It does not support management of microservices that reside outside of the cluster, or in a multi-cluster scenario.
  • This release only supports configurations that do not integrate external services such as virtual machines.

3.1.1.1. Supported configurations for Kiali on Red Hat OpenShift Service Mesh

  • The Kiali observability console is only supported on the two most recent releases of the Chrome, Edge, Firefox, or Safari browsers.

3.1.1.2. Supported Mixer adapters

  • This release only supports the following Mixer adapter:

    • 3scale Istio Adapter

3.1.2. Red Hat OpenShift Service Mesh installation activities

To install the Red Hat OpenShift Service Mesh Operator, you must first install these Operators:

  • Elasticsearch - Based on the open source Elasticsearch project that enables you to configure and manage an Elasticsearch cluster for tracing and logging with Jaeger.
  • Jaeger - based on the open source Jaeger project, lets you perform tracing to monitor and troubleshoot transactions in complex distributed systems.
  • Kiali - based on the open source Kiali project, provides observability for your service mesh. By using Kiali you can view configurations, monitor traffic, and view and analyze traces in a single console.

After you install the Elasticsearch, Jaeger, and Kiali Operators, then you install the Red Hat OpenShift Service Mesh Operator. The Service Mesh Operator defines and monitors the ServiceMeshControlPlane resources that manage the deployment, updating, and deletion of the Service Mesh components.

  • Red Hat OpenShift Service Mesh - based on the open source Istio project, lets you connect, secure, control, and observe the microservices that make up your applications.
Warning

Please see configuring Elasticsearch for details on configuring the default Jaeger parameters for Elasticsearch in a production environment.

Next steps

3.2. Installing Red Hat OpenShift Service Mesh

Installing the Service Mesh involves installing the Elasticsearch, Jaeger, Kiali and Service Mesh Operators, creating and managing a ServiceMeshControlPlane resource to deploy the control plane, and creating a ServiceMeshMemberRoll resource to specify the namespaces associated with the Service Mesh.

Note

Mixer’s policy enforcement is disabled by default. You must enable it to run policy tasks. See Update Mixer policy enforcement for instructions on enabling Mixer policy enforcement.

Note

Multi-tenant control plane installations are the default configuration starting with Red Hat OpenShift Service Mesh 1.0.

Note

The Service Mesh documentation uses istio-system as the example project, but you may deploy the service mesh to any project.

Prerequisites

3.2.1. Installing the Operators from OperatorHub

The Service Mesh installation process uses the OperatorHub to install the ServiceMeshControlPlane custom resource definition within the openshift-operators project. The Red Hat OpenShift Service Mesh defines and monitors the ServiceMeshControlPlane related to the deployment, update, and deletion of the control plane.

Starting with Red Hat OpenShift Service Mesh 1.1.2, you must install the Elasticsearch Operator, the Jaeger Operator, and the Kiali Operator before the Red Hat OpenShift Service Mesh Operator can install the control plane.

3.2.1.1. Installing the Elasticsearch Operator

You must install the Elasticsearch Operator for the Red Hat OpenShift Service Mesh Operator to install the control plane.

Warning

Do not install Community versions of the Operators. Community Operators are not supported.

Prerequisites

  • Access to the OpenShift Container Platform web console.

Procedure

  1. Log in to the OpenShift Container Platform web console.
  2. Navigate to OperatorsOperatorHub.
  3. Type Elasticsearch into the filter box to locate the Elasticsearch Operator.
  4. Click the Elasticsearch Operator to display information about the Operator.
  5. Click Install.
  6. On the Create Operator Subscription page, select All namespaces on the cluster (default). This installs the Operator in the default openshift-operators project and makes the Operator available to all projects in the cluster.
  7. In the Update Channel, select the most current version.
  8. Select the Automatic Approval Strategy.

    Note

    The Manual approval strategy requires a user with appropriate credentials to approve the Operator install and subscription process.

  9. Click Subscribe.
  10. The Installed Operators page displays the Elasticsearch Operator’s installation progress.

3.2.1.2. Installing the Jaeger Operator

You must install the Jaeger Operator for the Red Hat OpenShift Service Mesh Operator to install the control plane.

Warning

Do not install Community versions of the Operators. Community Operators are not supported.

Prerequisites

  • Access to the OpenShift Container Platform web console.
  • The Elasticsearch Operator must be installed.

Procedure

  1. Log in to the OpenShift Container Platform web console.
  2. Navigate to OperatorsOperatorHub.
  3. Type Jaeger into the filter box to locate the Jaeger Operator.
  4. Click the Jaeger Operator provided by Red Hat to display information about the Operator.
  5. Click Install.
  6. On the Create Operator Subscription page, select All namespaces on the cluster (default). This installs the Operator in the default openshift-operators project and makes the Operator available to all projects in the cluster.
  7. Select the stable Update Channel.
  8. Select the Automatic Approval Strategy.

    Note

    The Manual approval strategy requires a user with appropriate credentials to approve the Operator install and subscription process.

  9. Click Subscribe.
  10. The Installed Operators page displays the Jaeger Operator’s installation progress.

3.2.1.3. Installing the Kiali Operator

You must install the Kiali Operator for the Red Hat OpenShift Service Mesh Operator to install the control plane.

Warning

Do not install Community versions of the Operators. Community Operators are not supported.

Prerequisites

  • Access to the OpenShift Container Platform web console.

Procedure

  1. Log in to the OpenShift Container Platform web console.
  2. Navigate to OperatorsOperatorHub.
  3. Type Kiali into the filter box to find the Kiali Operator.
  4. Click the Kiali Operator provided by Red Hat to display information about the Operator.
  5. Click Install.
  6. On the Create Operator Subscription page, select All namespaces on the cluster (default). This installs the Operator in the default openshift-operators project and makes the Operator available to all projects in the cluster.
  7. Select the stable Update Channel.
  8. Select the Automatic Approval Strategy.

    Note

    The Manual approval strategy requires a user with appropriate credentials to approve the Operator install and subscription process.

  9. Click Subscribe.
  10. The Installed Operators page displays the Kiali Operator’s installation progress.

3.2.1.4. Installing the Red Hat OpenShift Service Mesh Operator

Prerequisites

  • Access to the OpenShift Container Platform web console.
  • The Elasticsearch Operator must be installed.
  • The Jaeger Operator must be installed.
  • The Kiali Operator must be installed.

Procedure

  1. Log in to the OpenShift Container Platform web console.
  2. Navigate to OperatorsOperatorHub.
  3. Type Red Hat OpenShift Service Mesh into the filter box to find the Red Hat OpenShift Service Mesh Operator.
  4. Click the Red Hat OpenShift Service Mesh Operator to display information about the Operator.
  5. On the Create Operator Subscription page, select All namespaces on the cluster (default). This installs the Operator in the default openshift-operators project and makes the Operator available to all projects in the cluster.
  6. Click Install.
  7. Select the stable Update Channel.
  8. Select the Automatic Approval Strategy.

    Note

    The Manual approval strategy requires a user with appropriate credentials to approve the Operator install and subscription process.

  9. Click Subscribe.
  10. The Installed Operators page displays the Red Hat OpenShift Service Mesh Operator’s installation progress.

3.2.1.5. Deploying the Red Hat OpenShift Service Mesh control plane

The ServiceMeshControlPlane resource defines the configuration to be used during installation. You can deploy the default configuration provided by Red Hat or customize the ServiceMeshControlPlane file to fit your business needs.

You can deploy the Service Mesh control plane by using the OpenShift Container Platform web console or from the command line using the oc client tool.

3.2.1.5.1. Deploying the control plane from the web console

Follow this procedure to deploy the Red Hat OpenShift Service Mesh control plane by using the web console.

Prerequisites

  • The Red Hat OpenShift Service Mesh Operator must be installed.
  • Review the instructions for how to customize the Red Hat OpenShift Service Mesh installation.
  • An account with the cluster-admin role.

Procedure

  1. Log in to the OpenShift Container Platform web console as a user with the cluster-admin role.
  2. Create a project named istio-system.

    1. Navigate to HomeProjects.
    2. Click Create Project.
    3. Enter istio-system in the Name field.
    4. Click Create.
  3. Navigate to OperatorsInstalled Operators.
  4. If necessary, select istio-system from the Project menu. You may have to wait a few moments for the Operators to be copied to the new project.
  5. Click the Red Hat OpenShift Service Mesh Operator. Under Provided APIs, the Operator provides links to create two resource types:

    • A ServiceMeshControlPlane resource
    • A ServiceMeshMemberRoll resource
  6. Under Istio Service Mesh Control Plane click Create ServiceMeshControlPlane.
  7. On the Create Service Mesh Control Plane page, modify the YAML for the default ServiceMeshControlPlane template as needed.

    Note

    For additional information about customizing the control plane, see customizing the Red Hat OpenShift Service Mesh installation. For production, you must change the default Jaeger template.

  8. Click Create to create the control plane. The Operator creates Pods, services, and Service Mesh control plane components based on your configuration parameters.
  9. Click the Istio Service Mesh Control Plane tab.
  10. Click the name of the new control plane.
  11. Click the Resources tab to see the Red Hat OpenShift Service Mesh control plane resources the Operator created and configured.
3.2.1.5.2. Deploying the control plane from the CLI

Follow this procedure to deploy the Red Hat OpenShift Service Mesh control plane the command line.

Prerequisites

  • The Red Hat OpenShift Service Mesh Operator must be installed.
  • Review the instructions for how to customize the Red Hat OpenShift Service Mesh installation.
  • An account with the cluster-admin role.
  • Access to the OpenShift Container Platform Command-line Interface (CLI), commonly known as oc.

Procedure

  1. Log in to the OpenShift Container Platform CLI as a user with the cluster-admin role.

    $ oc login https://{HOSTNAME}:6443
  2. Create a project named istio-system.

    $ oc new-project istio-system
  3. Create a ServiceMeshControlPlane file named istio-installation.yaml using the full example found in "Customize the Red Hat OpenShift Service Mesh installation". You can customize the values as needed to match your use case. For production, you must change the default Jaeger template.
  4. Run the following command to deploy the control plane:

    $ oc create -n istio-system -f istio-installation.yaml
  5. Execute the following command to see the status of the control plane installation.

    $ oc get smcp -n istio-system

    The installation has finished successfully when the READY column is true.

    NAME           READY
    basic-install   True
  6. Run the following command to watch the progress of the Pods during the installation process:

    $ oc get pods -n istio-system -w

    You should see output similar to the following:

    NAME                                     READY   STATUS             RESTARTS   AGE
    grafana-7bf5764d9d-2b2f6                 2/2     Running            0          28h
    istio-citadel-576b9c5bbd-z84z4           1/1     Running            0          28h
    istio-egressgateway-5476bc4656-r4zdv     1/1     Running            0          28h
    istio-galley-7d57b47bb7-lqdxv            1/1     Running            0          28h
    istio-ingressgateway-dbb8f7f46-ct6n5     1/1     Running            0          28h
    istio-pilot-546bf69578-ccg5x             2/2     Running            0          28h
    istio-policy-77fd498655-7pvjw            2/2     Running            0          28h
    istio-sidecar-injector-df45bd899-ctxdt   1/1     Running            0          28h
    istio-telemetry-66f697d6d5-cj28l         2/2     Running            0          28h
    jaeger-896945cbc-7lqrr                   2/2     Running            0          11h
    kiali-78d9c5b87c-snjzh                   0/1     Running            0          22h
    prometheus-6dff867c97-gr2n5              2/2     Running            0          28h

For a multitenant installation, Red Hat OpenShift Service Mesh supports multiple independent control planes within the cluster. You can create reusable configurations with ServiceMeshControlPlane templates. For more information, see Creating control plane templates.

3.2.1.6. Creating the Red Hat OpenShift Service Mesh member roll

The ServiceMeshMemberRoll lists the projects belonging to the control plane. Only projects listed in the ServiceMeshMemberRoll are affected by the control plane. A project does not belong to a service mesh until you add it to the member roll for a particular control plane deployment.

You must create a ServiceMeshMemberRoll resource named default in the same project as the ServiceMeshControlPlane.

Note

The member projects are only updated if the Service Mesh control plane installation succeeds.

3.2.1.6.1. Creating the member roll from the web console

Follow this procedure to add one or more projects to the Service Mesh member roll by using the web console.

Prerequisites

  • An installed, verified Red Hat OpenShift Service Mesh Operator.
  • Location of the installed ServiceMeshControlPlane.
  • List of existing projects to add to the service mesh.

Procedure

  1. If you don’t already have projects for your mesh, or you are starting from scratch, create a project. It must be different from istio-system.

    1. Navigate to HomeProjects.
    2. Enter a name in the Name field.
    3. Click Create.
  2. Log in to the OpenShift Container Platform web console.
  3. Navigate to OperatorsInstalled Operators.
  4. Click the Project menu and choose the project where your ServiceMeshControlPlane is deployed from the list, for example istio-system.
  5. Click the Red Hat OpenShift Service Mesh Operator.
  6. Click the All Instances tab.
  7. Click Create New, and then select Create Istio Service Mesh Member Roll.

