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Chapter 5. Using AMQ Streams Operators

Use the AMQ Streams operators to manage your Kafka cluster, and Kafka topics and users.

5.1. Using the Cluster Operator
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The Cluster Operator is used to deploy a Kafka cluster and other Kafka components.

The Cluster Operator is deployed using YAML installation files.

Note

On OpenShift, a Kafka Connect deployment can incorporate a Source2Image feature to provide a convenient way to add additional connectors.

5.1.1. Cluster Operator configuration
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You can configure the Cluster Operator using supported environment variables, and through its logging configuration.

The environment variables relate to container configuration for the deployment of the Cluster Operator image. For more information on image configuration, see, Section 13.1.6, “image”.

STRIMZI_NAMESPACE

A comma-separated list of namespaces that the operator should operate in. When not set, set to empty string, or set to *, the Cluster Operator will operate in all namespaces. The Cluster Operator deployment might use the OpenShift Downward API to set this automatically to the namespace the Cluster Operator is deployed in.

Example configuration for Cluster Operator namespaces

env:
  - name: STRIMZI_NAMESPACE
    valueFrom:
      fieldRef:
        fieldPath: metadata.namespace
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STRIMZI_FULL_RECONCILIATION_INTERVAL_MS
Optional, default is 120000 ms. The interval between periodic reconciliations, in milliseconds.
STRIMZI_OPERATION_TIMEOUT_MS
Optional, default 300000 ms. The timeout for internal operations, in milliseconds. This value should be increased when using AMQ Streams on clusters where regular OpenShift operations take longer than usual (because of slow downloading of Docker images, for example).
STRIMZI_OPERATIONS_THREAD_POOL_SIZE
Optional, default 10 The worker thread pool size, which is used for various asynchronous and blocking operations that are run by the cluster operator.
STRIMZI_OPERATOR_NAMESPACE

The name of the namespace where the AMQ Streams Cluster Operator is running. Do not configure this variable manually. Use the OpenShift Downward API. 

env:
  - name: STRIMZI_OPERATOR_NAMESPACE
    valueFrom:
      fieldRef:
        fieldPath: metadata.namespace
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STRIMZI_OPERATOR_NAMESPACE_LABELS

Optional. The labels of the namespace where the AMQ Streams Cluster Operator is running. Namespace labels are used to configure the namespace selector in network policies to allow the AMQ Streams Cluster Operator to only have access to the operands from the namespace with these labels. When not set, the namespace selector in network policies is configured to allow access to the AMQ Streams Cluster Operator from any namespace in the OpenShift cluster. 

env:
  - name: STRIMZI_OPERATOR_NAMESPACE_LABELS
    value: label1=value1,label2=value2
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STRIMZI_CUSTOM_RESOURCE_SELECTOR

Optional. Specifies label selector used to filter the custom resources handled by the operator. The operator will operate only on those custom resources which will have the specified labels set. Resources without these labels will not be seen by the operator. The label selector applies to Kafka, KafkaConnect, KafkaConnectS2I, KafkaBridge, KafkaMirrorMaker, and KafkaMirrorMaker2 resources. KafkaRebalance and KafkaConnector resources will be operated only when their corresponding Kafka and Kafka Connect clusters have the matching labels. 

env:
  - name: STRIMZI_CUSTOM_RESOURCE_SELECTOR
    value: label1=value1,label2=value2
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STRIMZI_LABELS_EXCLUSION_PATTERN

Optional, default regex pattern is ^app.kubernetes.io/(?!part-of).*. Specifies regex exclusion pattern used to filter labels propagation from the main custom resource to its subresources. The labels exclusion filter is not applied to labels in template sections such as spec.kafka.template.pod.metadata.labels. 

env:
  - name: STRIMZI_LABELS_EXCLUSION_PATTERN
    value: "^key1.*"
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STRIMZI_KAFKA_IMAGES
Required. This provides a mapping from Kafka version to the corresponding Docker image containing a Kafka broker of that version. The required syntax is whitespace or comma separated <version>=<image> pairs. For example 2.7.0=registry.redhat.io/amq7/amq-streams-kafka-27-rhel8:1.8.4, 2.8.0=registry.redhat.io/amq7/amq-streams-kafka-28-rhel8:1.8.4. This is used when a Kafka.spec.kafka.version property is specified but not the Kafka.spec.kafka.image in the Kafka resource.
STRIMZI_DEFAULT_KAFKA_INIT_IMAGE
Optional, default registry.redhat.io/amq7/amq-streams-rhel8-operator:1.8.4. The image name to use as default for the init container started before the broker for initial configuration work (that is, rack support), if no image is specified as the kafka-init-image in the Kafka resource.
STRIMZI_KAFKA_CONNECT_IMAGES
Required. This provides a mapping from the Kafka version to the corresponding Docker image containing a Kafka connect of that version. The required syntax is whitespace or comma separated <version>=<image> pairs. For example 2.7.0=registry.redhat.io/amq7/amq-streams-kafka-27-rhel8:1.8.4, 2.8.0=registry.redhat.io/amq7/amq-streams-kafka-28-rhel8:1.8.4. This is used when a KafkaConnect.spec.version property is specified but not the KafkaConnect.spec.image.
STRIMZI_KAFKA_CONNECT_S2I_IMAGES
Required. This provides a mapping from the Kafka version to the corresponding Docker image containing a Kafka connect of that version. The required syntax is whitespace or comma separated <version>=<image> pairs. For example 2.7.0=registry.redhat.io/amq7/amq-streams-kafka-27-rhel8:1.8.4, 2.8.0=registry.redhat.io/amq7/amq-streams-kafka-28-rhel8:1.8.4. This is used when a KafkaConnectS2I.spec.version property is specified but not the KafkaConnectS2I.spec.image.
STRIMZI_KAFKA_MIRROR_MAKER_IMAGES
Required. This provides a mapping from the Kafka version to the corresponding Docker image containing a Kafka mirror maker of that version. The required syntax is whitespace or comma separated <version>=<image> pairs. For example 2.7.0=registry.redhat.io/amq7/amq-streams-kafka-27-rhel8:1.8.4, 2.8.0=registry.redhat.io/amq7/amq-streams-kafka-28-rhel8:1.8.4. This is used when a KafkaMirrorMaker.spec.version property is specified but not the KafkaMirrorMaker.spec.image.
STRIMZI_DEFAULT_TOPIC_OPERATOR_IMAGE
Optional, default registry.redhat.io/amq7/amq-streams-rhel8-operator:1.8.4. The image name to use as the default when deploying the topic operator, if no image is specified as the Kafka.spec.entityOperator.topicOperator.image in Kafka resource.
STRIMZI_DEFAULT_USER_OPERATOR_IMAGE
Optional, default registry.redhat.io/amq7/amq-streams-rhel8-operator:1.8.4. The image name to use as the default when deploying the user operator, if no image is specified as the Kafka.spec.entityOperator.userOperator.image in the Kafka resource.
STRIMZI_DEFAULT_TLS_SIDECAR_ENTITY_OPERATOR_IMAGE
Optional, default registry.redhat.io/amq7/amq-streams-kafka-28-rhel8:1.8.4. The image name to use as the default when deploying the sidecar container which provides TLS support for the Entity Operator, if no image is specified as the Kafka.spec.entityOperator.tlsSidecar.image in the Kafka resource.
STRIMZI_IMAGE_PULL_POLICY
Optional. The ImagePullPolicy which will be applied to containers in all pods managed by AMQ Streams Cluster Operator. The valid values are Always, IfNotPresent, and Never. If not specified, the OpenShift defaults will be used. Changing the policy will result in a rolling update of all your Kafka, Kafka Connect, and Kafka MirrorMaker clusters.
STRIMZI_IMAGE_PULL_SECRETS
Optional. A comma-separated list of Secret names. The secrets referenced here contain the credentials to the container registries where the container images are pulled from. The secrets are used in the imagePullSecrets field for all Pods created by the Cluster Operator. Changing this list results in a rolling update of all your Kafka, Kafka Connect, and Kafka MirrorMaker clusters.
STRIMZI_KUBERNETES_VERSION

