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Chapter 5. Deploying AMQ Streams using installation artifacts
Having prepared your environment for a deployment of AMQ Streams, you can deploy AMQ Streams to an OpenShift cluster. You can use the deployment files provided with the release artifacts.
Use the deployment files to create the Kafka cluster.
Optionally, you can deploy the following Kafka components according to your requirements:
AMQ Streams is based on Strimzi 0.26.x. You can deploy AMQ Streams 2.0 on OpenShift 4.6 to 4.9.
To run the commands in this guide, your cluster user must have the rights to manage role-based access control (RBAC) and CRDs.
5.1. Create the Kafka cluster Copia collegamentoCollegamento copiato negli appunti!
To be able to manage a Kafka cluster with the Cluster Operator, you must deploy it as a Kafka resource. AMQ Streams provides example deployment files to do this. You can use these files to deploy the Topic Operator and User Operator at the same time.
If you haven’t deployed a Kafka cluster as a Kafka resource, you can’t use the Cluster Operator to manage it. This applies, for example, to a Kafka cluster running outside of OpenShift. But you can deploy and use the Topic Operator and User Operator as standalone components.
The Cluster Operator can watch one, multiple, or all namespaces in an OpenShift cluster. The Topic Operator and User Operator watch for KafkaTopics and KafkaUsers in the single namespace of the Kafka cluster deployment.
Deploying a Kafka cluster with the Topic Operator and User Operator
Perform these deployment steps if you want to use the Topic Operator and User Operator with a Kafka cluster managed by AMQ Streams.
- Deploy the Cluster Operator
Use the Cluster Operator to deploy the:
Deploying a standalone Topic Operator and User Operator
Perform these deployment steps if you want to use the Topic Operator and User Operator with a Kafka cluster that is not managed by AMQ Streams.
5.1.1. Deploying the Cluster Operator Copia collegamentoCollegamento copiato negli appunti!
The Cluster Operator is responsible for deploying and managing Apache Kafka clusters within an OpenShift cluster.
The procedures in this section show:
How to deploy the Cluster Operator to watch:
5.1.1.1. Watch options for a Cluster Operator deployment Copia collegamentoCollegamento copiato negli appunti!
When the Cluster Operator is running, it starts to watch for updates of Kafka resources.
You can choose to deploy the Cluster Operator to watch Kafka resources from:
- A single namespace (the same namespace containing the Cluster Operator)
- Multiple namespaces
- All namespaces
AMQ Streams provides example YAML files to make the deployment process easier.
The Cluster Operator watches for changes to the following resources:
-
Kafkafor the Kafka cluster. -
KafkaConnectfor the Kafka Connect cluster. -
KafkaConnectorfor creating and managing connectors in a Kafka Connect cluster. -
KafkaMirrorMakerfor the Kafka MirrorMaker instance. -
KafkaMirrorMaker2for the Kafka MirrorMaker 2.0 instance. -
KafkaBridgefor the Kafka Bridge instance. -
KafkaRebalancefor the Cruise Control optimization requests.
When one of these resources is created in the OpenShift cluster, the operator gets the cluster description from the resource and starts creating a new cluster for the resource by creating the necessary OpenShift resources, such as StatefulSets, Services and ConfigMaps.
Each time a Kafka resource is updated, the operator performs corresponding updates on the OpenShift resources that make up the cluster for the resource.
Resources are either patched or deleted, and then recreated in order to make the cluster for the resource reflect the desired state of the cluster. This operation might cause a rolling update that might lead to service disruption.
When a resource is deleted, the operator undeploys the cluster and deletes all related OpenShift resources.
5.1.1.2. Deploying the Cluster Operator to watch a single namespace Copia collegamentoCollegamento copiato negli appunti!
This procedure shows how to deploy the Cluster Operator to watch AMQ Streams resources in a single namespace in your OpenShift cluster.
Prerequisites
-
This procedure requires use of an OpenShift user account which is able to create
CustomResourceDefinitions,ClusterRolesandClusterRoleBindings. 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 assystem:admin.
Procedure
Edit the AMQ Streams installation files to use the namespace the Cluster Operator is going to be installed into.
For example, in this procedure the Cluster Operator is installed into the namespace
my-cluster-operator-namespace.On Linux, use:
sed -i 's/namespace: .*/namespace: my-cluster-operator-namespace/' install/cluster-operator/*RoleBinding*.yamlOn MacOS, use:
sed -i '' 's/namespace: .*/namespace: my-cluster-operator-namespace/' install/cluster-operator/*RoleBinding*.yamlDeploy the Cluster Operator:
oc create -f install/cluster-operator -n my-cluster-operator-namespaceVerify that the Cluster Operator was successfully deployed:
oc get deployments
5.1.1.3. Deploying the Cluster Operator to watch multiple namespaces Copia collegamentoCollegamento copiato negli appunti!
This procedure shows how to deploy the Cluster Operator to watch AMQ Streams resources across multiple namespaces in your OpenShift cluster.
Prerequisites
-
This procedure requires use of an OpenShift user account which is able to create
CustomResourceDefinitions,ClusterRolesandClusterRoleBindings. 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 assystem:admin.