    Note

    It can take a short time for the Operator to finish copying the resources, therefore you may need to refresh the screen to see the Create Istio Service Mesh Member Roll button.

  8. On the Create Service Mesh Member Roll page, modify the YAML to add your projects as members. You can add any number of projects, but a project can only belong to one ServiceMeshMemberRoll resource.
  9. Click Create to save the Service Mesh Member Roll.
3.2.1.6.2. Creating the member roll from the CLI

Follow this procedure to add a project to the ServiceMeshMemberRoll from the command line.

Prerequisites

  • An installed, verified Red Hat OpenShift Service Mesh Operator.
  • Location of the installed ServiceMeshControlPlane.
  • List of projects to add to the service mesh.
  • Access to the OpenShift Container Platform Command-line Interface (CLI) commonly known as oc.

Procedure

  1. Log in to the OpenShift Container Platform CLI.

    $ oc login
  2. Create a ServiceMeshMemberRoll resource in the same project as the ServiceMeshControlPlane resource, in our example that is istio-system. The resource must be named default.

    $ oc create -n istio-system -f servicemeshmemberroll-default.yaml

    Example servicemeshmemberroll-default.yaml

    apiVersion: maistra.io/v1
    kind: ServiceMeshMemberRoll
    metadata:
      name: default
      namespace: istio-system
    spec:
      members:
        # a list of projects joined into the service mesh
        - your-project-name
        - another-project-name

  3. Modify the default YAML to add your projects as members. You can add any number of projects, but a project can only belong to one ServiceMeshMemberRoll resource.
3.2.1.6.3. Creating the Red Hat OpenShift Service Mesh members

ServiceMeshMember resources can be created by service mesh users who don’t have privileges to add members to the ServiceMeshMemberRoll directly. While project administrators are automatically given permission to create the ServiceMeshMember resource in their project, they cannot point it to any ServiceMeshControlPlane until the service mesh administrator explicitly grants access to the service mesh. Administrators can grant users permissions to access the mesh by granting them the mesh-user user role, for example:

$ oc policy add-role-to-user -n <control-plane-namespace> --role-namespace <control-plane-namespace> mesh-user <user-name>.

Administrators can modify the mesh user role binding in the control plane project to specify the users and groups that are granted access. The ServiceMeshMember adds the project to the ServiceMeshMemberRoll within the control plane project it references.

apiVersion: maistra.io/v1
kind: ServiceMeshMember
metadata:
  name: default
spec:
  controlPlaneRef:
    namespace: control-plane-namespace
    name: minimal-install

The mesh-users role binding is created automatically after the administrator creates the ServiceMeshControlPlane resource. An administrator can use the following command to add a role to a user.

$ oc policy add-role-to-user

The administrator can also create the mesh-user role binding before the administrator creates the ServiceMeshControlPlane resource. For example, the administrator can create it in the same oc apply operation as the ServiceMeshControlPlane resource.

This example adds a role binding for alice:

apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  namespace: control-plane-namespace
  name: mesh-users
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: Role
  name: mesh-user
subjects:
- apiGroup: rbac.authorization.k8s.io
  kind: User
  name: alice

3.2.1.7. Adding or removing projects from the service mesh

Follow this procedure to modify an existing Service Mesh ServiceMeshMemberRoll resource using the web console.

  • You can add any number of projects, but a project can only belong to one ServiceMeshMemberRoll resource.
  • The ServiceMeshMemberRoll resource is deleted when its corresponding ServiceMeshControlPlane resource is deleted.
3.2.1.7.1. Modifying the member roll from the web console

Prerequisites

  • An installed, verified Red Hat OpenShift Service Mesh Operator.
  • An existing ServiceMeshMemberRoll resource.
  • Name of the project with the ServiceMeshMemberRoll resource.
  • Names of the projects you want to add or remove from the mesh.

Procedure

  1. Log in to the OpenShift Container Platform web console.
  2. Navigate to OperatorsInstalled Operators.
  3. Click the Project menu and choose the project where your ServiceMeshControlPlane is deployed from the list, for example istio-system.
  4. Click the Red Hat OpenShift Service Mesh Operator.
  5. Click the Istio Service Mesh Member Roll tab.
  6. Click the default link.
  7. Click the YAML tab.
  8. Modify the YAML to add or remove projects as members. You can add any number of projects, but a project can only belong to one ServiceMeshMemberRoll resource.
  9. Click Save.
  10. Click Reload.
3.2.1.7.2. Modifying the member roll from the CLI

Follow this procedure to modify an existing Service Mesh member roll using the command line.

Prerequisites

  • An installed, verified Red Hat OpenShift Service Mesh Operator.
  • An existing ServiceMeshMemberRoll resource.
  • Name of the project with the ServiceMeshMemberRoll resource.
  • Names of the projects you want to add or remove from the mesh.
  • Access to the OpenShift Container Platform Command-line Interface (CLI) commonly known as oc.

Procedure

  1. Log in to the OpenShift Container Platform CLI.
  2. Edit the ServiceMeshMemberRoll resource.

    $ oc edit smmr -n <controlplane-namespace>
  3. Modify the YAML to add or remove projects as members. You can add any number of projects, but a project can only belong to one ServiceMeshMemberRoll resource.

    Example servicemeshmemberroll-default.yaml

    apiVersion: maistra.io/v1
    kind: ServiceMeshMemberRoll
    metadata:
      name: default
      namespace: istio-system
    spec:
      members:
        # a list of projects joined into the service mesh
        - your-project-name
        - another-project-name

3.2.1.8. Deleting the Red Hat OpenShift Service Mesh member roll

The ServiceMeshMemberRoll resource is automatically deleted when you delete the ServiceMeshControlPlane resource it is associated with.

3.2.2. Updating your application pods

If you selected the Automatic Approval Strategy when you were installing your Operators, then the Operators update the control plane automatically, but not your applications. Existing applications continue to be part of the mesh and function accordingly. The application administrator must restart applications to upgrade the sidecar.

If your deployment uses Automatic sidecar injection, you can update the pod template in the deployment by adding or modifying an annotation. Run the following command to redeploy the pods:

$ oc patch deployment/<deployment> -p '{"spec":{"template":{"metadata":{"annotations":{"kubectl.kubernetes.io/restartedAt": "'`date -Iseconds`'"}}}}}'

If your deployment does not use automatic sidecar injection, you must manually update the sidecars by modifying the sidecar container image specified in the deployment or pod.

3.3. Customizing the Red Hat OpenShift Service Mesh installation

You can customize your Red Hat OpenShift Service Mesh by modifying the default Service Mesh custom resource or by creating a new custom resource.

Prerequisites

3.3.1. Red Hat OpenShift Service Mesh custom resources

Note

The istio-system project is used as an example throughout the Service Mesh documentation, but you can use other projects as necessary.

A custom resource allows you to extend the API in an Red Hat OpenShift Service Mesh project or cluster. When you deploy Service Mesh it creates a default ServiceMeshControlPlane that you can modify to change the project parameters.

The Service Mesh operator extends the API by adding the ServiceMeshControlPlane resource type, which enables you to create ServiceMeshControlPlane objects within projects. By creating a ServiceMeshControlPlane object, you instruct the Operator to install a Service Mesh control plane into the project, configured with the parameters you set in the ServiceMeshControlPlane object.

This example ServiceMeshControlPlane definition contains all of the supported parameters and deploys Red Hat OpenShift Service Mesh 1.1.2 images based on Red Hat Enterprise Linux (RHEL).

Important

The 3scale Istio Adapter is deployed and configured in the custom resource file. It also requires a working 3scale account (SaaS or On-Premises).

Full example istio-installation.yaml

  apiVersion: maistra.io/v1
  kind: ServiceMeshControlPlane
  metadata:
    name: full-install
  spec:

    istio:
      global:
        proxy:
          resources:
            requests:
              cpu: 100m
              memory: 128Mi
            limits:
              cpu: 500m
              memory: 128Mi

      gateways:
        istio-egressgateway:
          autoscaleEnabled: false
        istio-ingressgateway:
          autoscaleEnabled: false

      mixer:
        policy:
          autoscaleEnabled: false

        telemetry:
          autoscaleEnabled: false
          resources:
            requests:
              cpu: 100m
              memory: 1G
            limits:
              cpu: 500m
              memory: 4G

      pilot:
        autoscaleEnabled: false
        traceSampling: 100

      kiali:
        enabled: true

      grafana:
        enabled: true

      tracing:
        enabled: true
        jaeger:
          template: all-in-one

3.3.2. ServiceMeshControlPlane parameters

The following examples illustrate use of the ServiceMeshControlPlane parameters and the tables provide additional information about supported parameters.

Important

The resources you configure for Red Hat OpenShift Service Mesh with these parameters, including CPUs, memory, and the number of pods, are based on the configuration of your OpenShift cluster. Configure these parameters based on the available resources in your current cluster configuration.

3.3.2.1. Istio global example

Here is an example that illustrates the Istio global parameters for the ServiceMeshControlPlane and a description of the available parameters with appropriate values.

Note

In order for the 3scale Istio Adapter to work, disablePolicyChecks must be false.

Example global parameters

  istio:
    global:
      tag: 1.1.0
      hub: registry.redhat.io/openshift-service-mesh/
      proxy:
        resources:
          requests:
            cpu: 10m
            memory: 128Mi
          limits:
      mtls:
        enabled: false
      disablePolicyChecks: true
      policyCheckFailOpen: false
      imagePullSecrets:
        - MyPullSecret

Table 3.1. Global parameters

ParameterDescriptionValuesDefault value

disablePolicyChecks

This parameter enables/disables policy checks.

true/false

true

policyCheckFailOpen

This parameter indicates whether traffic is allowed to pass through to the Envoy sidecar when the Mixer policy service cannot be reached.

true/false

false

tag

The tag that the Operator uses to pull the Istio images.

A valid container image tag.

1.1.0

hub

The hub that the Operator uses to pull Istio images.

A valid image repository.

maistra/ or registry.redhat.io/openshift-service-mesh/

mtls

This parameter controls whether to enable/disable Mutual Transport Layer Security (mTLS) between services by default.

true/false

false

imagePullSecrets

If access to the registry providing the Istio images is secure, list an imagePullSecret here.

redhat-registry-pullsecret OR quay-pullsecret

None

These parameters are specific to the proxy subset of global parameters.

Table 3.2. Proxy parameters

TypeParameterDescriptionValuesDefault value

Resources

cpu

The amount of CPU resources requested for Envoy proxy.

CPU resources, specified in cores or millicores (for example, 200m, 0.5, 1) based on your environment’s configuration.

10m

 

memory

The amount of memory requested for Envoy proxy

Available memory in bytes(for example, 200Ki, 50Mi, 5Gi) based on your environment’s configuration.

1024Mi

Limits

cpu

The maximum amount of CPU resources requested for Envoy proxy.

CPU resources, specified in cores or millicores (for example, 200m, 0.5, 1) based on your environment’s configuration.

2000m

 

memory

The maximum amount of memory Envoy proxy is permitted to use.

Available memory in bytes (for example, 200Ki, 50Mi, 5Gi) based on your environment’s configuration.

128Mi

3.3.2.2. Istio gateway configuration

Here is an example that illustrates the Istio gateway parameters for the ServiceMeshControlPlane and a description of the available parameters with appropriate values.

Example gateway parameters

  gateways:
       istio-egressgateway:
         autoscaleEnabled: false
         autoscaleMin: 1
         autoscaleMax: 5
       istio-ingressgateway:
         autoscaleEnabled: false
         autoscaleMin: 1
         autoscaleMax: 5

Table 3.3. Istio Gateway parameters

TypeParameterDescriptionValuesDefault value

istio-egressgateway

autoscaleEnabled

This parameter enables/disables autoscaling.

true/false

true

 

autoscaleMin

The minimum number of pods to deploy for the egress gateway based on the autoscaleEnabled setting.

A valid number of allocatable pods based on your environment’s configuration.

1

 

autoscaleMax

The maximum number of pods to deploy for the egress gateway based on the autoscaleEnabled setting.

A valid number of allocatable pods based on your environment’s configuration.

5

istio-ingressgateway

autoscaleEnabled

This parameter enables/disables autoscaling.

true/false

true

 

autoscaleMin

The minimum number of pods to deploy for the ingress gateway based on the autoscaleEnabled setting.

A valid number of allocatable pods based on your environment’s configuration.

1

 

autoscaleMax

The maximum number of pods to deploy for the ingress gateway based on the autoscaleEnabled setting.

A valid number of allocatable pods based on your environment’s configuration.

5

3.3.2.3. Istio Mixer configuration

Here is an example that illustrates the Mixer parameters for the ServiceMeshControlPlane and a description of the available parameters with appropriate values.