Optional. Overrides the Kubernetes version information detected from the API server.

Example configuration for Kubernetes version override

env:
  - name: STRIMZI_KUBERNETES_VERSION
    value: |
           major=1
           minor=16
           gitVersion=v1.16.2
           gitCommit=c97fe5036ef3df2967d086711e6c0c405941e14b
           gitTreeState=clean
           buildDate=2019-10-15T19:09:08Z
           goVersion=go1.12.10
           compiler=gc
           platform=linux/amd64
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KUBERNETES_SERVICE_DNS_DOMAIN

Optional. Overrides the default OpenShift DNS domain name suffix.

By default, services assigned in the OpenShift cluster have a DNS domain name that uses the default suffix cluster.local.

For example, for broker kafka-0: 

<cluster-name>-kafka-0.<cluster-name>-kafka-brokers.<namespace>.svc.cluster.local
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The DNS domain name is added to the Kafka broker certificates used for hostname verification.

If you are using a different DNS domain name suffix in your cluster, change the KUBERNETES_SERVICE_DNS_DOMAIN environment variable from the default to the one you are using in order to establish a connection with the Kafka brokers.

STRIMZI_CONNECT_BUILD_TIMEOUT_MS
Optional, default 300000 ms. The timeout for building new Kafka Connect images with additional connectots, in milliseconds. This value should be increased when using AMQ Streams to build container images containing many connectors or using a slow container registry.
STRIMZI_FEATURE_GATES
Optional. Enables or disables features and functionality controlled by feature gates. For more information about each feature gate, see Section 5.1.1.1, “Feature gates”.

5.1.1.1. Feature gates
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AMQ Streams operators support feature gates to enable or disable certain features and functionality. Enabling a feature gate changes the behavior of the relevant operator and introduces the feature to your AMQ Streams deployment.

Feature gates have a default state of either enabled or disabled. To modify a feature gate’s default state, use the STRIMZI_FEATURE_GATES environment variable in the operator’s configuration. You can modify multiple feature gates using this single environment variable.

Feature gates have three stages of maturity:

  • Alpha — typically disabled by default
  • Beta — typically enabled by default
  • General Availability (GA) — typically enabled by default

Alpha stage features might be experimental or unstable, subject to change, or not sufficiently tested for production use. Beta stage features are well tested and their functionality is not likely to change. GA stage features are stable and should not change in future. Alpha and beta stage features are removed if they do not prove to be useful.

Note

Feature gates might be removed when they reach GA. This means that the feature was incorporated into the AMQ Streams core features and can no longer be disabled.

Expand
Table 5.1. All feature gates and the AMQ Streams versions when they moved to alpha, beta, or GA
Feature gateAlphaBetaGA

ControlPlaneListener

1.8

-

-

ServiceAccountPatching

1.8

-

-

Configuring feature gates

You configure feature gates using the STRIMZI_FEATURE_GATES environment variable in the operator’s configuration. Specify a comma-separated list of feature gate names and prefixes. A + prefix enables the feature gate and a - prefix disables it.

Example feature gate configuration that enables FeatureGate1 and disables FeatureGate2

env:
  - name: STRIMZI_FEATURE_GATES
    value: +FeatureGate1,-FeatureGate2
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5.1.1.1.1. Control plane listener feature gate
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Use the ControlPlaneListener feature gate to change the communication paths used for inter-broker communications within your Kafka cluster.

The OpenShift control plane manages the workloads running on the worker nodes. Services such as the Kubernetes API server and the controller manager run on the control plane. The OpenShift data plane provides resources to containers, including CPU, memory, network, and storage.

In AMQ Streams, control plane traffic consists of controller connections that maintain the desired state of the Kafka cluster. Data plane traffic mainly consists of data replication between the leader broker and the follower brokers.

When the ControlPlaneListener feature gate is disabled, control plane and data plane traffic go through the same internal listener on port 9091. This was the default behavior before the feature gate was introduced.