Procedure
Edit the AMQ Streams installation files to use the namespace the Cluster Operator is going to be installed into.
For example, in this procedure the Cluster Operator is installed into the namespace
my-cluster-operator-namespace.On Linux, use:
sed -i 's/namespace: .*/namespace: my-cluster-operator-namespace/' install/cluster-operator/*RoleBinding*.yamlOn MacOS, use:
sed -i '' 's/namespace: .*/namespace: my-cluster-operator-namespace/' install/cluster-operator/*RoleBinding*.yamlEdit the
install/cluster-operator/060-Deployment-strimzi-cluster-operator.yamlfile to add a list of all the namespaces the Cluster Operator will watch to theSTRIMZI_NAMESPACEenvironment variable.For example, in this procedure the Cluster Operator will watch the namespaces
watched-namespace-1,watched-namespace-2,watched-namespace-3.apiVersion: apps/v1 kind: Deployment spec: # ... template: spec: serviceAccountName: strimzi-cluster-operator containers: - name: strimzi-cluster-operator image: registry.redhat.io/amq7/amq-streams-rhel8-operator:2.0.1 imagePullPolicy: IfNotPresent env: - name: STRIMZI_NAMESPACE value: watched-namespace-1,watched-namespace-2,watched-namespace-3For each namespace listed, install the
RoleBindings.In this example, we replace
watched-namespacein these commands with the namespaces listed in the previous step, repeating them forwatched-namespace-1,watched-namespace-2,watched-namespace-3:oc create -f install/cluster-operator/020-RoleBinding-strimzi-cluster-operator.yaml -n watched-namespace oc create -f install/cluster-operator/031-RoleBinding-strimzi-cluster-operator-entity-operator-delegation.yaml -n watched-namespaceDeploy the Cluster Operator:
oc create -f install/cluster-operator -n my-cluster-operator-namespaceVerify that the Cluster Operator was successfully deployed:
oc get deployments
5.1.1.4. Deploying the Cluster Operator to watch all namespaces Copia collegamentoCollegamento copiato negli appunti!
This procedure shows how to deploy the Cluster Operator to watch AMQ Streams resources across all namespaces in your OpenShift cluster.
When running in this mode, the Cluster Operator automatically manages clusters in any new namespaces that are created.
Prerequisites
-
This procedure requires use of an OpenShift user account which is able to create
CustomResourceDefinitions,ClusterRolesandClusterRoleBindings. 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 assystem:admin.
Procedure
Edit the AMQ Streams installation files to use the namespace the Cluster Operator is going to be installed into.
For example, in this procedure the Cluster Operator is installed into the namespace
my-cluster-operator-namespace.On Linux, use:
sed -i 's/namespace: .*/namespace: my-cluster-operator-namespace/' install/cluster-operator/*RoleBinding*.yamlOn MacOS, use:
sed -i '' 's/namespace: .*/namespace: my-cluster-operator-namespace/' install/cluster-operator/*RoleBinding*.yamlEdit the
install/cluster-operator/060-Deployment-strimzi-cluster-operator.yamlfile to set the value of theSTRIMZI_NAMESPACEenvironment variable to*.apiVersion: apps/v1 kind: Deployment spec: # ... template: spec: # ... serviceAccountName: strimzi-cluster-operator containers: - name: strimzi-cluster-operator image: registry.redhat.io/amq7/amq-streams-rhel8-operator:2.0.1 imagePullPolicy: IfNotPresent env: - name: STRIMZI_NAMESPACE value: "*" # ...Create
ClusterRoleBindingsthat grant cluster-wide access for all namespaces to the Cluster Operator.oc create clusterrolebinding strimzi-cluster-operator-namespaced --clusterrole=strimzi-cluster-operator-namespaced --serviceaccount my-cluster-operator-namespace:strimzi-cluster-operator oc create clusterrolebinding strimzi-cluster-operator-entity-operator-delegation --clusterrole=strimzi-entity-operator --serviceaccount my-cluster-operator-namespace:strimzi-cluster-operatorReplace
my-cluster-operator-namespacewith the namespace you want to install the Cluster Operator into.Deploy the Cluster Operator to your OpenShift cluster.
oc create -f install/cluster-operator -n my-cluster-operator-namespaceVerify that the Cluster Operator was successfully deployed:
oc get deployments
5.1.2. Deploying Kafka Copia collegamentoCollegamento copiato negli appunti!
Apache Kafka is an open-source distributed publish-subscribe messaging system for fault-tolerant real-time data feeds.
The procedures in this section show:
How to use the Cluster Operator to deploy:
- An ephemeral or persistent Kafka cluster
The Topic Operator and User Operator by configuring the
Kafkacustom resource:
Alternative standalone deployment procedures for the Topic Operator and User Operator:
When installing Kafka, AMQ Streams also installs a ZooKeeper cluster and adds the necessary configuration to connect Kafka with ZooKeeper.
5.1.2.1. Deploying the Kafka cluster Copia collegamentoCollegamento copiato negli appunti!
This procedure shows how to deploy a Kafka cluster to your OpenShift cluster using the Cluster Operator.
The deployment uses a YAML file to provide the specification to create a Kafka resource.