Example mixer parameters

mixer:
  enabled: true
  policy:
    autoscaleEnabled: false
  telemetry:
    autoscaleEnabled: false
    resources:
    requests:
      cpu: 10m
      memory: 128Mi
      limits:

Table 3.4. Istio Mixer policy parameters

ParameterDescriptionValuesDefault value

enabled

This parameter enables/disables Mixer.

true/false

true

autoscaleEnabled

This parameter enables/disables autoscaling. Disable this for small environments.

true/false

true

autoscaleMin

The minimum number of pods to deploy based on the autoscaleEnabled setting.

A valid number of allocatable pods based on your environment’s configuration.

1

autoscaleMax

The maximum number of pods to deploy based on the autoscaleEnabled setting.

A valid number of allocatable pods based on your environment’s configuration.

5

Table 3.5. Istio Mixer telemetry parameters

TypeParameterDescriptionValuesDefault

Resources

cpu

The percentage of CPU resources requested for Mixer telemetry.

CPU resources in millicores based on your environment’s configuration.

10m

 

memory

The amount of memory requested for Mixer telemetry.

Available memory in bytes (for example, 200Ki, 50Mi, 5Gi) based on your environment’s configuration.

128Mi

Limits

cpu

The maximum percentage of CPU resources Mixer telemetry is permitted to use.

CPU resources in millicores based on your environment’s configuration.

4800m

 

memory

The maximum amount of memory Mixer telemetry is permitted to use.

Available memory in bytes (for example, 200Ki, 50Mi, 5Gi) based on your environment’s configuration.

4G

3.3.2.4. Istio Pilot configuration

Here is an example that illustrates the Istio Pilot parameters for the ServiceMeshControlPlane and a description of the available parameters with appropriate values.

Example pilot parameters

  pilot:
    resources:
      requests:
        cpu: 100m
        memory: 128Mi
    autoscaleEnabled: false
    traceSampling: 100

Table 3.6. Istio Pilot parameters

ParameterDescriptionValuesDefault value

cpu

The percentage of CPU resources requested for Pilot.

CPU resources in millicores based on your environment’s configuration.

10m

memory

The amount of memory requested for Pilot.

Available memory in bytes (for example, 200Ki, 50Mi, 5Gi) based on your environment’s configuration.

128Mi

autoscaleEnabled

This parameter enables/disables autoscaling. Disable this for small environments.

true/false

true

traceSampling

This value controls how often random sampling occurs. Note: Increase for development or testing.

A valid percentage.

1.0

3.3.3. Configuring Kiali

When the Service Mesh Operator creates the ServiceMeshControlPlane it also processes the Kiali resource. The Kiali Operator then uses this object when creating Kiali instances.

The default Kiali parameters specified in the ServiceMeshControlPlane are as follows:

Example Kiali parameters

apiVersion: maistra.io/v1
kind: ServiceMeshControlPlane
spec:
    kiali:
      enabled: true
      dashboard:
        viewOnlyMode: false
      ingress:
        enabled: true

Table 3.7. Kiali parameters

ParameterDescriptionValuesDefault value
enabled

This parameter enables/disables Kiali. Kiali is enabled by default.

true/false

true

dashboard
   viewOnlyMode

This parameter enables/disables view-only mode for the Kiali console. When view-only mode is enabled, users cannot use the console to make changes to the Service Mesh.

true/false

false

ingress
   enabled

This parameter enables/disables ingress for Kiali.

true/false

true

3.3.3.1. Configuring Kiali for Grafana

When you install Kiali and Grafana as part of Red Hat OpenShift Service Mesh the Operator configures the following by default:

  • Grafana is enabled as an external service for Kiali
  • Grafana authorization for the Kiali console
  • Grafana URL for the Kiali console

Kiali can automatically detect the Grafana URL. However if you have a custom Grafana installation that is not easily auto-detectable by Kiali, you must update the URL value in the ServiceMeshControlPlane resource.

Additional Grafana parameters

spec:
  kiali:
    enabled: true
    dashboard:
      viewOnlyMode: false
      grafanaURL:  "https://grafana-istio-system.127.0.0.1.nip.io"
    ingress:
      enabled: true

3.3.3.2. Configuring Kiali for Jaeger

When you install Kiali and Jaeger as part of Red Hat OpenShift Service Mesh the Operator configures the following by default:

  • Jaeger is enabled as an external service for Kiali
  • Jaeger authorization for the Kiali console
  • Jaeger URL for the Kiali console

Kiali can automatically detect the Jaeger URL. However if you have a custom Jaeger installation that is not easily auto-detectable by Kiali, you must update the URL value in the ServiceMeshControlPlane resource.

Additional Jaeger parameters

spec:
  kiali:
    enabled: true
    dashboard:
      viewOnlyMode: false
      jaegerURL: "http://jaeger-query-istio-system.127.0.0.1.nip.io"
    ingress:
      enabled: true

3.3.4. Configuring Jaeger

When the Service Mesh Operator creates the ServiceMeshControlPlane resource it also creates the Jaeger resource. The Jaeger Operator then uses this object when creating Jaeger instances.

The default Jaeger parameters specified in the ServiceMeshControlPlane are as follows:

Default all-in-one Jaeger parameters

  apiVersion: maistra.io/v1
  kind: ServiceMeshControlPlane
  spec:
    istio:
      tracing:
        enabled: true
        jaeger:
          template: all-in-one

Table 3.8. Jaeger parameters

ParameterDescriptionValuesDefault value
tracing
   enabled

This parameter enables/disables tracing in Service Mesh. Jaeger is installed by default.

true/false

true

jaeger
   template

This parameter specifies which Jaeger deployment strategy to use.

  • all-in-one- For development, testing, demonstrations, and proof of concept.
  • production-elasticsearch - For production use.

all-in-one

Note

The default template in the ServiceMeshControlPlane resource is the all-in-one deployment strategy which uses in-memory storage. For production, the only supported storage option is Elasticsearch, therefore you must configure the ServiceMeshControlPlane to request the production-elasticsearch template when you deploy Service Mesh within a production environment.

3.3.4.1. Configuring Elasticsearch

The default Jaeger deployment strategy uses the all-in-one template so that the installation can be completed using minimal resources. However, because the all-in-one template uses in-memory storage, it is only recommended for development, demo, or testing purposes and should NOT be used for production environments.

If you are deploying Service Mesh and Jaeger in a production environment you must change the template to the production-elasticsearch template, which uses Elasticsearch for Jaeger’s storage needs.

Elasticsearch is a memory intensive application. The initial set of nodes specified in the default OpenShift Container Platform installation may not be large enough to support the Elasticsearch cluster. You should modify the default Elasticsearch configuration to match your use case and the resources you have requested for your OpenShift Container Platform installation. You can adjust both the CPU and memory limits for each component by modifying the resources block with valid CPU and memory values. Additional nodes must be added to the cluster if you want to run with the recommended amount (or more) of memory. Ensure that you do not exceed the resources requested for your OpenShift Container Platform installation.

Default "production" Jaeger parameters with Elasticsearch

  apiVersion: maistra.io/v1
  kind: ServiceMeshControlPlane
  spec:
    istio:
      tracing:
      enabled: true
      ingress:
        enabled: true
      jaeger:
        template: production-elasticsearch
        elasticsearch:
          nodeCount: 3
          redundancyPolicy:
          resources:
            requests:
              cpu: "1"
              memory: "16Gi"
            limits:
              cpu: "1"
              memory: "16Gi"

Table 3.9. Elasticsearch parameters

ParameterDescriptionValuesDefault ValueExamples
tracing:
  enabled

This parameter enables/disables tracing in Service Mesh. Jaeger is installed by default.

true/false

true

 
ingress:
  enabled

This parameter enables/disables ingress for Jaeger.

true/false

true

 
jaeger
   template

This parameter specifies which Jaeger deployment strategy to use.

all-in-one/production-elasticsearch

all-in-one

 
elasticsearch:
  nodeCount

Number of Elasticsearch nodes to create.

Integer value.

1

Proof of concept = 1, Minimum deployment =3

requests:
  cpu

Number of central processing units for requests, based on your environment’s configuration.

Specified in cores or millicores (for example, 200m, 0.5, 1).

1Gi

Proof of concept = 500m, Minimum deployment =1

requests:
  memory

Available memory for requests, based on your environment’s configuration.

Specified in bytes (for example, 200Ki, 50Mi, 5Gi).

500m

Proof of concept = 1Gi, Minimum deployment = 16Gi*

limits:
  cpu

Limit on number of central processing units, based on your environment’s configuration.

Specified in cores or millicores (for example, 200m, 0.5, 1).

 

Proof of concept = 500m, Minimum deployment =1

limits:
  memory

Available memory limit based on your environment’s configuration.

Specified in bytes (for example, 200Ki, 50Mi, 5Gi).

 

Proof of concept = 1Gi, Minimum deployment = 16Gi*

* Each Elasticsearch node can operate with a lower memory setting though this is not recommended for production deployments. For production use, you should have no less than 16Gi allocated to each Pod by default, but preferably allocate as much as you can, up to 64Gi per Pod.

Procedure

  1. Log in to the OpenShift Container Platform web console as a user with the cluster-admin role.
  2. Navigate to OperatorsInstalled Operators.
  3. Click the Red Hat OpenShift Service Mesh Operator.
  4. Click the Istio Service Mesh Control Plane tab.
  5. Click the name of your control plane file, for example, basic-install.
  6. Click the YAML tab.
  7. Edit the Jaeger parameters, replacing the default all-in-one template with parameters for the production-elasticsearch template, modified for your use case. Ensure that the indentation is correct.
  8. Click Save.
  9. Click Reload. OpenShift Container Platform redeploys Jaeger and creates the Elasticsearch resources based on the specified parameters.

For more information about configuring Elasticsearch with OpenShift Container Platform, see Configuring Elasticsearch.

3.3.5. 3scale configuration

Here is an example that illustrates the 3scale Istio Adapter parameters for the Red Hat OpenShift Service Mesh custom resource and a description of the available parameters with appropriate values.

Example 3scale parameters

threeScale:
  enabled: false
  PARAM_THREESCALE_LISTEN_ADDR: 3333
  PARAM_THREESCALE_LOG_LEVEL: info
  PARAM_THREESCALE_LOG_JSON: true
  PARAM_THREESCALE_LOG_GRPC: false
  PARAM_THREESCALE_REPORT_METRICS: true
  PARAM_THREESCALE_METRICS_PORT: 8080
  PARAM_THREESCALE_CACHE_TTL_SECONDS: 300
  PARAM_THREESCALE_CACHE_REFRESH_SECONDS: 180
  PARAM_THREESCALE_CACHE_ENTRIES_MAX: 1000
  PARAM_THREESCALE_CACHE_REFRESH_RETRIES: 1
  PARAM_THREESCALE_ALLOW_INSECURE_CONN: false
  PARAM_THREESCALE_CLIENT_TIMEOUT_SECONDS: 10
  PARAM_THREESCALE_GRPC_CONN_MAX_SECONDS: 60

Table 3.10. 3scale parameters

ParameterDescriptionValuesDefault value

enabled

Whether to use the 3scale adapter

true/false

false

PARAM_THREESCALE_LISTEN_ADDR

Sets the listen address for the gRPC server

Valid port number

3333

PARAM_THREESCALE_LOG_LEVEL

Sets the minimum log output level.

debug, info, warn, error, or none

info

PARAM_THREESCALE_LOG_JSON

Controls whether the log is formatted as JSON

true/false

true

PARAM_THREESCALE_LOG_GRPC

Controls whether the log contains gRPC info

true/false

true

PARAM_THREESCALE_REPORT_METRICS

Controls whether 3scale system and backend metrics are collected and reported to Prometheus

true/false

true

PARAM_THREESCALE_METRICS_PORT

Sets the port that the 3scale /metrics endpoint can be scrapped from

Valid port number

8080

PARAM_THREESCALE_CACHE_TTL_SECONDS

Time period, in seconds, to wait before purging expired items from the cache

Time period in seconds

300

PARAM_THREESCALE_CACHE_REFRESH_SECONDS

Time period before expiry when cache elements are attempted to be refreshed

Time period in seconds

180

PARAM_THREESCALE_CACHE_ENTRIES_MAX

Max number of items that can be stored in the cache at any time. Set to 0 to disable caching

Valid number

1000

PARAM_THREESCALE_CACHE_REFRESH_RETRIES

The number of times unreachable hosts are retried during a cache update loop

Valid number

1

PARAM_THREESCALE_ALLOW_INSECURE_CONN

Allow to skip certificate verification when calling 3scale APIs. Enabling this is not recommended.

true/false

false

PARAM_THREESCALE_CLIENT_TIMEOUT_SECONDS

Sets the number of seconds to wait before terminating requests to 3scale System and Backend

Time period in seconds

10

PARAM_THREESCALE_GRPC_CONN_MAX_SECONDS

Sets the maximum amount of seconds (+/-10% jitter) a connection may exist before it is closed

Time period in seconds

60

Next steps

3.4. Updating Red Hat OpenShift Service Mesh

If you are updating from Red Hat OpenShift Service Mesh 1.0 to 1.1, you must update the ServiceMeshControlPlane resource to update the control plane components to the new version.