When ControlPlaneListener is enabled, control plane traffic goes through a dedicated control plane listener on port 9090. Data plane traffic continues to use the internal listener on port 9091.

Using control plane listeners might improve performance because important controller connections, such as partition leadership changes, are not delayed by data replication across brokers.

Enabling the control plane listener feature gate

The ControlPlaneListener feature gate is in the alpha stage and has a default state of disabled. To enable it, specify +ControlPlaneListener in the STRIMZI_FEATURE_GATES environment variable in the Cluster Operator configuration.

This feature gate must be disabled when:

  • Upgrading from AMQ Streams 1.7 and earlier
  • Downgrading to AMQ Streams 1.7 and earlier
Note

The ControlPlaneListener feature gate was introduced in AMQ Streams 1.8 and is expected to remain in the alpha stage for a number of releases before moving to the beta stage.

5.1.1.1.2. Service Account patching feature gate
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By default, the Cluster Operator does not update service accounts. To allow the Cluster Operator to apply updates, enable the ServiceAccountPatching feature gate.

Add +ServiceAccountPatching to the STRIMZI_FEATURE_GATES environment variable in the Cluster Operator configuration.

The feature gate is currently in the alpha phase and disabled by default. With the feature gate enabled, the Cluster Operator applies updates to service account configuration in every reconciliation. For example, you can change service account labels and annotations after the operands are already created.

Note

The ServiceAccountPatching feature gate was introduced in AMQ Streams 1.8 and is expected to remain in the alpha phase for a number of releases before it moves to the beta phase and is enabled by default.

5.1.1.2. Logging configuration by ConfigMap
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The Cluster Operator’s logging is configured by the strimzi-cluster-operator ConfigMap.

A ConfigMap containing logging configuration is created when installing the Cluster Operator. This ConfigMap is described in the file install/cluster-operator/050-ConfigMap-strimzi-cluster-operator.yaml. You configure Cluster Operator logging by changing the data field log4j2.properties in this ConfigMap.

To update the logging configuration, you can edit the 050-ConfigMap-strimzi-cluster-operator.yaml file and then run the following command: 

oc create -f install/cluster-operator/050-ConfigMap-strimzi-cluster-operator.yaml
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Alternatively, edit the ConfigMap directly: 

oc edit configmap strimzi-cluster-operator
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To change the frequency of the reload interval, set a time in seconds in the monitorInterval option in the created ConfigMap.

If the ConfigMap is missing when the Cluster Operator is deployed, the default logging values are used.

If the ConfigMap is accidentally deleted after the Cluster Operator is deployed, the most recently loaded logging configuration is used. Create a new ConfigMap to load a new logging configuration.

Note

Do not remove the monitorInterval option from the ConfigMap.

The Cluster Operator can run in the same namespace as the resources it manages, or in a separate namespace. By default, the STRIMZI_OPERATOR_NAMESPACE environment variable is configured to use the OpenShift Downward API to find which namespace the Cluster Operator is running in. If the Cluster Operator is running in the same namespace as the resources, only local access is required, and allowed by AMQ Streams.

If the Cluster Operator is running in a separate namespace to the resources it manages, any namespace in the OpenShift cluster is allowed access to the Cluster Operator unless network policy is configured. Use the optional STRIMZI_OPERATOR_NAMESPACE_LABELS environment variable to establish network policy for the Cluster Operator using namespace labels. By adding namespace labels, access to the Cluster Operator is restricted to the namespaces specified.

Network policy configured for the Cluster Operator deployment

#...
env:
  # ...
  - name: STRIMZI_OPERATOR_NAMESPACE_LABELS
    value: label1=value1,label2=value2
  #...
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5.1.1.4. Periodic reconciliation
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Although the Cluster Operator reacts to all notifications about the desired cluster resources received from the OpenShift cluster, if the operator is not running, or if a notification is not received for any reason, the desired resources will get out of sync with the state of the running OpenShift cluster.

In order to handle failovers properly, a periodic reconciliation process is executed by the Cluster Operator so that it can compare the state of the desired resources with the current cluster deployments in order to have a consistent state across all of them. You can set the time interval for the periodic reconciliations using the [STRIMZI_FULL_RECONCILIATION_INTERVAL_MS] variable.

For the Cluster Operator to function it needs permission within the OpenShift cluster to interact with resources such as Kafka, KafkaConnect, and so on, as well as the managed resources, such as ConfigMaps, Pods, Deployments, StatefulSets and Services. Such permission is described in terms of OpenShift role-based access control (RBAC) resources:

  • ServiceAccount,
  • Role and ClusterRole,
  • RoleBinding and ClusterRoleBinding.

In addition to running under its own ServiceAccount with a ClusterRoleBinding, the Cluster Operator manages some RBAC resources for the components that need access to OpenShift resources.

OpenShift also includes privilege escalation protections that prevent components operating under one ServiceAccount from granting other ServiceAccounts privileges that the granting ServiceAccount does not have. Because the Cluster Operator must be able to create the ClusterRoleBindings, and RoleBindings needed by resources it manages, the Cluster Operator must also have those same privileges.

5.1.2.1. Delegated privileges
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When the Cluster Operator deploys resources for a desired Kafka resource it also creates ServiceAccounts, RoleBindings, and ClusterRoleBindings, as follows:

  • The Kafka broker pods use a ServiceAccount called cluster-name-kafka

    • When the rack feature is used, the strimzi-cluster-name-kafka-init ClusterRoleBinding is used to grant this ServiceAccount access to the nodes within the cluster via a ClusterRole called strimzi-kafka-broker
    • When the rack feature is not used and the cluster is not exposed via nodeport, no binding is created
  • The ZooKeeper pods use a ServiceAccount called cluster-name-zookeeper

  • The Entity Operator pod uses a ServiceAccount called cluster-name-entity-operator

    • The Topic Operator produces OpenShift events with status information, so the ServiceAccount is bound to a ClusterRole called strimzi-entity-operator which grants this access via the strimzi-entity-operator RoleBinding
  • The pods for KafkaConnect and KafkaConnectS2I resources use a ServiceAccount called cluster-name-cluster-connect
  • The pods for KafkaMirrorMaker use a ServiceAccount called cluster-name-mirror-maker
  • The pods for KafkaMirrorMaker2 use a ServiceAccount called cluster-name-mirrormaker2
  • The pods for KafkaBridge use a ServiceAccount called cluster-name-bridge