AMQ Streams provides example configuration files. For a Kafka deployment, the following examples are provided:
kafka-persistent.yaml- Deploys a persistent cluster with three ZooKeeper and three Kafka nodes.
kafka-jbod.yaml- Deploys a persistent cluster with three ZooKeeper and three Kafka nodes (each using multiple persistent volumes).
kafka-persistent-single.yaml- Deploys a persistent cluster with a single ZooKeeper node and a single Kafka node.
kafka-ephemeral.yaml- Deploys an ephemeral cluster with three ZooKeeper and three Kafka nodes.
kafka-ephemeral-single.yaml- Deploys an ephemeral cluster with three ZooKeeper nodes and a single Kafka node.
In this procedure, we use the examples for an ephemeral and persistent Kafka cluster deployment.
- Ephemeral cluster
-
In general, an ephemeral (or temporary) Kafka cluster is suitable for development and testing purposes, not for production. This deployment uses
emptyDirvolumes for storing broker information (for ZooKeeper) and topics or partitions (for Kafka). Using anemptyDirvolume means that its content is strictly related to the pod life cycle and is deleted when the pod goes down. - Persistent cluster
-
A persistent Kafka cluster uses
PersistentVolumesto store ZooKeeper and Kafka data. ThePersistentVolumeis acquired using aPersistentVolumeClaimto make it independent of the actual type of thePersistentVolume. For example, it can use Amazon EBS volumes in Amazon AWS deployments without any changes in the YAML files. ThePersistentVolumeClaimcan use aStorageClassto trigger automatic volume provisioning.
The example YAML files specify the latest supported Kafka version, and configuration for its supported log message format version and inter-broker protocol version. The inter.broker.protocol.version property for the Kafka config must be the version supported by the specified Kafka version (spec.kafka.version). The property represents the version of Kafka protocol used in a Kafka cluster.
From Kafka 3.0.0, when the inter.broker.protocol.version is set to 3.0 or higher, the log.message.format.version option is ignored and doesn’t need to be set.
An update to the inter.broker.protocol.version is required when upgrading Kafka.
The example clusters are named my-cluster by default. The cluster name is defined by the name of the resource and cannot be changed after the cluster has been deployed. To change the cluster name before you deploy the cluster, edit the Kafka.metadata.name property of the Kafka resource in the relevant YAML file.
Default cluster name and specified Kafka versions
apiVersion: kafka.strimzi.io/v1beta2
kind: Kafka
metadata:
name: my-cluster
spec:
kafka:
version: 3.0.0
#...
config:
#...
log.message.format.version: "3.0"
inter.broker.protocol.version: "3.0"
# ...
Prerequisites
Procedure
Create and deploy an ephemeral or persistent cluster.
For development or testing, you might prefer to use an ephemeral cluster. You can use a persistent cluster in any situation.
To create and deploy an ephemeral cluster:
oc apply -f examples/kafka/kafka-ephemeral.yamlTo create and deploy a persistent cluster:
oc apply -f examples/kafka/kafka-persistent.yaml
Verify that the Kafka cluster was successfully deployed:
oc get deployments
5.1.2.2. Deploying the Topic Operator using the Cluster Operator Copia collegamentoCollegamento copiato negli appunti!
This procedure describes how to deploy the Topic Operator using the Cluster Operator.
You configure the entityOperator property of the Kafka resource to include the topicOperator. By default, the Topic Operator watches for KafkaTopics in the namespace of the Kafka cluster deployment.
If you want to use the Topic Operator with a Kafka cluster that is not managed by AMQ Streams, you must deploy the Topic Operator as a standalone component.
For more information about configuring the entityOperator and topicOperator properties, see Configuring the Entity Operator in the Using AMQ Streams on OpenShift guide.
Prerequisites
Procedure
Edit the
entityOperatorproperties of theKafkaresource to includetopicOperator:apiVersion: kafka.strimzi.io/v1beta2 kind: Kafka metadata: name: my-cluster spec: #... entityOperator: topicOperator: {} userOperator: {}Configure the Topic Operator
specusing the properties described inEntityTopicOperatorSpecschema reference.Use an empty object (
{}) if you want all properties to use their default values.Create or update the resource:
Use
oc apply:oc apply -f <your-file>
5.1.2.3. Deploying the User Operator using the Cluster Operator Copia collegamentoCollegamento copiato negli appunti!
This procedure describes how to deploy the User Operator using the Cluster Operator.
You configure the entityOperator property of the Kafka resource to include the userOperator. By default, the User Operator watches for KafkaUsers in the namespace of the Kafka cluster deployment.
If you want to use the User Operator with a Kafka cluster that is not managed by AMQ Streams, you must deploy the User Operator as a standalone component.
For more information about configuring the entityOperator and userOperator properties, see Configuring the Entity Operator in the Using AMQ Streams on OpenShift guide.
Prerequisites
Procedure
Edit the
entityOperatorproperties of theKafkaresource to includeuserOperator:apiVersion: kafka.strimzi.io/v1beta2 kind: Kafka metadata: name: my-cluster spec: #... entityOperator: topicOperator: {} userOperator: {}Configure the User Operator
specusing the properties described inEntityUserOperatorSpecschema reference in the Using AMQ Streams on OpenShift guide.Use an empty object (
{}) if you want all properties to use their default values.Create or update the resource:
oc apply -f <your-file>
5.1.3. Alternative standalone deployment options for AMQ Streams Operators Copia collegamentoCollegamento copiato negli appunti!