  1. In the web console, click the Red Hat OpenShift Service Mesh operator.
  2. Click the Project menu and choose the project where your ServiceMeshControlPlane is deployed from the list, for example istio-system.
  3. Click the name of your control plane, for example basic-install.
  4. Click YAML and add a version field to the spec: of your ServiceMeshControlPlane resource. For example, to update to Red Hat OpenShift Service Mesh 1.1.0, add version: v1.1.
spec:
  version: v1.1
  ...

The version field specifies the version of ServiceMesh to install and defaults to the latest available version.

3.4.1. Manual updates

If you choose to update manually, the Operator Lifecycle Manager (OLM) controls the installation, upgrade, and role-based access control (RBAC) of Operators in a cluster. OLM runs by default in OpenShift Container Platform. OLM uses CatalogSources, which use the Operator Registry API, to query for available Operators as well as upgrades for installed Operators.

  • For more information about how OpenShift Container Platform handled upgrades, refer to the Operator Lifecycle Manager documentation.

3.5. Removing Red Hat OpenShift Service Mesh

This process allows you to remove Red Hat OpenShift Service Mesh from an existing OpenShift Container Platform instance. Remove the control plane before removing the operators.

3.5.1. Removing the Red Hat OpenShift Service Mesh control plane

You can remove the Service Mesh control plane by using the OpenShift Container Platform web console or the CLI.

3.5.1.1. Removing the control plane with the web console

Follow this procedure to remove the Red Hat OpenShift Service Mesh control plane by using the web console.

Prerequisites

  • The Red Hat OpenShift Service Mesh control plane must be deployed.

Procedure

  1. Log in to the OpenShift Container Platform web console.
  2. Click the Project menu and choose the istio-system project from the list.
  3. Navigate to OperatorsInstalled Operators.
  4. Click on Service Mesh Control Plane under Provided APIs.
  5. Click the ServiceMeshControlPlane menu kebab .
  6. Click Delete Service Mesh Control Plane.
  7. Click Delete on the confirmation dialog window to remove the ServiceMeshControlPlane.

3.5.1.2. Removing the control plane from the CLI

Follow this procedure to remove the Red Hat OpenShift Service Mesh control plane by using the CLI.

Prerequisites

  • The Red Hat OpenShift Service Mesh control plane must be deployed.
  • Access to the OpenShift Container Platform Command-line Interface (CLI) also known as oc.
Procedure

When you remove the ServiceMeshControlPlane, Service Mesh tells the Operator to begin uninstalling everything it installed.

Tip

You can use the shortened smcp alias in place of servicemeshcontrolplane.

  1. Log in to the OpenShift Container Platform CLI.
  2. Run this command to retrieve the name of the installed ServiceMeshControlPlane:

    $ oc get servicemeshcontrolplanes -n istio-system
  3. Replace <name_of_custom_resource> with the output from the previous command, and run this command to remove the custom resource:

    $ oc delete servicemeshcontrolplanes -n istio-system <name_of_custom_resource>

3.5.2. Removing the installed Operators

You must remove the Operators to successfully remove Red Hat OpenShift Service Mesh. Once you remove the Red Hat OpenShift Service Mesh Operator, you must remove the Jaeger Operator, Kiali Operator, and the Elasticsearch Operator.

3.5.2.1. Removing the Red Hat OpenShift Service Mesh Operator

Follow this procedure to remove the Red Hat OpenShift Service Mesh Operator.

Prerequisites

  • Access to the OpenShift Container Platform web console.
  • The Red Hat OpenShift Service Mesh Operator must be installed.

Procedure

  1. Log in to the OpenShift Container Platform web console.
  2. From the OperatorsInstalled Operators page, scroll or type a keyword into the Filter by name to find the Red Hat OpenShift Service Mesh Operator. Then, click on it.
  3. On the right-hand side of the Operator Details page, select Uninstall Operator from the Actions drop-down menu.
  4. When prompted by the Remove Operator Subscription window, optionally select the Also completely remove the Operator from the selected namespace check box if you want all components related to the installation to be removed. This removes the CSV, which in turn removes the Pods, Deployments, CRDs, and CRs associated with the Operator.

3.5.2.2. Removing the Jaeger Operator

Follow this procedure to remove the Jaeger Operator.

Prerequisites

  • Access to the OpenShift Container Platform web console.
  • The Jaeger Operator must be installed.

Procedure

  1. Log in to the OpenShift Container Platform web console.
  2. From the OperatorsInstalled Operators page, scroll or type a keyword into the Filter by name to find the Jaeger Operator. Then, click on it.
  3. On the right-hand side of the Operator Details page, select Uninstall Operator from the Actions drop-down menu.
  4. When prompted by the Remove Operator Subscription window, optionally select the Also completely remove the Operator from the selected namespace check box if you want all components related to the installation to be removed. This removes the CSV, which in turn removes the Pods, Deployments, CRDs, and CRs associated with the Operator.

3.5.2.3. Removing the Kiali Operator

Follow this procedure to remove the Kiali Operator.

Prerequisites

  • Access to the OpenShift Container Platform web console.
  • The Kiali Operator must be installed.

Procedure

  1. Log in to the OpenShift Container Platform web console.
  2. From the OperatorsInstalled Operators page, scroll or type a keyword into the Filter by name to find the Kiali Operator. Then, click on it.
  3. On the right-hand side of the Operator Details page, select Uninstall Operator from the Actions drop-down menu.
  4. When prompted by the Remove Operator Subscription window, optionally select the Also completely remove the Operator from the selected namespace check box if you want all components related to the installation to be removed. This removes the CSV, which in turn removes the Pods, Deployments, CRDs, and CRs associated with the Operator.

3.5.2.4. Removing the Elasticsearch Operator

Follow this procedure to remove the Elasticsearch Operator.

Prerequisites

  • Access to the OpenShift Container Platform web console.
  • The Elasticsearch Operator must be installed.

Procedure

  1. Log in to the OpenShift Container Platform web console.
  2. From the OperatorsInstalled Operators page, scroll or type a keyword into the Filter by name to find the Elasticsearch Operator. Then, click on it.
  3. On the right-hand side of the Operator Details page, select Uninstall Operator from the Actions drop-down menu.
  4. When prompted by the Remove Operator Subscription window, optionally select the Also completely remove the Operator from the selected namespace check box if you want all components related to the installation to be removed. This removes the CSV, which in turn removes the Pods, Deployments, CRDs, and CRs associated with the Operator.

3.5.2.5. Clean up Operator resources

Follow this procedure to manually remove resources left behind after removing the Red Hat OpenShift Service Mesh Operator by using the OperatorHub interface.

Prerequisites

  • An account with cluster administration access.
  • Access to the OpenShift Container Platform Command-line Interface (CLI) also known as oc.

Procedure

  1. Log in to the OpenShift Container Platform CLI as a cluster administrator.
  2. Run the following commands to clean up resources after uninstalling the Operators:

    Note

    Replace <operator-project> with the name of the project where the Red Hat OpenShift Service Mesh Operator was installed. This is typically openshift-operators.

    $ oc delete validatingwebhookconfiguration/<operator-project>.servicemesh-resources.maistra.io
    $ oc delete mutatingwebhoookconfigurations/<operator-project>.servicemesh-resources.maistra.io
    $ oc delete -n <operator-project> daemonset/istio-node
    $ oc delete clusterrole/istio-admin clusterrole/istio-cni clusterrolebinding/istio-cni
    $ oc get crds -o name | grep '.*\.istio\.io' | xargs -r -n 1 oc delete
    $ oc get crds -o name | grep '.*\.maistra\.io' | xargs -r -n 1 oc delete

Chapter 4. Day Two

4.1. Deploying applications on Red Hat OpenShift Service Mesh

When you deploy an application into the Service Mesh, there are several differences between the behavior of applications in the upstream community version of Istio and the behavior of applications within a Red Hat OpenShift Service Mesh installation.

4.1.1. Creating control plane templates

You can create reusable configurations with ServiceMeshControlPlane templates. Individual users can extend the templates you create with their own configurations. Templates can also inherit configuration information from other templates. For example, you can create an accounting control plane for the accounting team and a marketing control plane for the marketing team. If you create a development template and a production template, members of the marketing team and the accounting team can extend the development and production templates with team specific customization.

When you configure control plane templates, which follow the same syntax as the ServiceMeshControlPlane, users inherit settings in a hierarchical fashion. The Operator is delivered with a default template with default settings for Red Hat OpenShift Service Mesh. To add custom templates you must create a ConfigMap named smcp-templates in the openshift-operators project and mount the ConfigMap in the Operator container at /usr/local/share/istio-operator/templates.

4.1.1.1. Creating the ConfigMap

Follow this procedure to create the ConfigMap.

Prerequisites

  • An installed, verified Service Mesh Operator.
  • An account with the cluster-admin role.
  • Location of the Operator deployment.
  • Access to the OpenShift Container Platform Command-line Interface (CLI) also known as oc.

Procedure

  1. Log in to the OpenShift Container Platform CLI as a cluster administrator.
  2. From the CLI, run this command to create the ConfigMap named smcp-templates in the openshift-operators project and replace <templates-directory> with the location of the ServiceMeshControlPlane files on your local disk:

    $ oc create configmap --from-file=<templates-directory> smcp-templates -n openshift-operators
  3. Locate the Operator ClusterServiceVersion name.

    $ oc get clusterserviceversion -n openshift-operators | grep 'Service Mesh'
    maistra.v1.0.0            Red Hat OpenShift Service Mesh   1.0.0                Succeeded
  4. Edit the Operator cluster service version to instruct the Operator to use the smcp-templates ConfigMap.

    $ oc edit clusterserviceversion -n openshift-operators maistra.v1.0.0
  5. Add a volume mount and volume to the Operator deployment.

    deployments:
      - name: istio-operator
        spec:
          template:
            spec:
              containers:
                volumeMounts:
                  - name: discovery-cache
                    mountPath: /home/istio-operator/.kube/cache/discovery
                  - name: smcp-templates
                    mountPath: /usr/local/share/istio-operator/templates/
              volumes:
                - name: discovery-cache
                  emptyDir:
                    medium: Memory
                - name: smcp-templates
                  configMap:
                    name: smcp-templates
    ...
  6. Save your changes and exit the editor.
  7. You can now use the template parameter in the ServiceMeshControlPlane to specify a template.

      apiVersion: maistra.io/v1
      kind: ServiceMeshControlPlane
      metadata:
        name: minimal-install
      spec:
        template: default

4.1.2. Red Hat OpenShift Service Mesh's sidecar injection

Red Hat OpenShift Service Mesh relies on a proxy sidecar within the application’s pod to provide Service Mesh capabilities to the application. You can enable automatic sidecar injection or manage it manually. Red Hat recommends automatic injection using the annotation with no need to label projects. This ensures that your application contains the appropriate configuration for the Service Mesh upon deployment. This method requires fewer privileges and does not conflict with other OpenShift capabilities such as builder pods.

Note

The upstream version of Istio injects the sidecar by default if you have labeled the project. Red Hat OpenShift Service Mesh requires you to opt in to having the sidecar automatically injected to a deployment, so you are not required to label the project. This avoids injecting a sidecar if it is not wanted (for example, in build or deploy pods).

The webhook checks the configuration of pods deploying into all projects to see if they are opting in to injection with the appropriate annotation.

4.1.2.1. Enabling automatic sidecar injection

When deploying an application into the Red Hat OpenShift Service Mesh you must opt in to injection by specifying the sidecar.istio.io/inject annotation with a value of "true". Opting in ensures that the sidecar injection does not interfere with other OpenShift features such as builder pods used by numerous frameworks within the OpenShift ecosystem.

Prerequisites

  • Identify the deployments for which you want to enable automatic sidecar injection.
  • Locate the application’s YAML configuration file.

Procedure

  1. Open the application’s configuration YAML file in an editor.
  2. Add sidecar.istio.io/inject to the configuration YAML with a value of "true" as illustrated here:

    Sleep test application example

    apiVersion: apps/v1
    kind: Deployment
    metadata:
      labels:
        app: sleep
      name: sleep
    spec:
      replicas: 1
      selector:
        matchLabels:
          app: sleep
      template:
        metadata:
          annotations:
            sidecar.istio.io/inject: "true"
          labels:
            app: sleep
        spec:
          containers:
          - name: sleep
            image: tutum/curl
            command: ["/bin/sleep","infinity"]
            imagePullPolicy: IfNotPresent

  3. Save the configuration file.

4.1.2.2. Updating Mixer policy enforcement

In previous versions of Red Hat OpenShift Service Mesh, Mixer’s policy enforcement was enabled by default. Mixer policy enforcement is now disabled by default. You must enable it before running policy tasks.

Prerequisites

  • Access to the OpenShift Container Platform Command-line Interface (CLI) also known as oc.