5.1.2.2. ServiceAccount
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The Cluster Operator is best run using a ServiceAccount:

Example ServiceAccount for the Cluster Operator

apiVersion: v1
kind: ServiceAccount
metadata:
  name: strimzi-cluster-operator
  labels:
    app: strimzi
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The Deployment of the operator then needs to specify this in its spec.template.spec.serviceAccountName:

Partial example of Deployment for the Cluster Operator

apiVersion: apps/v1
kind: Deployment
metadata:
  name: strimzi-cluster-operator
  labels:
    app: strimzi
spec:
  replicas: 1
  selector:
    matchLabels:
      name: strimzi-cluster-operator
      strimzi.io/kind: cluster-operator
  template:
      # ...
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Note line 12, where the strimzi-cluster-operator ServiceAccount is specified as the serviceAccountName.

5.1.2.3. ClusterRoles
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The Cluster Operator needs to operate using ClusterRoles that gives access to the necessary resources. Depending on the OpenShift cluster setup, a cluster administrator might be needed to create the ClusterRoles.

Note

Cluster administrator rights are only needed for the creation of the ClusterRoles. The Cluster Operator will not run under the cluster admin account.

The ClusterRoles follow the principle of least privilege and contain only those privileges needed by the Cluster Operator to operate Kafka, Kafka Connect, and ZooKeeper clusters. The first set of assigned privileges allow the Cluster Operator to manage OpenShift resources such as StatefulSets, Deployments, Pods, and ConfigMaps.

Cluster Operator uses ClusterRoles to grant permission at the namespace-scoped resources level and cluster-scoped resources level:

ClusterRole with namespaced resources for the Cluster Operator

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: strimzi-cluster-operator-namespaced
  labels:
    app: strimzi
rules:
  - apiGroups:
      - "rbac.authorization.k8s.io"
    resources:
      # The cluster operator needs to access and manage rolebindings to grant Strimzi components cluster permissions
      - rolebindings
    verbs:
      - get
      - list
      - watch
      - create
      - delete
      - patch
      - update
  - apiGroups:
      - "rbac.authorization.k8s.io"
    resources:
      # The cluster operator needs to access and manage roles to grant the entity operator permissions
      - roles
    verbs:
      - get
      - list
      - watch
      - create
      - delete
      - patch
      - update
  - apiGroups:
      - ""
    resources:
      # The cluster operator needs to access and delete pods, this is to allow it to monitor pod health and coordinate rolling updates
      - pods
      # The cluster operator needs to access and manage service accounts to grant Strimzi components cluster permissions
      - serviceaccounts
      # The cluster operator needs to access and manage config maps for Strimzi components configuration
      - configmaps
      # The cluster operator needs to access and manage services and endpoints to expose Strimzi components to network traffic
      - services
      - endpoints
      # The cluster operator needs to access and manage secrets to handle credentials
      - secrets
      # The cluster operator needs to access and manage persistent volume claims to bind them to Strimzi components for persistent data
      - persistentvolumeclaims
    verbs:
      - get
      - list
      - watch
      - create
      - delete
      - patch
      - update
  - apiGroups:
      - "kafka.strimzi.io"
    resources:
      # The cluster operator runs the KafkaAssemblyOperator, which needs to access and manage Kafka resources
      - kafkas
      - kafkas/status
      # The cluster operator runs the KafkaConnectAssemblyOperator, which needs to access and manage KafkaConnect resources
      - kafkaconnects
      - kafkaconnects/status
      # The cluster operator runs the KafkaConnectS2IAssemblyOperator, which needs to access and manage KafkaConnectS2I resources
      - kafkaconnects2is
      - kafkaconnects2is/status
      # The cluster operator runs the KafkaConnectorAssemblyOperator, which needs to access and manage KafkaConnector resources
      - kafkaconnectors
      - kafkaconnectors/status
      # The cluster operator runs the KafkaMirrorMakerAssemblyOperator, which needs to access and manage KafkaMirrorMaker resources
      - kafkamirrormakers
      - kafkamirrormakers/status
      # The cluster operator runs the KafkaBridgeAssemblyOperator, which needs to access and manage BridgeMaker resources
      - kafkabridges
      - kafkabridges/status
      # The cluster operator runs the KafkaMirrorMaker2AssemblyOperator, which needs to access and manage KafkaMirrorMaker2 resources
      - kafkamirrormaker2s
      - kafkamirrormaker2s/status
      # The cluster operator runs the KafkaRebalanceAssemblyOperator, which needs to access and manage KafkaRebalance resources
      - kafkarebalances
      - kafkarebalances/status
    verbs:
      - get
      - list
      - watch
      - create
      - delete
      - patch
      - update
  - apiGroups:
      # The cluster operator needs the extensions api as the operator supports Kubernetes version 1.11+
      # apps/v1 was introduced in Kubernetes 1.14
      - "extensions"
    resources:
      # The cluster operator needs to access and manage deployments to run deployment based Strimzi components
      - deployments
      - deployments/scale
      # The cluster operator needs to access replica sets to manage Strimzi components and to determine error states
      - replicasets
      # The cluster operator needs to access and manage replication controllers to manage replicasets
      - replicationcontrollers
      # The cluster operator needs to access and manage network policies to lock down communication between Strimzi components
      - networkpolicies
      # The cluster operator needs to access and manage ingresses which allow external access to the services in a cluster
      - ingresses
    verbs:
      - get
      - list
      - watch
      - create
      - delete
      - patch
      - update
  - apiGroups:
      - "apps"
    resources:
      # The cluster operator needs to access and manage deployments to run deployment based Strimzi components
      - deployments
      - deployments/scale
      - deployments/status
      # The cluster operator needs to access and manage stateful sets to run stateful sets based Strimzi components
      - statefulsets
      # The cluster operator needs to access replica-sets to manage Strimzi components and to determine error states
      - replicasets
    verbs:
      - get
      - list
      - watch
      - create
      - delete
      - patch
      - update
  - apiGroups:
      - ""
    resources:
      # The cluster operator needs to be able to create events and delegate permissions to do so
      - events
    verbs:
      - create
  - apiGroups:
      # OpenShift S2I requirements
      - apps.openshift.io
    resources:
      - deploymentconfigs
      - deploymentconfigs/scale
      - deploymentconfigs/status
      - deploymentconfigs/finalizers
    verbs:
      - get
      - list
      - watch
      - create
      - delete
      - patch
      - update
  - apiGroups:
      # OpenShift S2I requirements
      - build.openshift.io
    resources:
      - buildconfigs
      - buildconfigs/instantiate
      - builds
    verbs:
      - get
      - list
      - watch
      - create
      - delete
      - patch
      - update
  - apiGroups:
      # OpenShift S2I requirements
      - image.openshift.io
    resources:
      - imagestreams
      - imagestreams/status
    verbs:
      - get
      - list
      - watch
      - create
      - delete
      - patch
      - update
  - apiGroups:
      - networking.k8s.io
    resources:
      # The cluster operator needs to access and manage network policies to lock down communication between Strimzi components
      - networkpolicies
      # The cluster operator needs to access and manage ingresses which allow external access to the services in a cluster
      - ingresses
    verbs:
      - get
      - list
      - watch
      - create
      - delete
      - patch
      - update
  - apiGroups:
      - route.openshift.io
    resources:
      # The cluster operator needs to access and manage routes to expose Strimzi components for external access
      - routes
      - routes/custom-host
    verbs:
      - get
      - list
      - watch
      - create
      - delete
      - patch
      - update
  - apiGroups:
      - policy
    resources:
      # The cluster operator needs to access and manage pod disruption budgets this limits the number of concurrent disruptions
      # that a Strimzi component experiences, allowing for higher availability
      - poddisruptionbudgets
    verbs:
      - get
      - list
      - watch
      - create
      - delete
      - patch
      - update
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The second includes the permissions needed for cluster-scoped resources.