You can perform a standalone deployment of the Topic Operator and User Operator. Consider a standalone deployment of these operators if you are using a Kafka cluster that is not managed by the Cluster Operator.
You deploy the operators to OpenShift. Kafka can be running outside of OpenShift. For example, you might be using a Kafka as a managed service. You adjust the deployment configuration for the standalone operator to match the address of your Kafka cluster.
5.1.3.1. Deploying the standalone Topic Operator Copia collegamentoCollegamento copiato negli appunti!
This procedure shows how to deploy the Topic Operator as a standalone component for topic management. You can use a standalone Topic Operator with a Kafka cluster that is not managed by the Cluster Operator.
A standalone deployment can operate with any Kafka cluster.
Standalone deployment files are provided with AMQ Streams. Use the 05-Deployment-strimzi-topic-operator.yaml deployment file to deploy the Topic Operator. Add or set the environment variables needed to make a connection to a Kafka cluster.
Prerequisites
You are running a Kafka cluster for the Topic Operator to connect to.
As long as the standalone Topic Operator is correctly configured for connection, the Kafka cluster can be running on a bare-metal environment, a virtual machine, or as a managed cloud application service.
Procedure
Edit the
envproperties in theinstall/topic-operator/05-Deployment-strimzi-topic-operator.yamlstandalone deployment file.Example standalone Topic Operator deployment configuration
apiVersion: apps/v1 kind: Deployment metadata: name: strimzi-topic-operator labels: app: strimzi spec: # ... template: # ... spec: # ... containers: - name: strimzi-topic-operator # ... env: - name: STRIMZI_NAMESPACE1 valueFrom: fieldRef: fieldPath: metadata.namespace - name: STRIMZI_KAFKA_BOOTSTRAP_SERVERS2 value: my-kafka-bootstrap-address:9092 - name: STRIMZI_RESOURCE_LABELS3 value: "strimzi.io/cluster=my-cluster" - name: STRIMZI_ZOOKEEPER_CONNECT4 value: my-cluster-zookeeper-client:2181 - name: STRIMZI_ZOOKEEPER_SESSION_TIMEOUT_MS5 value: "18000" - name: STRIMZI_FULL_RECONCILIATION_INTERVAL_MS6 value: "120000" - name: STRIMZI_TOPIC_METADATA_MAX_ATTEMPTS7 value: "6" - name: STRIMZI_LOG_LEVEL8 value: INFO - name: STRIMZI_TLS_ENABLED9 value: "false" - name: STRIMZI_JAVA_OPTS10 value: "-Xmx=512M -Xms=256M" - name: STRIMZI_JAVA_SYSTEM_PROPERTIES11 value: "-Djavax.net.debug=verbose -DpropertyName=value" - name: STRIMZI_PUBLIC_CA12 value: "false" - name: STRIMZI_TLS_AUTH_ENABLED13 value: "false" - name: STRIMZI_SASL_ENABLED14 value: "false" - name: STRIMZI_SASL_USERNAME15 value: "admin" - name: STRIMZI_SASL_PASSWORD16 value: "password" - name: STRIMZI_SASL_MECHANISM17 value: "scram-sha-512" - name: STRIMZI_SECURITY_PROTOCOL18 value: "SSL"- 1
- The OpenShift namespace for the Topic Operator to watch for
KafkaTopicresources. Specify the namespace of the Kafka cluster. - 2
- The host and port pair of the bootstrap broker address to discover and connect to all brokers in the Kafka cluster. Use a comma-separated list to specify two or three broker addresses in case a server is down.
- 3
- The label selector to identify the
KafkaTopicresources managed by the Topic Operator. - 4
- The host and port pair of the address to connect to the ZooKeeper cluster. This must be the same ZooKeeper cluster that your Kafka cluster is using.
- 5
- The ZooKeeper session timeout, in milliseconds. The default is
18000(18 seconds). - 6
- The interval between periodic reconciliations, in milliseconds. The default is
120000(2 minutes). - 7
- The number of attempts at getting topic metadata from Kafka. The time between each attempt is defined as an exponential backoff. Consider increasing this value when topic creation takes more time due to the number of partitions or replicas. The default is
6attempts. - 8
- The level for printing logging messages. You can set the level to
ERROR,WARNING,INFO,DEBUG, orTRACE. - 9
- Enables TLS support for encrypted communication with the Kafka brokers.
- 10
- (Optional) The Java options used by the JVM running the Topic Operator.