Procedure

  1. Log in to the OpenShift Container Platform CLI.
  2. Run this command to check the current Mixer policy enforcement status:

    $ oc get cm -n istio-system istio -o jsonpath='{.data.mesh}' | grep disablePolicyChecks
  3. If disablePolicyChecks: true, edit the Service Mesh ConfigMap:

    $ oc edit cm -n istio-system istio
  4. Locate disablePolicyChecks: true within the ConfigMap and change the value to false.
  5. Save the configuration and exit the editor.
  6. Re-check the Mixer policy enforcement status to ensure it is set to false.

4.1.3. Setting the correct network policy

Service Mesh creates network policies in the control plane and member namespaces to whitelist traffic between them. Before you deploy, consider the following conditions to ensure the services in your mesh that were previously exposed through an OpenShift Container Platform route.

  • Traffic into the mesh must always go through the ingress-gateway for Istio to work properly.
  • Deploy services external to the mesh in separate namespaces that are not in any mesh.
  • Non-mesh services that need to be deployed within a service mesh enlisted namespace should label their deployments maistra.io/expose-route: "true", which ensures OpenShift Container Platform routes to these services still work.

Next steps

4.2. Configuring your service mesh for distributed tracing

This section describes configuration that is performed in the CRD or in the CR file.

Prerequisites

  • Access to an OpenShift Container Platform cluster with cluster-admin user privileges.
  • Elasticsearch operator has been installed on the cluster
  • Jaeger operator has been installed on the cluster.

4.2.1. Configuring the Elasticsearch index cleaner job

When the Service Mesh Operator creates the ServiceMeshControlPlane it also creates the custom resource (CR) for Jaeger. The Jaeger operator then uses this CR when creating Jaeger instances.

When using Elasticsearch storage, by default a job is created to clean old traces from it. To configure the options for this job, you edit the Jaeger custom resource (CR), to customize it for your use case. The relevant options are listed below.

  apiVersion: jaegertracing.io/v1
  kind: Jaeger
  spec:
    strategy: production
    storage:
      type: elasticsearch
      esIndexCleaner:
        enabled: false
        numberOfDays: 7
        schedule: "55 23 * * *"

Table 4.1. Elasticsearch index cleaner parameters

ParameterValuesDescription

enabled

true/ false

Enable or disable the index cleaner job.

numberOfDays

integer value

Number of days to wait before deleting an index.

schedule

"55 23 * * *"

Cron expression for the job to run

4.3. Example Application

Warning

The Bookinfo example application allows you to test your Red Hat OpenShift Service Mesh 1.1.2 installation on OpenShift Container Platform.

Red Hat does not provide support for the Bookinfo application.

4.3.1. Bookinfo application

The upstream Istio project has an example tutorial called Bookinfo, which is composed of four separate microservices used to demonstrate various Istio features. The Bookinfo application displays information about a book, similar to a single catalog entry of an online book store. Displayed on the page is a description of the book, book details (ISBN, number of pages, and other information), and book reviews.

The Bookinfo application consists of these microservices:

  • The productpage microservice calls the details and reviews microservices to populate the page.
  • The details microservice contains book information.
  • The reviews microservice contains book reviews. It also calls the ratings microservice.
  • The ratings microservice contains book ranking information that accompanies a book review.

There are three versions of the reviews microservice:

  • Version v1 does not call the ratings Service.
  • Version v2 calls the ratings Service and displays each rating as one to five black stars.
  • Version v3 calls the ratings Service and displays each rating as one to five red stars.

4.3.2. Installing the Bookinfo application

This tutorial walks you through creating a Bookinfo project, deploying the Bookinfo application, and running Bookinfo on OpenShift Container Platform with Service Mesh 1.1.2.

Prerequisites:

  • OpenShift Container Platform 4.1 or higher installed.
  • Red Hat OpenShift Service Mesh 1.1.2 installed.
  • Access to the OpenShift Container Platform Command-line Interface (CLI) also known as oc.
Note

Red Hat OpenShift Service Mesh implements auto-injection differently than the upstream Istio project, therefore this procedure uses a version of the bookinfo.yaml file annotated to enable automatic injection of the Istio sidecar for Red Hat OpenShift Service Mesh.

Procedure

  1. Log in to the OpenShift Container Platform web console as a user with cluster-admin rights.
  2. Click to HomeProjects.
  3. Click Create Project.
  4. Enter bookinfo as the Project Name, enter a Display Name, and enter a Description, then click Create.

    • Alternatively, you can run this command from the CLI to create the bookinfo project.

      $ oc new-project bookinfo
  5. Click OperatorsInstalled Operators.
  6. Click the Project menu and use the control plane namespace. In this example, use istio-system.
  7. Click the Red Hat OpenShift Service Mesh Operator.
  8. Click the Istio Service Mesh Member Roll link.

    1. If you have already created a Istio Service Mesh Member Roll, click the name, then click the YAML tab to open the YAML editor.
    2. If you have not created a Istio Service Mesh Member Roll, click Create Service Mesh Member Roll.

      Note

      You need cluster-admin rights to edit the Istio Service Mesh Member Roll.

  9. Edit the default Service Mesh Member Roll YAML and add bookinfo to the members list.

    Bookinfo ServiceMeshMemberRoll example

      apiVersion: maistra.io/v1
      kind: ServiceMeshMemberRoll
      metadata:
        name: default
      spec:
        members:
        - bookinfo

    • Alternatively, you can run this command from the CLI to add the bookinfo project to the ServiceMeshMemberRoll. Replace <control plane project> with the name of your control plane project.

      $ oc -n <control plane project> patch --type='json' smmr default -p '[{"op": "add", "path": "/spec/members", "value":["'"bookinfo"'"]}]'
  10. Click Create to save the updated Service Mesh Member Roll.
  11. From the CLI, deploy the Bookinfo application in the `bookinfo` project by applying the bookinfo.yaml file:

    $ oc apply -n bookinfo -f https://raw.githubusercontent.com/Maistra/istio/maistra-1.1/samples/bookinfo/platform/kube/bookinfo.yaml
  12. Create the ingress gateway by applying the bookinfo-gateway.yaml file:

    $ oc apply -n bookinfo -f https://raw.githubusercontent.com/Maistra/istio/maistra-1.1/samples/bookinfo/networking/bookinfo-gateway.yaml
  13. Set the value for the GATEWAY_URL parameter:

    Note

    Replace <control_plane_project> with the name of your control plane project. In this example, the control plane project is istio-system.

    $ export GATEWAY_URL=$(oc -n <control_plane_project> get route istio-ingressgateway -o jsonpath='{.spec.host}')

4.3.3. Adding default destination rules

Before you can use the Bookinfo application, you have to add default destination rules. There are two preconfigured YAML files, depending on whether or not you enabled mutual transport layer security (TLS) authentication.

Procedure

  1. To add destination rules, run one of the following commands:

    • If you did not enable mutual TLS:

      $ oc apply -n bookinfo -f https://raw.githubusercontent.com/Maistra/istio/maistra-1.1/samples/bookinfo/networking/destination-rule-all.yaml
    • If you enabled mutual TLS:

      $ oc apply -n bookinfo -f https://raw.githubusercontent.com/Maistra/istio/maistra-1.1/samples/bookinfo/networking/destination-rule-all-mtls.yaml

4.3.4. Verifying the Bookinfo installation

Before configuring your application, verify that it successfully deployed.

Prerequisites

  • OpenShift Container Platform 4.1 or higher installed.
  • Red Hat OpenShift Service Mesh 1.1.2 installed.
  • Access to the OpenShift Container Platform Command-line Interface (CLI) also known as oc.

Procedure

  1. Log in to the OpenShift Container Platform CLI.
  2. Run this command to confirm that Bookinfo is deployed:

    $ curl -o /dev/null -s -w "%{http_code}\n" http://$GATEWAY_URL/productpage
    • Alternatively, you can open http://$GATEWAY_URL/productpage in your browser.
    • You can also verify that all pods are ready with this command:

      $ oc get pods -n bookinfo

4.3.5. Removing the Bookinfo application

Follow these steps to remove the Bookinfo application.

Prerequisites

  • OpenShift Container Platform 4.1 or higher installed.
  • Red Hat OpenShift Service Mesh 1.1.2 installed.
  • Access to the OpenShift Container Platform Command-line Interface (CLI) also known as oc.

4.3.5.1. Delete the Bookinfo project

Procedure

  1. Log in to the OpenShift Container Platform web console.
  2. Click to HomeProjects.
  3. Click on the bookinfo menu kebab , and then click Delete Project.
  4. Type bookinfo in the confirmation dialog box, and then click Delete.

    • Alternatively, you can run this command from the CLI to create the bookinfo project.

      $ oc delete project bookinfo

4.3.5.2. Remove the Bookinfo project from the Service Mesh member roll

Procedure

  1. Log in to the OpenShift Container Platform web console.
  2. Click OperatorsInstalled Operators.
  3. Click the Project menu and choose openshift-operators from the list.
  4. Click the Istio Service Mesh Member Roll link under Provided APIS for the Red Hat OpenShift Service Mesh Operator.
  5. Click the ServiceMeshMemberRoll menu kebab and select Edit Service Mesh Member Roll.
  6. Edit the default Service Mesh Member Roll YAML and remove bookinfo from the members list.

    • Alternatively, you can run this command from the CLI to remove the bookinfo project from the ServiceMeshMemberRoll. Replace <control plane project> with the name of your control plane project.

      $ oc -n <control plane project> patch --type='json' smmr default -p '[{"op": "remove", "path": "/spec/members", "value":["'"bookinfo"'"]}]'
  7. Click Save to update Service Mesh Member Roll.

4.4. Kiali tutorial

Kiali works with Istio to visualize your service mesh topology to provide visibility into features like circuit breakers, request rates, and more. Kiali offers insights about the mesh components at different levels, from abstract Applications to Services and Workloads. Kiali provides an interactive graph view of your Namespace in real time. It can display the interactions at several levels (applications, versions, workloads) with contextual information and charts on the selected graph node or edge.

This tutorial uses Service Mesh and the Bookinfo tutorial to demonstrate how you can use the Kiali console to view the topography and health of your service mesh.

Note

The Bookinfo example application allows you to test your Red Hat OpenShift Service Mesh 1.1.2 installation on OpenShift Container Platform.

Red Hat does not provide support for the Bookinfo application.

4.4.1. Accessing the Kiali console

The Kiali console provides visualization and observability for your Service Mesh. The Kiali console has different views that provide insights into Service Mesh components at different levels, from Applications to Services to Workloads. It also provides validation for Istio configurations.

Prerequisites

  • OpenShift Container Platform 4.1 or higher installed.
  • Red Hat OpenShift Service Mesh 1.1.2 installed.
  • Kiali enabled during the installation.
  • Bookinfo demonstration application installed.

The installation process creates a route to access the Kiali console.

Procedure from the console

  1. In the OpenShift Container Platform console, navigate to NetworkingRoutes and search for the Kiali route.
  2. Click the URL listed under Location.

    The default login strategy is openshift which means that you should be automatically logged into the Kiali console using the same user name and password as you use to access the OpenShift Container Platform console. When you first log in you see the Overview page, which provides a quick overview of the health of the various Namespaces that are part of your Service Mesh.

    Overview Page

  3. Use the left navigation or click one of the Namespace icons to view your Applications, Workloads, or Services.

Procedure from the CLI

  1. Run this command from the CLI to obtain the route and Kiali URL:

    $ oc get routes

    Sample CLI output showing routes

    NAME                   HOST/PORT                                                PATH      SERVICES               PORT              TERMINATION   WILDCARD
    grafana                grafana-openshift-operators.127.0.0.1.nip.io                          grafana                http                            None
    istio-ingress          istio-ingress-openshift-operators.127.0.0.1.nip.io                    istio-ingress          http                            None
    istio-ingressgateway   istio-ingressgateway-openshift-operators.127.0.0.1.nip.io             istio-ingressgateway   http                            None
    jaeger-query           jaeger-query-openshift-operators.127.0.0.1.nip.io                     jaeger-query           jaeger-query      edge          None
    kiali                  kiali-openshift-operators.127.0.0.1.nip.io                            kiali                  <all>                           None
    prometheus             prometheus-openshift-operators.127.0.0.1.nip.io                       prometheus             http-prometheus                 None
    tracing                tracing-openshift-operators.127.0.0.1.nip.io                          tracing                tracing           edge          None

  2. Launch a browser and navigate to https://<KIALI_URL> (in the CLI output example, this is kiali-openshift-operators.127.0.0.1.nip.io). You should see the Kiali console login screen.
  3. Log in to the Kiali console using the user name and password that you use when logging in to the OpenShift Container Platform console.

4.4.2. Exploring the Graph page

The Graph page shows a graph of microservices, which are connected by the requests going through them. On this page, you can see how Applications, Workloads, or Services interact with each other.