ClusterRole with cluster-scoped resources for the Cluster Operator

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: strimzi-cluster-operator-global
  labels:
    app: strimzi
rules:
  - apiGroups:
      - "rbac.authorization.k8s.io"
    resources:
      # The cluster operator needs to create and manage cluster role bindings in the case of an install where a user
      # has specified they want their cluster role bindings generated
      - clusterrolebindings
    verbs:
      - get
      - list
      - watch
      - create
      - delete
      - patch
      - update
  - apiGroups:
      - storage.k8s.io
    resources:
      # The cluster operator requires "get" permissions to view storage class details
      # This is because only a persistent volume of a supported storage class type can be resized
      - storageclasses
    verbs:
      - get
  - apiGroups:
      - ""
    resources:
      # The cluster operator requires "list" permissions to view all nodes in a cluster
      # The listing is used to determine the node addresses when NodePort access is configured
      # These addresses are then exposed in the custom resource states
      - nodes
    verbs:
      - list
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The strimzi-kafka-broker ClusterRole represents the access needed by the init container in Kafka pods that is used for the rack feature. As described in the Delegated privileges section, this role is also needed by the Cluster Operator in order to be able to delegate this access.

ClusterRole for the Cluster Operator allowing it to delegate access to OpenShift nodes to the Kafka broker pods

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: strimzi-kafka-broker
  labels:
    app: strimzi
rules:
  - apiGroups:
      - ""
    resources:
      # The Kafka Brokers require "get" permissions to view the node they are on
      # This information is used to generate a Rack ID that is used for High Availability configurations
      - nodes
    verbs:
      - get
Copy to Clipboard Toggle word wrap

The strimzi-topic-operator ClusterRole represents the access needed by the Topic Operator. As described in the Delegated privileges section, this role is also needed by the Cluster Operator in order to be able to delegate this access.

ClusterRole for the Cluster Operator allowing it to delegate access to events to the Topic Operator

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: strimzi-entity-operator
  labels:
    app: strimzi
rules:
  - apiGroups:
      - "kafka.strimzi.io"
    resources:
      # The entity operator runs the KafkaTopic assembly operator, which needs to access and manage KafkaTopic resources
      - kafkatopics
      - kafkatopics/status
      # The entity operator runs the KafkaUser assembly operator, which needs to access and manage KafkaUser resources
      - kafkausers
      - kafkausers/status
    verbs:
      - get
      - list
      - watch
      - create
      - patch
      - update
      - delete
  - apiGroups:
      - ""
    resources:
      - events
    verbs:
      # The entity operator needs to be able to create events
      - create
  - apiGroups:
      - ""
    resources:
      # The entity operator user-operator needs to access and manage secrets to store generated credentials
      - secrets
    verbs:
      - get
      - list
      - watch
      - create
      - delete
      - patch
      - update
Copy to Clipboard Toggle word wrap

The strimzi-kafka-client ClusterRole represents the access needed by the components based on Kafka clients which use the client rack-awareness. As described in the Delegated privileges section, this role is also needed by the Cluster Operator in order to be able to delegate this access.

ClusterRole for the Cluster Operator allowing it to delegate access to OpenShift nodes to the Kafka client based pods

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: strimzi-kafka-client
  labels:
    app: strimzi
rules:
  - apiGroups:
      - ""
    resources:
      # The Kafka clients (Connect, Mirror Maker, etc.) require "get" permissions to view the node they are on
      # This information is used to generate a Rack ID (client.rack option) that is used for consuming from the closest
      # replicas when enabled
      - nodes
    verbs:
      - get
Copy to Clipboard Toggle word wrap

5.1.2.4. ClusterRoleBindings
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The operator needs ClusterRoleBindings and RoleBindings which associates its ClusterRole with its ServiceAccount: ClusterRoleBindings are needed for ClusterRoles containing cluster-scoped resources.