- 11
- (Optional) The debugging (
-D) options set for the Topic Operator. - 12
- (Optional) Skips the generation of trust store certificates if TLS is enabled through
STRIMZI_TLS_ENABLED. If this environment variable is enabled, the brokers must use a public trusted certificate authority for their TLS certificates. The default isfalse. - 13
- (Optional) Generates key store certificates for mutual TLS authentication. Setting this to
falsedisables client authentication with TLS to the Kafka brokers. The default istrue. - 14
- (Optional) Enables SASL support for client authentication when connecting to Kafka brokers. The default is
false. - 15
- (Optional) The SASL username for client authentication. Mandatory only if SASL is enabled through
STRIMZI_SASL_ENABLED. - 16
- (Optional) The SASL password for client authentication. Mandatory only if SASL is enabled through
STRIMZI_SASL_ENABLED. - 17
- (Optional) The SASL mechanism for client authentication. Mandatory only if SASL is enabled through
STRIMZI_SASL_ENABLED. You can set the value toplain,scram-sha-256, orscram-sha-512. - 18
- (Optional) The security protocol used for communication with Kafka brokers. The default value is "PLAINTEXT". You can set the value to
PLAINTEXT,SSL,SASL_PLAINTEXT, orSASL_SSL.
-
If you want to connect to Kafka brokers that are using certificates from a public certificate authority, set
STRIMZI_PUBLIC_CAtotrue. Set this property totrue, for example, if you are using Amazon AWS MSK service. If you enabled TLS with the
STRIMZI_TLS_ENABLEDenvironment variable, specify the keystore and truststore used to authenticate connection to the Kafka cluster.Example TLS configuration
# .... env: - name: STRIMZI_TRUSTSTORE_LOCATION1 value: "/path/to/truststore.p12" - name: STRIMZI_TRUSTSTORE_PASSWORD2 value: "TRUSTSTORE-PASSWORD" - name: STRIMZI_KEYSTORE_LOCATION3 value: "/path/to/keystore.p12" - name: STRIMZI_KEYSTORE_PASSWORD4 value: "KEYSTORE-PASSWORD" # ...Deploy the Topic Operator.
oc create -f install/topic-operatorVerify that the Topic Operator has been deployed successfully.
oc describe deployment strimzi-topic-operatorThe Topic Operator is deployed when the
Replicasentry shows1 available.NoteYou may experience a delay with the deployment if you have a slow connection to the OpenShift cluster and the Topic Operator images have not been downloaded before.
5.1.3.2. Deploying the standalone User Operator Copia collegamentoCollegamento copiato negli appunti!
This procedure shows how to deploy the User Operator as a standalone component for user management. You can use a standalone User Operator with a Kafka cluster that is not managed by the Cluster Operator.
A standalone deployment can operate with any Kafka cluster.
Standalone deployment files are provided with AMQ Streams. Use the 05-Deployment-strimzi-user-operator.yaml deployment file to deploy the User Operator. Add or set the environment variables needed to make a connection to a Kafka cluster.
Prerequisites
You are running a Kafka cluster for the User Operator to connect to.
As long as the standalone User Operator is correctly configured for connection, the Kafka cluster can be running on a bare-metal environment, a virtual machine, or as a managed cloud application service.
Procedure
Edit the following
envproperties in theinstall/user-operator/05-Deployment-strimzi-user-operator.yamlstandalone deployment file.Example standalone User Operator deployment configuration
apiVersion: apps/v1 kind: Deployment metadata: name: strimzi-user-operator labels: app: strimzi spec: # ... template: # ... spec: # ... containers: - name: strimzi-user-operator # ... env: - name: STRIMZI_NAMESPACE1 valueFrom: fieldRef: fieldPath: metadata.namespace - name: STRIMZI_KAFKA_BOOTSTRAP_SERVERS2 value: my-kafka-bootstrap-address:9092 - name: STRIMZI_CA_CERT_NAME3 value: my-cluster-clients-ca-cert - name: STRIMZI_CA_KEY_NAME4 value: my-cluster-clients-ca - name: STRIMZI_LABELS5 value: "strimzi.io/cluster=my-cluster" - name: STRIMZI_FULL_RECONCILIATION_INTERVAL_MS6 value: "120000" - name: STRIMZI_LOG_LEVEL7 value: INFO - name: STRIMZI_GC_LOG_ENABLED8 value: "true" - name: STRIMZI_CA_VALIDITY9 value: "365" - name: STRIMZI_CA_RENEWAL10 value: "30" - name: STRIMZI_JAVA_OPTS11 value: "-Xmx=512M -Xms=256M" - name: STRIMZI_JAVA_SYSTEM_PROPERTIES12 value: "-Djavax.net.debug=verbose -DpropertyName=value" - name: STRIMZI_SECRET_PREFIX13 value: "kafka-" - name: STRIMZI_ACLS_ADMIN_API_SUPPORTED14 value: "true"- 1
- The OpenShift namespace for the User Operator to watch for
KafkaUserresources. Only one namespace can be specified. - 2
- The host and port pair of the bootstrap broker address to discover and connect to all brokers in the Kafka cluster. Use a comma-separated list to specify two or three broker addresses in case a server is down.