Procedure

  1. In the Kiali console, click Graph in the left navigation.

    Kiali graph

  2. If necessary, select bookinfo from the Namespace menu. The graph displays the applications in the Bookinfo application.
  3. Click the question mark (?) under the Namespace menu to take the Graph Help Tour.
  4. Click Done to close the Help Tour.
  5. Click Legend in the lower left corner. Kiali displays the graph legend.

    Kiali legend

  6. Close the Graph Legend.
  7. Hover over the productpage Node. Note how the graph highlights only the incoming and outgoing traffic from the Node.
  8. Click the productpage Node. Note how the details on the right side of the page change to display the productpage details.

4.4.3. Exploring the Applications page

The Applications page lets you search for and view applications, their health, and other details.

Procedure

  1. In the Kiali console, click Applications in the left navigation.
  2. If necessary, select bookinfo from the Namespace menu. The page displays the applications in the selected Namespace and their health.
  3. Hover over the Health icon to view additional health details.
  4. Click the reviews Service to view the details for that application.

    Kiali Applications details

  5. On the Applications Details page you can view more detailed health information, and drill down for further details about the three versions of the reviews Service.
  6. From the Application Details page you can also click tabs to view Traffic and Inbound and Outbound Metrics for the application.

4.4.4. Exploring the Workloads page

The Workloads page lets you search for and view Workloads, their health, and other details.

Procedure

  1. In the Kiali console, click Workloads in the left navigation.
  2. If necessary, select bookinfo from the Namespace menu. The page displays the Workloads in the selected Namespace, their health, and labels.
  3. Click the reviews-v1 Workload to view the details for that Workload.
  4. On the Workload Details page you can view an overview of Pods and Services associated with the Workload.

    Kiali Workloads details

  5. From the Workload Details page you can also click tabs to view Traffic, Logs, and Inbound and Outbound Metrics for the Workload.

4.4.5. Exploring the Services page

The Services page lets you search for and view Services, their health, and other details.

Procedure

  1. In the Kiali console, click Services in the left navigation.
  2. If necessary, select bookinfo from the Namespace menu. The page displays a listing of all the Services that are running in the selected Namespace and additional information about them, such as health status.
  3. Hover over the health icon for any of the Services to view health information about the Service. A Service is considered healthy when it is online and responding to requests without errors.
  4. Click the Reviews Service to view its details. Note that there are three different versions of this Service.

    Kiali Services details

  5. On the Services Details page you can view an overview of Workloads, virtual Services, and destination rules associated with the Service.
  6. From the Services Details page you can also click tabs to view Traffic, Inbound Metrics, and Traces for the Service.
  7. Click the Actions menu. From here you can perform the following actions:

    • Create Weighted Routing
    • Create Matching Routing
    • Suspend Traffic
    • Delete ALL Traffic Routing
  8. Click the name of one of the Services to view additional details about that specific version of the Service.

4.4.6. Exploring the Istio Config page

The Istio Config page lets you view all of the currently running configurations to your Service Mesh, such as Circuit Breakers, Destination Rules, Fault Injection, Gateways, Routes, Route Rules, and Virtual Services.

Procedure

  1. In the Kiali console, click Istio Config in the left navigation.
  2. If necessary, select bookinfo from the Namespace menu. The page displays a listing of configurations running in the selected Namespace and validation status.

    Istio configuration

  3. Click one of the configurations to view additional information about the configuration file.

    Istio Configuration YAML

4.5. Distributed tracing tutorial

Jaeger is an open source distributed tracing system. You use Jaeger for monitoring and troubleshooting microservices-based distributed systems. Using Jaeger you can perform a trace, which follows the path of a request through various microservices that make up an application. Jaeger is installed by default as part of the Service Mesh.

This tutorial uses Service Mesh and the bookinfo tutorial to demonstrate how you can use Jeager to perform distributed tracing.

Note

The Bookinfo example application allows you to test your Red Hat OpenShift Service Mesh 1.1.2 installation on OpenShift Container Platform.

Red Hat does not provide support for the Bookinfo application.

4.5.1. Generating traces and analyzing trace data

This tutorial uses Service Mesh and the Bookinfo tutorial to demonstrate how you can perform a trace using the Jaeger component of Red Hat OpenShift Service Mesh.

Prerequisites:

  • OpenShift Container Platform 4.1 or higher installed.
  • Red Hat OpenShift Service Mesh 1.1.2 installed.
  • Jaeger enabled during the installation.
  • Bookinfo example application installed.

Procedure

  1. After you have deployed the Bookinfo application you will need to generate calls to the Bookinfo application so that you have some trace data to analyze. Access http://<GATEWAY_URL>/productpage and refresh the page a few times to generate some trace data.
  2. The installation process creates a route to access the Jaeger console.

    1. In the OpenShift Container Platform console, navigate to NetworkingRoutes and search for the Jaeger route, which is the URL listed under Location.
    2. Use the CLI to query for details of the route:

      $ export JAEGER_URL=$(oc get route -n bookinfo jaeger-query -o jsonpath='{.spec.host}')
  3. Launch a browser and navigate to https://<JAEGER_URL>.
  4. If necessary, log in using the same user name and password as you use to access the OpenShift Container Platform console.
  5. In the left pane of the Jaeger dashboard, from the Service menu, select "productpage" and click the Find Traces button at the bottom of the pane. A list of traces is displayed, as shown in the following image:

    ossm jaeger main screen
  6. Click one of the traces in the list to open a detailed view of that trace. If you click on the top (most recent) trace, you see the details that correspond to the latest refresh of the `/productpage.

    ossm jaeger spans

    The trace in the previous figure consists of a few nested spans, each corresponding to a Bookinfo Service call, all performed in response to a `/productpage request. Overall processing time was 2.62s, with the details Service taking 3.56ms, the reviews Service taking 2.6s, and the ratings Service taking 5.32ms. Each of the calls to remote Services is represented by a client-side and server-side span. For example, the details client-side span is labeled productpage details.myproject.svc.cluster.local:9080. The span nested underneath it, labeled details details.myproject.svc.cluster.local:9080, corresponds to the server-side processing of the request. The trace also shows calls to istio-policy, which reflect authorization checks made by Istio.

4.6. Automatic route creation

OpenShift routes for Istio Gateways are automatically managed in Red Hat OpenShift Service Mesh. Every time an Istio Gateway is created, updated or deleted inside the service mesh, an OpenShift route is created, updated or deleted.

4.6.1. Enabling Automatic Route Creation

A Red Hat OpenShift Service Mesh control plane component called Istio OpenShift Routing (IOR) synchronizes the gateway route. Enable IOR as part of the control plane deployment.

If the Gateway contains a TLS section, the OpenShift Route will be configured to support TLS.

  1. In the ServiceMeshControlPlane resource, add the ior_enabled parameter and set it to true. For example, see the following resource snippet:
spec:
  istio:
    gateways:
     istio-egressgateway:
       autoscaleEnabled: false
       autoscaleMin: 1
       autoscaleMax: 5
     istio-ingressgateway:
       autoscaleEnabled: false
       autoscaleMin: 1
       autoscaleMax: 5
       ior_enabled: true

For more information, see Istio gateway configuration.

If the following gateway is created:

apiVersion: networking.istio.io/v1alpha3
kind: Gateway
metadata:
  name: gateway1
spec:
  selector:
    istio: ingressgateway
  servers:
  - port:
      number: 80
      name: http
      protocol: HTTP
    hosts:
    - www.bookinfo.com
    - bookinfo.example.com

Then, the following OpenShift Routes are created automatically. You can check that the routes are created with the following command.

$ oc -n <your-control-plane-namespace> get routes
NAME           HOST/PORT             PATH  SERVICES               PORT  TERMINATION   WILDCARD
gateway1-lvlfn bookinfo.example.com        istio-ingressgateway   <all>               None
gateway1-scqhv www.bookinfo.com            istio-ingressgateway   <all>               None

If the gateway is deleted, Red Hat OpenShift Service Mesh deletes the routes. However, routes created manually are never modified by Red Hat OpenShift Service Mesh.

Chapter 5. Service Mesh user guide

5.1. Traffic management

You can control the flow of traffic and API calls between services in Red Hat OpenShift Service Mesh. For example, some services in your service mesh may need to to communicate within the mesh and others may need to be hidden. Manage the traffic to hide specific backend services, expose services, create testing or versioning deployments, or add a security layer on a set of services.

This guide references the Bookinfo sample application to provide examples of routing in an example application. Install the Bookinfo application to learn how these routing examples work.

5.1.1. Routing and managing traffic

Configure your service mesh by adding your own traffic configuration to Red Hat OpenShift Service Mesh with a custom resource definitions in a YAML file.

5.1.1.1. Traffic management with virtual services

You can route requests dynamically to multiple versions of a microservice through Red Hat OpenShift Service Mesh with a virtual service. With virtual services, you can:

  • Address multiple application services through a single virtual service. If your mesh uses Kubernetes, for example, you can configure a virtual service to handle all services in a specific namespace. Mapping a single virtual service to many services is particularly useful in facilitating turning a monolithic application into a composite service built out of distinct microservices without requiring the consumers of the service to adapt to the transition.
  • Configure traffic rules in combination with gateways to control ingress and egress traffic.
5.1.1.1.1. Configuring virtual services

Requests are routed to a services within a service mesh with virtual services. Each virtual service consists of a set of routing rules that are evaluated in order. Red Hat OpenShift Service Mesh matches each given request to the virtual service to a specific real destination within the mesh.

Without virtual services, Red Hat OpenShift Service Mesh distributes traffic using round-robin load balancing between all service instances. With a virtual service, you can specify traffic behavior for one or more hostnames. Routing rules in the virtual service tell Red Hat OpenShift Service Mesh how to send the traffic for the virtual service to appropriate destinations. Route destinations can be versions of the same service or entirely different services.

The following example routes requests to different versions of a service depending on which user connects to the application. Use this command to apply this example YAML file, or one you create.

$ oc apply -f - <<EOF
apiVersion: networking.istio.io/v1alpha3
kind: VirtualService
metadata:
  name: reviews
spec:
  hosts:
  - reviews
  http:
  - match:
    - headers:
      end-user:
        exact: jason
    route:
    - destination:
      host: reviews
      subset: v2
  - route:
    - destination:
      host: reviews
      subset: v3
EOF

5.1.1.2. Configuring your virtual host

The following sections explain each field in the YAML file and explain how you can create a virtual host in a virtual service.

5.1.1.2.1. Hosts

The hosts field lists the virtual service’s user-addressable destination that these routing rules apply to. This is the address or addresses the client uses when sending requests to the service.

The virtual service hostname can be an IP address, a DNS name, or, depending on the platform, a short name that resolves to a fully qualified domain name.

spec:
  hosts:
  - reviews
5.1.1.2.2. Routing rules

The http section contains the virtual service’s routing rules, describing match conditions and actions for routing HTTP/1.1, HTTP2, and gRPC traffic sent to the destination specified in the hosts field. A routing rule consists of the destination where you want the traffic to go and zero or more match conditions, depending on your use case.

Match condition

The first routing rule in the example has a condition and begins with the match field. In this example, this routing applies to all requests from the user jason. Add the headers, end-user, and exact fields to select the appropriate requests.

spec:
  hosts:
  - reviews
  http:
  - match:
    - headers:
      end-user:
        exact: jason

Destination

The destination field in the route section specifies the actual destination for traffic that matches this condition. Unlike the virtual service’s host, the destination’s host must be a real destination that exists in the Red Hat OpenShift Service Mesh service registry. This can be a mesh service with proxies or a non-mesh service added using a service entry. In this example, the host name is a Kubernetes service name:

spec:
  hosts:
  - reviews
  http:
  - match:
    - headers:
      end-user:
        exact: jason
    route:
    - destination:
      host: reviews
      subset: v2
5.1.1.2.3. Destination rules

Destination rules are applied after virtual service routing rules are evaluated, so they apply to the traffic’s real destination. Virtual services route traffic to a destination. Destination rules configure what happens to traffic at that destination.

5.1.1.2.3.1. Load balancing options

By default, Red Hat OpenShift Service Mesh uses a round-robin load balancing policy, where each service instance in the instance pool gets a request in turn. Red Hat OpenShift Service Mesh also supports the following models, which you can specify in destination rules for requests to a particular service or service subset.

  • Random: Requests are forwarded at random to instances in the pool.
  • Weighted: Requests are forwarded to instances in the pool according to a specific percentage.
  • Least requests: Requests are forwarded to instances with the least number of requests.

Destination rule example

The following example destination rule configures three different subsets for the my-svc destination service, with different load balancing policies:

apiVersion: networking.istio.io/v1alpha3
kind: DestinationRule
metadata:
  name: my-destination-rule
spec:
  host: my-svc
  trafficPolicy:
    loadBalancer:
      simple: RANDOM
  subsets:
  - name: v1
    labels:
      version: v1
  - name: v2
    labels:
      version: v2
    trafficPolicy:
      loadBalancer:
        simple: ROUND_ROBIN
  - name: v3
    labels:
      version: v3
5.1.1.2.4. Gateways

You can use a gateway to manage inbound and outbound traffic for your mesh to specify which traffic you want to enter or leave the mesh. Gateway configurations are applied to standalone Envoy proxies that are running at the edge of the mesh, rather than sidecar Envoy proxies running alongside your service workloads.