Example ClusterRoleBinding for the Cluster Operator

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  name: strimzi-cluster-operator
  labels:
    app: strimzi
subjects:
  - kind: ServiceAccount
    name: strimzi-cluster-operator
    namespace: myproject
roleRef:
  kind: ClusterRole
  name: strimzi-cluster-operator-global
  apiGroup: rbac.authorization.k8s.io
Copy to Clipboard Toggle word wrap

ClusterRoleBindings are also needed for the ClusterRoles needed for delegation:

Example ClusterRoleBinding for the Cluster Operator for the Kafka broker rack-awareness

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  name: strimzi-cluster-operator-kafka-broker-delegation
  labels:
    app: strimzi
# The Kafka broker cluster role must be bound to the cluster operator service account so that it can delegate the cluster role to the Kafka brokers.
# This must be done to avoid escalating privileges which would be blocked by Kubernetes.
subjects:
  - kind: ServiceAccount
    name: strimzi-cluster-operator
    namespace: myproject
roleRef:
  kind: ClusterRole
  name: strimzi-kafka-broker
  apiGroup: rbac.authorization.k8s.io
Copy to Clipboard Toggle word wrap

and

Example ClusterRoleBinding for the Cluster Operator for the Kafka client rack-awareness

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  name: strimzi-cluster-operator-kafka-client-delegation
  labels:
    app: strimzi
# The Kafka clients cluster role must be bound to the cluster operator service account so that it can delegate the
# cluster role to the Kafka clients using it for consuming from closest replica.
# This must be done to avoid escalating privileges which would be blocked by Kubernetes.
subjects:
  - kind: ServiceAccount
    name: strimzi-cluster-operator
    namespace: myproject
roleRef:
  kind: ClusterRole
  name: strimzi-kafka-client
  apiGroup: rbac.authorization.k8s.io
Copy to Clipboard Toggle word wrap

ClusterRoles containing only namespaced resources are bound using RoleBindings only. 

apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  name: strimzi-cluster-operator
  labels:
    app: strimzi
subjects:
  - kind: ServiceAccount
    name: strimzi-cluster-operator
    namespace: myproject
roleRef:
  kind: ClusterRole
  name: strimzi-cluster-operator-namespaced
  apiGroup: rbac.authorization.k8s.io
Copy to Clipboard Toggle word wrap 
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  name: strimzi-cluster-operator-entity-operator-delegation
  labels:
    app: strimzi
# The Entity Operator cluster role must be bound to the cluster operator service account so that it can delegate the cluster role to the Entity Operator.
# This must be done to avoid escalating privileges which would be blocked by Kubernetes.
subjects:
  - kind: ServiceAccount
    name: strimzi-cluster-operator
    namespace: myproject
roleRef:
  kind: ClusterRole
  name: strimzi-entity-operator
  apiGroup: rbac.authorization.k8s.io
Copy to Clipboard Toggle word wrap

If you are running a Kafka cluster behind a HTTP proxy, you can still pass data in and out of the cluster. For example, you can run Kafka Connect with connectors that push and pull data from outside the proxy. Or you can use a proxy to connect with an authorization server.

Configure the Cluster Operator deployment to specify the proxy environment variables. The Cluster Operator accepts standard proxy configuration (HTTP_PROXY, HTTPS_PROXY and NO_PROXY) as environment variables. The proxy settings are applied to all AMQ Streams containers.

The format for a proxy address is http://IP-ADDRESS:PORT-NUMBER. To set up a proxy with a name and password, the format is http://USERNAME:PASSWORD@IP-ADDRESS:PORT-NUMBER.

Prerequisites

This procedure requires use of an OpenShift user account which is able to create CustomResourceDefinitions, ClusterRoles and ClusterRoleBindings. Use of Role Base Access Control (RBAC) in the OpenShift cluster usually means that permission to create, edit, and delete these resources is limited to OpenShift cluster administrators, such as system:admin.

Procedure

  1. To add proxy environment variables to the Cluster Operator, update its Deployment configuration (install/cluster-operator/060-Deployment-strimzi-cluster-operator.yaml).

    Example proxy configuration for the Cluster Operator

    apiVersion: apps/v1
kind: Deployment
spec:
  # ...
  template:
    spec:
      serviceAccountName: strimzi-cluster-operator
      containers:
        # ...
        env:
        # ...
        - name: "HTTP_PROXY"
          value: "http://proxy.com"
    1 
    
        - name: "HTTPS_PROXY"
          value: "https://proxy.com"
    2 
    
        - name: "NO_PROXY"
          value: "internal.com, other.domain.com"
    3 
    
  # ...
    Copy to Clipboard Toggle word wrap

    1
    Address of the proxy server.
    2
    Secure address of the proxy server.
    3
    Addresses for servers that are accessed directly as exceptions to the proxy server. The URLs are comma-separated.

    Alternatively, edit the Deployment directly: 

    oc edit deployment strimzi-cluster-operator
    Copy to Clipboard Toggle word wrap

  2. If you updated the YAML file instead of editing the Deployment directly, apply the changes: 

    oc create -f install/cluster-operator/060-Deployment-strimzi-cluster-operator.yaml
    Copy to Clipboard Toggle word wrap

5.2. Using the Topic Operator
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When you create, modify or delete a topic using the KafkaTopic resource, the Topic Operator ensures those changes are reflected in the Kafka cluster.

The Deploying and Upgrading AMQ Streams on OpenShift guide provides instructions to deploy the Topic Operator:

5.2.1. Kafka topic resource
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The KafkaTopic resource is used to configure topics, including the number of partitions and replicas.

The full schema for KafkaTopic is described in KafkaTopic schema reference.

A KafkaTopic resource includes a label that defines the appropriate name of the Kafka cluster (derived from the name of the Kafka resource) to which it belongs.

For example: 

apiVersion: kafka.strimzi.io/v1beta2
kind: KafkaTopic
metadata:
  name: topic-name-1
  labels:
    strimzi.io/cluster: my-cluster
Copy to Clipboard Toggle word wrap

The label is used by the Topic Operator to identify the KafkaTopic resource and create a new topic, and also in subsequent handling of the topic.