- 3
- The OpenShift
Secretthat contains the public key (ca.crt) value of the Certificate Authority that signs new user certificates for TLS client authentication. - 4
- The OpenShift
Secretthat contains the private key (ca.key) value of the Certificate Authority that signs new user certificates for TLS client authentication. - 5
- The label selector used to identify the
KafkaUserresources managed by the User Operator. - 6
- The interval between periodic reconciliations, in milliseconds. The default is
120000(2 minutes). The default is18000(18 seconds). - 7
- The level for printing logging messages. You can set the level to
ERROR,WARNING,INFO,DEBUG, orTRACE. - 8
- Enables garbage collection (GC) logging. The default is
true. - 9
- The validity period for the Certificate Authority. The default is
365days. - 10
- The renewal period for the Certificate Authority. The renewal period is measured backwards from the expiry date of the current certificate. The default is
30days to initiate certificate renewal before the old certificates expire. - 11
- (Optional) The Java options used by the JVM running the User Operator
- 12
- (Optional) The debugging (
-D) options set for the User Operator - 13
- (Optional) Prefix for the names of OpenShift secrets created by the User Operator.
- 14
- (Optional) Indicates whether the Kafka cluster supports management of authorization ACL rules using the Kafka Admin API. When set to
false, the User Operator will reject all resources withsimpleauthorization ACL rules. This helps to avoid unnecessary exceptions in the Kafka cluster logs. The default istrue.
If you are using TLS to connect to the Kafka cluster, specify the secrets used to authenticate connection. Otherwise, go to the next step.
Example TLS configuration
# .... env: - name: STRIMZI_CLUSTER_CA_CERT_SECRET_NAME1 value: my-cluster-cluster-cert - name: STRIMZI_EO_KEY_SECRET_NAME2 value: my-cluster-entity-operator-certs # ..."- 1
- The OpenShift
Secretthat contains the public key (ca.crt) value of the Certificate Authority that signs Kafka broker certificates for TLS client authentication. - 2
- The OpenShift
Secretthat contains the keystore (entity-operator.p12) with the private key and certificate for TLS authentication against the Kafka cluster. TheSecretmust also contain the password (entity-operator.password) for accessing the keystore.
Deploy the User Operator.
oc create -f install/user-operatorVerify that the User Operator has been deployed successfully.
oc describe deployment strimzi-user-operatorThe User Operator is deployed when the
Replicasentry shows1 available.NoteYou might experience a delay with the deployment if you have a slow connection to the OpenShift cluster and the User Operator images have not been downloaded before.
5.2. Deploy Kafka Connect Copia collegamentoCollegamento copiato negli appunti!
Kafka Connect is a tool for streaming data between Apache Kafka and external systems.
In AMQ Streams, Kafka Connect is deployed in distributed mode. Kafka Connect can also work in standalone mode, but this is not supported by AMQ Streams.
Using the concept of connectors, Kafka Connect provides a framework for moving large amounts of data into and out of your Kafka cluster while maintaining scalability and reliability.
Kafka Connect is typically used to integrate Kafka with external databases and storage and messaging systems.
The procedures in this section show how to:
-
Deploy a Kafka Connect cluster using a
KafkaConnectresource - Run multiple Kafka Connect instances
- Create a Kafka Connect image containing the connectors you need to make your connection
- Create and manage connectors using a KafkaConnector resource or the Kafka Connect REST API
- Deploy a KafkaConnector resource to Kafka Connect
- Restart a Kafka connector by annotating a KafkaConnector resource
- Restart a Kafka connector task by annotating a KafkaConnector resource
The term connector is used interchangeably to mean a connector instance running within a Kafka Connect cluster, or a connector class. In this guide, the term connector is used when the meaning is clear from the context.
5.2.1. Deploying Kafka Connect to your OpenShift cluster Copia collegamentoCollegamento copiato negli appunti!
This procedure shows how to deploy a Kafka Connect cluster to your OpenShift cluster using the Cluster Operator.
A Kafka Connect cluster is implemented as a Deployment with a configurable number of nodes (also called workers) that distribute the workload of connectors as tasks so that the message flow is highly scalable and reliable.
The deployment uses a YAML file to provide the specification to create a KafkaConnect resource.
AMQ Streams provides example configuration files. In this procedure, we use the following example file:
-
examples/connect/kafka-connect.yaml
Prerequisites
Procedure
Deploy Kafka Connect to your OpenShift cluster. Use the
examples/connect/kafka-connect.yamlfile to deploy Kafka Connect.oc apply -f examples/connect/kafka-connect.yamlVerify that Kafka Connect was successfully deployed:
oc get deployments
5.2.2. Kafka Connect configuration for multiple instances Copia collegamentoCollegamento copiato negli appunti!
If you are running multiple instances of Kafka Connect, you have to change the default configuration of the following config properties:
apiVersion: kafka.strimzi.io/v1beta2
kind: KafkaConnect
metadata:
name: my-connect
spec:
# ...
config:
group.id: connect-cluster
offset.storage.topic: connect-cluster-offsets
config.storage.topic: connect-cluster-configs
status.storage.topic: connect-cluster-status
# ...
# ...
Values for the three topics must be the same for all Kafka Connect instances with the same group.id.
Unless you change the default settings, each Kafka Connect instance connecting to the same Kafka cluster is deployed with the same values. What happens, in effect, is all instances are coupled to run in a cluster and use the same topics.
If multiple Kafka Connect clusters try to use the same topics, Kafka Connect will not work as expected and generate errors.
If you wish to run multiple Kafka Connect instances, change the values of these properties for each instance.