Unlike other mechanisms for controlling traffic entering your systems, such as the Kubernetes Ingress APIs, Red Hat OpenShift Service Mesh gateways let you use the full power and flexibility of traffic routing. The Red Hat OpenShift Service Mesh gateway resource can layer 4-6 load balancing properties such as ports to expose, Red Hat OpenShift Service Mesh TLS settings. Instead of adding application-layer traffic routing (L7) to the same API resource, you can bind a regular Red Hat OpenShift Service Mesh virtual service to the gateway and manage gateway traffic like any other data plane traffic in a service mesh.

Gateways are primarily used to manage ingress traffic, but you can also configure egress gateways. An egress gateway lets you configure a dedicated exit node for the traffic leaving the mesh, letting you limit which services have access to external networks, or to enable secure control of egress traffic to add security to your mesh, for example. You can also use a gateway to configure a purely internal proxy.

Gateway example

The following example shows a possible gateway configuration for external HTTPS ingress traffic:

apiVersion: networking.istio.io/v1alpha3
kind: Gateway
metadata:
  name: ext-host-gwy
spec:
  selector:
    istio: ingressgateway # use istio default controller
  servers:
  - port:
    number: 443
    name: https
    protocol: HTTPS
    hosts:
    - ext-host.example.com
    tls:
      mode: SIMPLE
      serverCertificate: /tmp/tls.crt
      privateKey: /tmp/tls.key

This gateway configuration lets HTTPS traffic from ext-host.example.com into the mesh on port 443, but doesn’t specify any routing for the traffic.

To specify routing and for the gateway to work as intended, you must also bind the gateway to a virtual service. You do this using the virtual service’s gateways field, as shown in the following example:

apiVersion: networking.istio.io/v1alpha3
kind: VirtualService
metadata:
  name: virtual-svc
spec:
  hosts:
  - ext-host.example.com
  gateways:
    - ext-host-gwy

You can then configure the virtual service with routing rules for the external traffic.

5.1.1.2.5. Service entries

A service entry adds an entry to the service registry that Red Hat OpenShift Service Mesh maintains internally. After you add the service entry, the Envoy proxies can send traffic to the service as if it was a service in your mesh. Configuring service entries allows you to manage traffic for services running outside of the mesh, including the following tasks:

  • Redirect and forward traffic for external destinations, such as APIs consumed from the web, or traffic to services in legacy infrastructure.
  • Define retry, timeout, and fault injection policies for external destinations.
  • Run a mesh service in a Virtual Machine (VM) by adding VMs to your mesh.
  • Logically add services from a different cluster to the mesh to configure a multicluster Red Hat OpenShift Service Mesh mesh on Kubernetes.
  • You don’t need to add a service entry for every external service that you want your mesh services to use. By default, Red Hat OpenShift Service Mesh configures the Envoy proxies to passthrough requests to unknown services. However, you can’t use Red Hat OpenShift Service Mesh features to control the traffic to destinations that aren’t registered in the mesh.

Service entry examples

The following example mesh-external service entry adds the ext-resource external dependency to the Red Hat OpenShift Service Mesh service registry:

apiVersion: networking.istio.io/v1alpha3
kind: ServiceEntry
metadata:
  name: svc-entry
spec:
  hosts:
  - ext-svc.example.com
  ports:
  - number: 443
    name: https
    protocol: HTTPS
  location: MESH_EXTERNAL
  resolution: DNS

Specify the external resource using the hosts field. You can qualify it fully or use a wildcard prefixed domain name.

You can configure virtual services and destination rules to control traffic to a service entry in the same way you configure traffic for any other service in the mesh. For example, the following destination rule configures the traffic route to use mutual TLS to secure the connection to the ext-svc.example.com external service that is configured using the service entry:

apiVersion: networking.istio.io/v1alpha3
kind: DestinationRule
metadata:
  name: ext-res-dr
spec:
  host: ext-svc.example.com
  trafficPolicy:
    tls:
      mode: MUTUAL
      clientCertificate: /etc/certs/myclientcert.pem
      privateKey: /etc/certs/client_private_key.pem
      caCertificates: /etc/certs/rootcacerts.pem
5.1.1.2.6. Sidecar

By default, Red Hat OpenShift Service Mesh configures every Envoy proxy to accept traffic on all the ports of its associated workload, and to reach every workload in the mesh when forwarding traffic. You can use a sidecar configuration to do the following:

  • Fine-tune the set of ports and protocols that an Envoy proxy accepts.
  • Limit the set of services that the Envoy proxy can reach.
  • You might want to limit sidecar reachability like this in larger applications, where having every proxy configured to reach every other service in the mesh can potentially affect mesh performance due to high memory usage.

Sidecar example

You can specify that you want a sidecar configuration to apply to all workloads in a particular namespace, or choose specific workloads using a workloadSelector. For example, the following sidecar configuration configures all services in the bookinfo namespace to only reach services running in the same namespace and the Red Hat OpenShift Service Mesh control plane (currently needed to use the Red Hat OpenShift Service Mesh policy and telemetry features):

apiVersion: networking.istio.io/v1alpha3
kind: Sidecar
metadata:
  name: default
  namespace: bookinfo
spec:
  egress:
  - hosts:
    - "./*"
    - "istio-system/*"

5.1.2. Managing ingress traffic

In Red Hat OpenShift Service Mesh, the Ingress Gateway enables Service Mesh features such as monitoring, security, and route rules to be applied to traffic entering the cluster. Configure Service Mesh to expose a service outside of the service mesh using an Service Mesh gateway.

5.1.2.1. Determining the ingress IP and ports

Run the following command to determine if your Kubernetes cluster is running in an environment that supports external load balancers:

$ oc get svc istio-ingressgateway -n istio-system

That command returns the NAME, TYPE, CLUSTER-IP, EXTERNAL-IP, PORT(S), and AGE of each item in your namespace.

If the EXTERNAL-IP value is set, your environment has an external load balancer that you can use for the ingress gateway.

If the EXTERNAL-IP value is <none>, or perpetually <pending>, your environment does not provide an external load balancer for the ingress gateway. You can access the gateway using the service’s node port.

Choose the instructions for your environment:

Configuring routing with a load balancer

Follow these instructions if your environment has an external load balancer.

Set the ingress IP and ports:

$ export INGRESS_HOST=$(oc -n istio-system get service istio-ingressgateway -o jsonpath='{.status.loadBalancer.ingress[0].ip}')
$ export INGRESS_PORT=$(oc -n istio-system get service istio-ingressgateway -o jsonpath='{.spec.ports[?(@.name=="http2")].port}')
$ export SECURE_INGRESS_PORT=$(oc -n istio-system get service istio-ingressgateway -o jsonpath='{.spec.ports[?(@.name=="https")].port}')

In some environments, the load balancer may be exposed using a host name instead of an IP address. For that case, the ingress gateway’s EXTERNAL-IP value is not be an IP address. Instead, it’s a host name, and the previous command fails to set the INGRESS_HOST environment variable.

Use the following command to correct the INGRESS_HOST value:

$ export INGRESS_HOST=$(oc -n istio-system get service istio-ingressgateway -o jsonpath='{.status.loadBalancer.ingress[0].hostname}')

Configuring routing without a load balancer

Follow these instructions if your environment does not have an external load balancer. You must use a node port instead.

Set the ingress ports:

$ export INGRESS_PORT=$(oc -n istio-system get service istio-ingressgateway -o jsonpath='{.spec.ports[?(@.name=="http2")].nodePort}')
$ export SECURE_INGRESS_PORT=$(oc -n istio-system get service istio-ingressgateway -o jsonpath='{.spec.ports[?(@.name=="https")].nodePort}')

5.1.3. Routing example using the bookinfo application

The Service Mesh Bookinfo sample application consists of four separate microservices, each with multiple versions. Three different versions, one of the microservices called reviews, have been deployed and are running concurrently.

Prerequisites:

  • Deploy the Bookinfo sample application to work with the following examples.

About this task

To illustrate the problem this causes, access the bookinfo app /product page in a browser and refresh several times.

Sometimes the book review output contains star ratings and other times it does not. Without an explicit default service version to route to, Service Mesh routes requests to all available versions one after the other.

This tutorial helps you apply rules that route all traffic to v1 (version 1) of the microservices. Later, you can apply a rule to route traffic based on the value of an HTTP request header.

5.1.3.1. Applying a virtual service

To route to one version only, apply virtual services that set the default version for the micro-services. In the following example, the virtual service routes all traffic to v1 of each micro-service

  1. Run the following command to apply the virtual services:

    $ oc apply -f https://raw.githubusercontent.com/Maistra/istio/maistra-1.1/samples/bookinfo/networking/virtual-service-all-v1.yaml
  2. To test the command was successful, display the defined routes with the following command:

    $ oc get virtualservices -o yaml

    That command returns the following YAML file.

    apiVersion: networking.istio.io/v1alpha3
    kind: VirtualService
    metadata:
      name: details
      ...
    spec:
      hosts:
      - details
      http:
      - route:
        - destination:
          host: details
          subset: v1
    ---
    apiVersion: networking.istio.io/v1alpha3
    kind: VirtualService
    metadata:
      name: productpage
      ...
    spec:
      gateways:
      - bookinfo-gateway
      - mesh
      hosts:
      - productpage
      http:
      - route:
        - destination:
          host: productpage
          subset: v1
    ---
    apiVersion: networking.istio.io/v1alpha3
    kind: VirtualService
    metadata:
      name: ratings
      ...
    spec:
      hosts:
      - ratings
      http:
      - route:
        - destination:
          host: ratings
          subset: v1
    ---
    apiVersion: networking.istio.io/v1alpha3
    kind: VirtualService
    metadata:
      name: reviews
      ...
    spec:
      hosts:
      - reviews
      http:
      - route:
        - destination:
          host: reviews
          subset: v1

    You have configured Service Mesh to route to the v1 version of the Bookinfo microservices, most importantly the reviews service version 1.

5.1.3.2. Test the new routing configuration

You can easily test the new configuration by once again refreshing the /productpage of the Bookinfo app.

  1. Open the Bookinfo site in your browser. The URL is http://$GATEWAY_URL/productpage, where $GATEWAY_URL is the External IP address of the ingress.

    The reviews part of the page displays with no rating stars, no matter how many times you refresh. This is because you configured Service Mesh to route all traffic for the reviews service to the version reviews:v1 and this version of the service does not access the star ratings service.

    Your service mesh now routes traffic to one version of a service.

5.1.3.3. Route based on user identity

Next, change the route configuration so that all traffic from a specific user is routed to a specific service version. In this case, all traffic from a user named jason will be routed to the service reviews:v2.

Note that Service Mesh doesn’t have any special, built-in understanding of user identity. This example is enabled by the fact that the productpage service adds a custom end-user header to all outbound HTTP requests to the reviews service.

  1. Run the following command to enable user-based routing:

    $ oc apply -f https://raw.githubusercontent.com/Maistra/istio/maistra-1.1/samples/bookinfo/networking/virtual-service-reviews-test-v2.yaml
  2. Confirm the rule is created:

    $ oc get virtualservice reviews -o yaml

    That command returns the following YAML file.

    apiVersion: networking.istio.io/v1alpha3
    kind: VirtualService
    metadata:
      name: reviews
      ...
    spec:
      hosts:
      - reviews
      http:
      - match:
        - headers:
          end-user:
            exact: jason
        route:
        - destination:
          host: reviews
          subset: v2
      - route:
        - destination:
          host: reviews
          subset: v1
  3. On the /productpage of the Bookinfo app, log in as user jason. Refresh the browser. What do you see? The star ratings appear next to each review.
  4. Log in as another user (pick any name you wish). Refresh the browser. Now the stars are gone. This is because traffic is routed to reviews:v1 for all users except Jason.

You have successfully configured Service Mesh to route traffic based on user identity.

Chapter 6. Support

6.1. Collecting Red Hat OpenShift Service Mesh data for Red Hat Support

When opening a support case, it is helpful to provide debugging information about your cluster to Red Hat Support.

The must-gather tool enables you to collect diagnostic information about your OpenShift Container Platform cluster, including virtual machines and other data related to Red Hat OpenShift Service Mesh.

For prompt support, supply diagnostic information for both OpenShift Container Platform and Red Hat OpenShift Service Mesh.

6.1.1. About the must-gather tool

The oc adm must-gather CLI command collects the information from your cluster that is most likely needed for debugging issues, such as:

  • Resource definitions
  • Audit logs
  • Service logs

You can specify one or more images when you run the command by including the --image argument. When you specify an image, the tool collects data related to that feature or product.