If the label does not match the Kafka cluster, the Topic Operator cannot identify the KafkaTopic and the topic is not created.

5.2.1.2. Kafka topic usage recommendations
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When working with topics, be consistent. Always operate on either KafkaTopic resources or topics directly in OpenShift. Avoid routinely switching between both methods for a given topic.

Use topic names that reflect the nature of the topic, and remember that names cannot be changed later.

If creating a topic in Kafka, use a name that is a valid OpenShift resource name, otherwise the Topic Operator will need to create the corresponding KafkaTopic with a name that conforms to the OpenShift rules.

Note

Recommendations for identifiers and names in OpenShift are outlined in Identifiers and Names in OpenShift community article.

5.2.1.3. Kafka topic naming conventions
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Kafka and OpenShift impose their own validation rules for the naming of topics in Kafka and KafkaTopic.metadata.name respectively. There are valid names for each which are invalid in the other.

Using the spec.topicName property, it is possible to create a valid topic in Kafka with a name that would be invalid for the Kafka topic in OpenShift.

The spec.topicName property inherits Kafka naming validation rules:

  • The name must not be longer than 249 characters.
  • Valid characters for Kafka topics are ASCII alphanumerics, ., _, and -.
  • The name cannot be . or .., though . can be used in a name, such as exampleTopic. or .exampleTopic.

spec.topicName must not be changed.

For example: 

apiVersion: kafka.strimzi.io/v1beta2
kind: KafkaTopic
metadata:
  name: topic-name-1
spec:
  topicName: topicName-1
1 

  # ...
Copy to Clipboard Toggle word wrap
1
Upper case is invalid in OpenShift.

cannot be changed to: 

apiVersion: kafka.strimzi.io/v1beta2
kind: KafkaTopic
metadata:
  name: topic-name-1
spec:
  topicName: name-2
  # ...
Copy to Clipboard Toggle word wrap
Note

Some Kafka client applications, such as Kafka Streams, can create topics in Kafka programmatically. If those topics have names that are invalid OpenShift resource names, the Topic Operator gives them a valid metadata.name based on the Kafka name. Invalid characters are replaced and a hash is appended to the name. For example: 

apiVersion: kafka.strimzi.io/v1beta2
kind: KafkaTopic
metadata:
  name: mytopic---c55e57fe2546a33f9e603caf57165db4072e827e
spec:
  topicName: myTopic
  # ...
Copy to Clipboard Toggle word wrap

5.2.2. Topic Operator topic store
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The Topic Operator uses Kafka to store topic metadata describing topic configuration as key-value pairs. The topic store is based on the Kafka Streams key-value mechanism, which uses Kafka topics to persist the state.

Topic metadata is cached in-memory and accessed locally within the Topic Operator. Updates from operations applied to the local in-memory cache are persisted to a backup topic store on disk. The topic store is continually synchronized with updates from Kafka topics or OpenShift KafkaTopic custom resources. Operations are handled rapidly with the topic store set up this way, but should the in-memory cache crash it is automatically repopulated from the persistent storage.

5.2.2.1. Internal topic store topics
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Internal topics support the handling of topic metadata in the topic store.

__strimzi_store_topic
Input topic for storing the topic metadata
__strimzi-topic-operator-kstreams-topic-store-changelog
Retains a log of compacted topic store values
Warning

Do not delete these topics, as they are essential to the running of the Topic Operator.

5.2.2.2. Migrating topic metadata from ZooKeeper
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In previous releases of AMQ Streams, topic metadata was stored in ZooKeeper. The new process removes this requirement, bringing the metadata into the Kafka cluster, and under the control of the Topic Operator.

When upgrading to AMQ Streams 1.8, the transition to Topic Operator control of the topic store is seamless. Metadata is found and migrated from ZooKeeper, and the old store is deleted.

If you are reverting back to a version of AMQ Streams earlier than 0.22, which uses ZooKeeper for the storage of topic metadata, you still downgrade your Cluster Operator to the previous version, then downgrade Kafka brokers and client applications to the previous Kafka version as standard.

However, you must also delete the topics that were created for the topic store using a kafka-admin command, specifying the bootstrap address of the Kafka cluster. For example: 

oc run kafka-admin -ti --image=registry.redhat.io/amq7/amq-streams-kafka-28-rhel8:1.8.4 --rm=true --restart=Never -- ./bin/kafka-topics.sh --bootstrap-server localhost:9092 --topic __strimzi-topic-operator-kstreams-topic-store-changelog --delete && ./bin/kafka-topics.sh --bootstrap-server localhost:9092 --topic __strimzi_store_topic --delete
Copy to Clipboard Toggle word wrap

The command must correspond to the type of listener and authentication used to access the Kafka cluster.

The Topic Operator will reconstruct the ZooKeeper topic metadata from the state of the topics in Kafka.

The recommended configuration for topics managed by the Topic Operator is a topic replication factor of 3, and a minimum of 2 in-sync replicas. 

apiVersion: kafka.strimzi.io/v1beta2
kind: KafkaTopic
metadata:
  name: my-topic
  labels:
    strimzi.io/cluster: my-cluster
spec:
  partitions: 1
1 

  replicas: 3
2 

  config:
    min.insync.replicas=2
3 

  #...
Copy to Clipboard Toggle word wrap
1
The number of partitions for the topic. Generally, 1 partition is sufficient.
2
The number of replica topic partitions. Currently, this cannot be changed in the KafkaTopic resource, but it can be changed using the kafka-reassign-partitions.sh tool.
3
The minimum number of replica partitions that a message must be successfully written to, or an exception is raised.
Note

In-sync replicas are used in conjunction with the acks configuration for producer applications. The acks configuration determines the number of follower partitions a message must be replicated to before the message is acknowledged as successfully received. The Topic Operator runs with acks=all, whereby messages must be acknowledged by all in-sync replicas.

When scaling Kafka clusters by adding or removing brokers, replication factor configuration is not changed and replicas are not reassigned automatically. However, you can use the kafka-reassign-partitions.sh tool to change the replication factor, and manually reassign replicas to brokers.