5.2.3. Extending Kafka Connect with connector plug-ins Copia collegamentoCollegamento copiato negli appunti!
The AMQ Streams container images for Kafka Connect include two built-in file connectors for moving file-based data into and out of your Kafka cluster.
| File Connector | Description |
|---|---|
|
| Transfers data to your Kafka cluster from a file (the source). |
|
| Transfers data from your Kafka cluster to a file (the sink). |
The procedures in this section show how to add your own connector classes to connector images by:
You create the configuration for connectors directly using the Kafka Connect REST API or KafkaConnector custom resources.
5.2.3.1. Creating a new container image automatically using AMQ Streams Copia collegamentoCollegamento copiato negli appunti!
This procedure shows how to configure Kafka Connect so that AMQ Streams automatically builds a new container image with additional connectors. You define the connector plugins using the .spec.build.plugins property of the KafkaConnect custom resource. AMQ Streams will automatically download and add the connector plugins into a new container image. The container is pushed into the container repository specified in .spec.build.output and automatically used in the Kafka Connect deployment.
Prerequisites
- The Cluster Operator must be deployed.
- A container registry.
You need to provide your own container registry where images can be pushed to, stored, and pulled from. AMQ Streams supports private container registries as well as public registries such as Quay or Docker Hub.
Procedure
Configure the
KafkaConnectcustom resource by specifying the container registry in.spec.build.output, and additional connectors in.spec.build.plugins:apiVersion: kafka.strimzi.io/v1beta2 kind: KafkaConnect metadata: name: my-connect-cluster spec:1 #... build: output:2 type: docker image: my-registry.io/my-org/my-connect-cluster:latest pushSecret: my-registry-credentials plugins:3 - name: debezium-postgres-connector artifacts: - type: tgz url: https://repo1.maven.org/maven2/io/debezium/debezium-connector-postgres/1.3.1.Final/debezium-connector-postgres-1.3.1.Final-plugin.tar.gz sha512sum: 962a12151bdf9a5a30627eebac739955a4fd95a08d373b86bdcea2b4d0c27dd6e1edd5cb548045e115e33a9e69b1b2a352bee24df035a0447cb820077af00c03 - name: camel-telegram artifacts: - type: tgz url: https://repo.maven.apache.org/maven2/org/apache/camel/kafkaconnector/camel-telegram-kafka-connector/0.7.0/camel-telegram-kafka-connector-0.7.0-package.tar.gz sha512sum: a9b1ac63e3284bea7836d7d24d84208c49cdf5600070e6bd1535de654f6920b74ad950d51733e8020bf4187870699819f54ef5859c7846ee4081507f48873479 #...Create or update the resource:
$ oc apply -f KAFKA-CONNECT-CONFIG-FILE- Wait for the new container image to build, and for the Kafka Connect cluster to be deployed.
- Use the Kafka Connect REST API or the KafkaConnector custom resources to use the connector plugins you added.
Additional resources
See the Using AMQ Streams on OpenShift guide for more information on:
5.2.3.2. Creating a Docker image from the Kafka Connect base image Copia collegamentoCollegamento copiato negli appunti!
This procedure shows how to create a custom image and add it to the /opt/kafka/plugins directory.
You can use the Kafka container image on Red Hat Ecosystem Catalog as a base image for creating your own custom image with additional connector plug-ins.
At startup, the AMQ Streams version of Kafka Connect loads any third-party connector plug-ins contained in the /opt/kafka/plugins directory.
Prerequisites
Procedure
Create a new
Dockerfileusingregistry.redhat.io/amq7/amq-streams-kafka-30-rhel8:2.0.1as the base image:FROM registry.redhat.io/amq7/amq-streams-kafka-30-rhel8:2.0.1 USER root:root COPY ./my-plugins/ /opt/kafka/plugins/ USER 1001Example plug-in file
$ tree ./my-plugins/ ./my-plugins/ ├── debezium-connector-mongodb │ ├── bson-3.4.2.jar │ ├── CHANGELOG.md │ ├── CONTRIBUTE.md │ ├── COPYRIGHT.txt │ ├── debezium-connector-mongodb-0.7.1.jar │ ├── debezium-core-0.7.1.jar │ ├── LICENSE.txt │ ├── mongodb-driver-3.4.2.jar │ ├── mongodb-driver-core-3.4.2.jar │ └── README.md ├── debezium-connector-mysql │ ├── CHANGELOG.md │ ├── CONTRIBUTE.md │ ├── COPYRIGHT.txt │ ├── debezium-connector-mysql-0.7.1.jar │ ├── debezium-core-0.7.1.jar │ ├── LICENSE.txt │ ├── mysql-binlog-connector-java-0.13.0.jar │ ├── mysql-connector-java-5.1.40.jar │ ├── README.md │ └── wkb-1.0.2.jar └── debezium-connector-postgres ├── CHANGELOG.md ├── CONTRIBUTE.md ├── COPYRIGHT.txt ├── debezium-connector-postgres-0.7.1.jar ├── debezium-core-0.7.1.jar ├── LICENSE.txt ├── postgresql-42.0.0.jar ├── protobuf-java-2.6.1.jar └── README.mdNoteThis example uses the Debezium connectors for MongoDB, MySQL, and PostgreSQL. Debezium running in Kafka Connect looks the same as any other Kafka Connect task.