When you run oc adm must-gather, a new Pod is created on the cluster. The data is collected on that Pod and saved in a new directory that starts with must-gather.local. This directory is created in the current working directory.

Prerequisites

  • Access to the cluster as a user with the cluster-admin role.
  • The OpenShift Container Platform CLI (oc) installed.

6.1.2. About collecting service mesh data

You can use the oc adm must-gather CLI command to collect information about your cluster, including features and objects associated with Red Hat OpenShift Service Mesh.

To collect Red Hat OpenShift Service Mesh data with must-gather, you must specify the Red Hat OpenShift Service Mesh image:

$ oc adm must-gather --image=registry.redhat.io/openshift-service-mesh/istio-must-gather-rhel7

Chapter 7. 3scale adapter

7.1. Using the 3scale Istio adapter

The 3scale Istio Adapter is an optional adapter that allows you to label a service running within the Red Hat OpenShift Service Mesh and integrate that service with the 3scale API Management solution. It is not required for Red Hat OpenShift Service Mesh.

7.1.1. Integrate the 3scale adapter with Red Hat OpenShift Service Mesh

You can use these examples to configure requests to your services using the 3scale Istio Adapter.

Prerequisites:

  • Red Hat OpenShift Service Mesh 0.12.0+
  • A working 3scale account (SaaS or 3scale 2.5 On-Premises)
  • Red Hat OpenShift Service Mesh prerequisites
  • Ensure Mixer policy enforcement is enabled. Update Mixer policy enforcement section provides instructions to check the current Mixer policy enforcement status and enable policy enforcement.
Note

To configure the 3scale Istio Adapter, refer to Red Hat OpenShift Service Mesh custom resources for instructions on adding adapter parameters to the custom resource file.

Note

Pay particular attention to the kind: handler resource. You must update this with your 3scale credentials and the service ID of the API you want to manage.

  1. Modify the handler configuration with your 3scale configuration.

    Handler configuration example

      apiVersion: "config.istio.io/v1alpha2"
      kind: handler
      metadata:
       name: threescale
      spec:
       adapter: threescale
       params:
         service_id: "<SERVICE_ID>"
         system_url: "https://<organization>-admin.3scale.net/"
         access_token: "<ACCESS_TOKEN>"
       connection:
         address: "threescale-istio-adapter:3333"

Optionally, you can provide a backend_url field within the params section to override the URL provided by the 3scale configuration. This may be useful if the adapter runs on the same cluster as the 3scale on-premise instance, and you wish to leverage the internal cluster DNS.

  1. Modify the rule configuration with your 3scale configuration to dispatch the rule to the threescale handler.

    Rule configuration example

      apiVersion: "config.istio.io/v1alpha2"
      kind: rule
      metadata:
        name: threescale
      spec:
        match: destination.labels["service-mesh.3scale.net"] == "true"
        actions:
          - handler: threescale.handler
            instances:
              - threescale-authorization.instance

7.1.1.1. Generating 3scale custom resources

The adapter includes a tool that allows you to generate the handler, instance, and rule custom resources.

Table 7.1. Usage

OptionDescriptionRequiredDefault value

-h, --help

Produces help output for available options

No

 

--name

Unique name for this URL, token pair

Yes

 

-n, --namespace

Namespace to generate templates

No

istio-system

-t, --token

3scale access token

Yes

 

-u, --url

3scale Admin Portal URL

Yes

 

--backend-url

3scale backend URL. If set, it overrides the value that is read from system configuration

No

 

-s, --service

3scale API/Service ID

No

 

--auth

3scale authentication pattern to specify (1=Api Key, 2=App Id/App Key, 3=OIDC)

No

Hybrid

-o, --output

File to save produced manifests to

No

Standard output

--version

Outputs the CLI version and exits immediately

No

 
7.1.1.1.1. Generate templates from URL examples
  • This example generates templates allowing the token, URL pair to be shared by multiple services as a single handler:

    $ 3scale-gen-config --name=admin-credentials --url="https://<organization>-admin.3scale.net:443" --token="[redacted]"
  • This example generates the templates with the service ID embedded in the handler:

    $ 3scale-gen-config --url="https://<organization>-admin.3scale.net" --name="my-unique-id" --service="123456789" --token="[redacted]"

7.1.1.2. Generating manifests from a deployed adapter

  1. Run this command to generate manifests from a deployed adapter in the istio-system namespace:

    $ export NS="istio-system" URL="https://replaceme-admin.3scale.net:443" NAME="name" TOKEN="token"
    oc exec -n ${NS} $(oc get po -n ${NS} -o jsonpath='{.items[?(@.metadata.labels.app=="3scale-istio-adapter")].metadata.name}') \
    -it -- ./3scale-config-gen \
    --url ${URL} --name ${NAME} --token ${TOKEN} -n ${NS}
  2. This will produce sample output to the terminal. Edit these samples if required and create the objects using the oc create command.
  3. When the request reaches the adapter, the adapter needs to know how the service maps to an API on 3scale. You can provide this information in two ways:

    1. Label the workload (recommended)
    2. Hard code the handler as service_id
  4. Update the workload with the required annotations:

    Note

    You only need to update the service ID provided in this example if it is not already embedded in the handler. The setting in the handler takes precedence.

    $ export CREDENTIALS_NAME="replace-me"
    export SERVICE_ID="replace-me"
    export DEPLOYMENT="replace-me"
    patch="$(oc get deployment "${DEPLOYMENT}"
    patch="$(oc get deployment "${DEPLOYMENT}" --template='{"spec":{"template":{"metadata":{"labels":{ {{ range $k,$v := .spec.template.metadata.labels }}"{{ $k }}":"{{ $v }}",{{ end }}"service-mesh.3scale.net/service-id":"'"${SERVICE_ID}"'","service-mesh.3scale.net/credentials":"'"${CREDENTIALS_NAME}"'"}}}}}' )"
    oc patch deployment "${DEPLOYMENT}" --patch ''"${patch}"''

7.1.1.3. Routing service traffic through the adapter

Follow these steps to drive traffic for your service through the 3scale adapter.

Prerequisites

  • Credentials and service ID from your 3scale administrator.

Procedure

  1. Match the rule destination.labels["service-mesh.3scale.net/credentials"] == "threescale" that you previously created in the configuration, in the kind: rule resource.
  2. Add the above label to PodTemplateSpec on the Deployment of the target workload to integrate a service. the value, threescale, refers to the name of the generated handler. This handler stores the access token required to call 3scale.
  3. Add the destination.labels["service-mesh.3scale.net/service-id"] == "replace-me" label to the workload to pass the service ID to the adapter via the instance at request time.

7.1.2. Configure the integration settings in 3scale

Follow this procedure to configure the 3scale integration settings.

Note

For 3scale SaaS customers, Red Hat OpenShift Service Mesh is enabled as part of the Early Access program.

Procedure

  1. Navigate to [your_API_name]IntegrationConfiguration.
  2. At the top of the Integration page click on edit integration settings in the top right corner.
  3. Under the Service Mesh heading, click the Istio option.
  4. Scroll to the bottom of the page and click Update Service.

7.1.3. Caching behavior

Responses from 3scale System APIs are cached by default within the adapter. Entries will be purged from the cache when they become older than the cacheTTLSeconds value. Also by default, automatic refreshing of cached entries will be attempted seconds before they expire, based on the cacheRefreshSeconds value. You can disable automatic refreshing by setting this value higher than the cacheTTLSeconds value.

Caching can be disabled entirely by setting cacheEntriesMax to a non-positive value.

By using the refreshing process, cached values whose hosts become unreachable will be retried before eventually being purged when past their expiry.

7.1.4. Authenticating requests

This release supports the following authentication methods:

  • Standard API Keys: single randomized strings or hashes acting as an identifier and a secret token.
  • Application identifier and key pairs: immutable identifier and mutable secret key strings.
  • OpenID authentication method: client ID string parsed from the JSON Web Token.

7.1.4.1. Applying authentication patterns

Modify the instance custom resource, as illustrated in the following authentication method examples, to configure authentication behavior. You can accept the authentication credentials from:

  • Request headers
  • Request parameters
  • Both request headers and query parameters
Note

When specifying values from headers, they must be lower case. For example, if you want to send a header as User-Key, this must be referenced in the configuration as request.headers["user-key"].

7.1.4.1.1. API key authentication method

Service Mesh looks for the API key in query parameters and request headers as specified in the user option in the subject custom resource parameter. It checks the values in the order given in the custom resource file. You can restrict the search for the API key to either query parameters or request headers by omitting the unwanted option.

In this example, Service Mesh looks for the API key in the user_key query parameter. If the API key is not in the query parameter, Service Mesh then checks the user-key header.

API key authentication method example

apiVersion: "config.istio.io/v1alpha2"
kind: instance
metadata:
  name: threescale-authorization
  namespace: istio-system
spec:
  template: authorization
  params:
    subject:
      user: request.query_params["user_key"] | request.headers["user-key"] | ""
    action:
      path: request.url_path
      method: request.method | "get"

If you want the adapter to examine a different query parameter or request header, change the name as appropriate. For example, to check for the API key in a query parameter named “key”, change request.query_params["user_key"] to request.query_params["key"].

7.1.4.1.2. Application ID and application key pair authentication method

Service Mesh looks for the application ID and application key in query parameters and request headers, as specified in the properties option in the subject custom resource parameter. The application key is optional. It checks the values in the order given in the custom resource file. You can restrict the search for the credentials to either query parameters or request headers by not including the unwanted option.

In this example, Service Mesh looks for the application ID and application key in the query parameters first, moving on to the request headers if needed.

Application ID and application key pair authentication method example

apiVersion: "config.istio.io/v1alpha2"
kind: instance
metadata:
  name: threescale-authorization
  namespace: istio-system
spec:
  template: authorization
  params:
    subject:
        app_id: request.query_params["app_id"] | request.headers["app-id"] | ""
        app_key: request.query_params["app_key"] | request.headers["app-key"] | ""
    action:
      path: request.url_path
      method: request.method | "get"

If you want the adapter to examine a different query parameter or request header, change the name as appropriate. For example, to check for the application ID in a query parameter named identification, change request.query_params["app_id"] to request.query_params["identification"].

7.1.4.1.3. OpenID authentication method

To use the OpenID Connect (OIDC) authentication method, use the properties value on the subject field to set client_id, and optionally app_key.

You can manipulate this object using the methods described previously. In the example configuration shown below, the client identifier (application ID) is parsed from the JSON Web Token (JWT) under the label azp. You can modify this as needed.

OpenID authentication method example

  apiVersion: "config.istio.io/v1alpha2"
  kind: instance
  metadata:
    name: threescale-authorization
  spec:
    template: threescale-authorization
    params:
      Subject:
  properties:
          app_key: request.query_params["app_key"] | request.headers["app-key"] | ""
          client_id: request.auth.claims["azp"] | ""
      action:
        path: request.url_path
        method: request.method | "get"
          service: destination.labels["service-mesh.3scale.net/service-id"] | ""

For this integration to work correctly, OIDC must still be done in 3scale for the client to be created in the identity provider (IdP). You should create end-user authentication for the service you want to protect in the same namespace as that service. The JWT is passed in the Authorization header of the request.

In the sample Policy defined below, replace issuer and jwksUri as appropriate.

OpenID Policy example

  apiVersion: authentication.istio.io/v1alpha1
  kind: Policy
  metadata:
    name: jwt-example
    namespace: bookinfo
  spec:
    origins:
      - jwt:
          issuer: >-
            http://keycloak-keycloak.34.242.107.254.nip.io/auth/realms/3scale-keycloak
          jwksUri: >-
  http://keycloak-keycloak.34.242.107.254.nip.io/auth/realms/3scale-keycloak/protocol/openid-connect/certs
    principalBinding: USE_ORIGIN
    targets:
      - name: productpage

7.1.4.1.4. Hybrid authentication method

You can choose to not enforce a particular authentication method and accept any valid credentials for either method. If both an API key and an application ID/application key pair are provided, Service Mesh uses the API key.

In this example, Service Mesh checks for an API key in the query parameters, then the request headers. If there is no API key, it then checks for an application ID and key in the query parameters, then the request headers.

Hybrid authentication method example

apiVersion: "config.istio.io/v1alpha2"
kind: instance
metadata:
  name: threescale-authorization
spec:
  template: authorization
  params:
    subject:
      user: request.query_params["user_key"] | request.headers["user-key"] |
      properties:
        app_id: request.query_params["app_id"] | request.headers["app-id"] | ""
        app_key: request.query_params["app_key"] | request.headers["app-key"] | ""
        client_id: request.auth.claims["azp"] | ""
    action:
      path: request.url_path
      method: request.method | "get"
        service: destination.labels["service-mesh.3scale.net/service-id"] | ""

7.1.5. 3scale Adapter metrics

The adapter, by default reports various Prometheus metrics that are exposed on port 8080 at the /metrics endpoint. These metrics provide insight into how the interactions between the adapter and 3scale are performing. The service is labeled to be automatically discovered and scraped by Prometheus.

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