Alternatively, though the integration of Cruise Control for AMQ Streams cannot change the replication factor for topics, the optimization proposals it generates for rebalancing Kafka include commands that transfer partition replicas and change partition leadership.

5.2.2.5. Handling changes to topics
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A fundamental problem that the Topic Operator needs to solve is that there is no single source of truth: both the KafkaTopic resource and the Kafka topic can be modified independently of the Topic Operator. Complicating this, the Topic Operator might not always be able to observe changes at each end in real time. For example, when the Topic Operator is down.

To resolve this, the Topic Operator maintains information about each topic in the topic store. When a change happens in the Kafka cluster or OpenShift, it looks at both the state of the other system and the topic store in order to determine what needs to change to keep everything in sync. The same thing happens whenever the Topic Operator starts, and periodically while it is running.

For example, suppose the Topic Operator is not running, and a KafkaTopic called my-topic is created. When the Topic Operator starts, the topic store does not contain information on my-topic, so it can infer that the KafkaTopic was created after it was last running. The Topic Operator creates the topic corresponding to my-topic, and also stores metadata for my-topic in the topic store.

If you update Kafka topic configuration or apply a change through the KafkaTopic custom resource, the topic store is updated after the Kafka cluster is reconciled.

The topic store also allows the Topic Operator to manage scenarios where the topic configuration is changed in Kafka topics and updated through OpenShift KafkaTopic custom resources, as long as the changes are not incompatible. For example, it is possible to make changes to the same topic config key, but to different values. For incompatible changes, the Kafka configuration takes priority, and the KafkaTopic is updated accordingly.

Note

You can also use the KafkaTopic resource to delete topics using a oc delete -f KAFKA-TOPIC-CONFIG-FILE command. To be able to do this, delete.topic.enable must be set to true (default) in the spec.kafka.config of the Kafka resource.

5.2.3. Configuring a Kafka topic
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Use the properties of the KafkaTopic resource to configure a Kafka topic.

You can use oc apply to create or modify topics, and oc delete to delete existing topics.

For example:

  • oc apply -f <topic-config-file>
  • oc delete KafkaTopic <topic-name>

This procedure shows how to create a topic with 10 partitions and 2 replicas.

Before you start

It is important that you consider the following before making your changes:

  • Kafka does not support making the following changes through the KafkaTopic resource:

    • Changing topic names using spec.topicName
    • Decreasing partition size using spec.partitions
  • You cannot use spec.replicas to change the number of replicas that were initially specified.
  • Increasing spec.partitions for topics with keys will change how records are partitioned, which can be particularly problematic when the topic uses semantic partitioning.

Prerequisites

Procedure

  1. Prepare a file containing the KafkaTopic to be created.

    An example KafkaTopic

    apiVersion: kafka.strimzi.io/v1beta2
kind: KafkaTopic
metadata:
  name: orders
  labels:
    strimzi.io/cluster: my-cluster
spec:
  partitions: 10
  replicas: 2
    Copy to Clipboard Toggle word wrap

    Tip

    When modifying a topic, you can get the current version of the resource using oc get kafkatopic orders -o yaml.

  2. Create the KafkaTopic resource in OpenShift. 

    oc apply -f TOPIC-CONFIG-FILE
    Copy to Clipboard Toggle word wrap

You can allocate resources, such as CPU and memory, to the Topic Operator and set a limit on the amount of resources it can consume.

Prerequisites

  • The Cluster Operator is running.

Procedure

  1. Update the Kafka cluster configuration in an editor, as required: 

    oc edit kafka MY-CLUSTER
    Copy to Clipboard Toggle word wrap

  2. In the spec.entityOperator.topicOperator.resources property in the Kafka resource, set the resource requests and limits for the Topic Operator. 

    apiVersion: kafka.strimzi.io/v1beta2
kind: Kafka
spec:
  # Kafka and ZooKeeper sections...
  entityOperator:
    topicOperator:
      resources:
        requests:
          cpu: "1"
          memory: 500Mi
        limits:
          cpu: "1"
          memory: 500Mi
    Copy to Clipboard Toggle word wrap

  3. Apply the new configuration to create or update the resource. 

    oc apply -f KAFKA-CONFIG-FILE
    Copy to Clipboard Toggle word wrap

5.3. Using the User Operator
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When you create, modify or delete a user using the KafkaUser resource, the User Operator ensures those changes are reflected in the Kafka cluster.

The Deploying and Upgrading AMQ Streams on OpenShift guide provides instructions to deploy the User Operator:

For more information about the schema, see KafkaUser schema reference.

Authenticating and authorizing access to Kafka

Use KafkaUser to enable the authentication and authorization mechanisms that a specific client uses to access Kafka.

For more information on using KafkUser to manage users and secure access to Kafka brokers, see Securing access to Kafka brokers.

You can allocate resources, such as CPU and memory, to the User Operator and set a limit on the amount of resources it can consume.

Prerequisites

  • The Cluster Operator is running.

Procedure

  1. Update the Kafka cluster configuration in an editor, as required: 

    oc edit kafka MY-CLUSTER
    Copy to Clipboard Toggle word wrap

  2. In the spec.entityOperator.userOperator.resources property in the Kafka resource, set the resource requests and limits for the User Operator. 

    apiVersion: kafka.strimzi.io/v1beta2
kind: Kafka
spec:
  # Kafka and ZooKeeper sections...
  entityOperator:
    userOperator:
      resources:
        requests:
          cpu: "1"
          memory: 500Mi
        limits:
          cpu: "1"
          memory: 500Mi
    Copy to Clipboard Toggle word wrap

    Save the file and exit the editor. The Cluster Operator applies the changes automatically.

5.4. Monitoring operators using Prometheus metrics
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AMQ Streams operators expose Prometheus metrics. The metrics are automatically enabled and contain information about:

  • Number of reconciliations
  • Number of Custom Resources the operator is processing
  • Duration of reconciliations
  • JVM metrics from the operators

Additionally, we provide an example Grafana dashboard.

For more information about Prometheus, see the Introducing Metrics to Kafka in the Deploying and Upgrading AMQ Streams on OpenShift guide.

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