- Build the container image.
- Push your custom image to your container registry.
Point to the new container image.
You can either:
Edit the
KafkaConnect.spec.imageproperty of theKafkaConnectcustom resource.If set, this property overrides the
STRIMZI_KAFKA_CONNECT_IMAGESvariable in the Cluster Operator.apiVersion: kafka.strimzi.io/v1beta2 kind: KafkaConnect metadata: name: my-connect-cluster spec:1 #... image: my-new-container-image2 config:3 #...or
-
In the
install/cluster-operator/060-Deployment-strimzi-cluster-operator.yamlfile, edit theSTRIMZI_KAFKA_CONNECT_IMAGESvariable to point to the new container image, and then reinstall the Cluster Operator.
Additional resources
See the Using AMQ Streams on OpenShift guide for more information on:
5.2.4. Creating and managing connectors Copia collegamentoCollegamento copiato negli appunti!
When you have created a container image for your connector plug-in, you need to create a connector instance in your Kafka Connect cluster. You can then configure, monitor, and manage a running connector instance.
A connector is an instance of a particular connector class that knows how to communicate with the relevant external system in terms of messages. Connectors are available for many external systems, or you can create your own.
You can create source and sink types of connector.
- Source connector
- A source connector is a runtime entity that fetches data from an external system and feeds it to Kafka as messages.
- Sink connector
- A sink connector is a runtime entity that fetches messages from Kafka topics and feeds them to an external system.
AMQ Streams provides two APIs for creating and managing connectors:
- KafkaConnector resources (referred to as KafkaConnectors)
- Kafka Connect REST API
Using the APIs, you can:
- Check the status of a connector instance
- Reconfigure a running connector
- Increase or decrease the number of connector tasks for a connector instance
- Restart connectors
- Restart connector tasks, including failed tasks
- Pause a connector instance
- Resume a previously paused connector instance
- Delete a connector instance
5.2.4.1. KafkaConnector resources Copia collegamentoCollegamento copiato negli appunti!
KafkaConnectors allow you to create and manage connector instances for Kafka Connect in an OpenShift-native way, so an HTTP client such as cURL is not required. Like other Kafka resources, you declare a connector’s desired state in a KafkaConnector YAML file that is deployed to your OpenShift cluster to create the connector instance. KafkaConnector resources must be deployed to the same namespace as the Kafka Connect cluster they link to.
You manage a running connector instance by updating its corresponding KafkaConnector resource, and then applying the updates. Annotations are used to manually restart connector instances and connector tasks. You remove a connector by deleting its corresponding KafkaConnector.
To ensure compatibility with earlier versions of AMQ Streams, KafkaConnectors are disabled by default. To enable them for a Kafka Connect cluster, you must use annotations on the KafkaConnect resource. For instructions, see Configuring Kafka Connect in the Using AMQ Streams on OpenShift guide.
When KafkaConnectors are enabled, the Cluster Operator begins to watch for them. It updates the configurations of running connector instances to match the configurations defined in their KafkaConnectors.
AMQ Streams provides example configuration files, including the following example KafkaConnector file:
-
examples/connect/source-connector.yaml.
You can use this example to create and manage a FileStreamSourceConnector and a FileStreamSinkConnector as described in Section 5.2.5, “Deploying the example KafkaConnector resources”.
5.2.4.2. Availability of the Kafka Connect REST API Copia collegamentoCollegamento copiato negli appunti!
The Kafka Connect REST API is available on port 8083 as the <connect-cluster-name>-connect-api service.
If KafkaConnectors are enabled, manual changes made directly using the Kafka Connect REST API are reverted by the Cluster Operator.
The operations supported by the REST API are described in the Apache Kafka documentation.
5.2.5. Deploying the example KafkaConnector resources Copia collegamentoCollegamento copiato negli appunti!
Use KafkaConnectors with Kafka Connect to stream data to and from a Kafka cluster.
AMQ Streams provides example configuration files. In this procedure, we use the following example file:
-
examples/connect/source-connector.yaml.
The file is used to create the following connector instances:
-
A
FileStreamSourceConnectorinstance that reads each line from the Kafka license file (the source) and writes the data as messages to a single Kafka topic. -
A
FileStreamSinkConnectorinstance that reads messages from the Kafka topic and writes the messages to a temporary file (the sink).
In a production environment, you prepare container images containing your desired Kafka Connect connectors, as described in Section 5.2.3, “Extending Kafka Connect with connector plug-ins”.
The FileStreamSourceConnector and FileStreamSinkConnector are provided as examples. Running these connectors in containers as described here is unlikely to be suitable for production use cases.
Prerequisites
- A Kafka Connect deployment
- KafkaConnectors are enabled in the Kafka Connect deployment
- The Cluster Operator is running
Procedure
Edit the
examples/connect/source-connector.yamlfile:apiVersion: kafka.strimzi.io/v1beta2 kind: KafkaConnector metadata: name: my-source-connector1 labels: strimzi.io/cluster: my-connect-cluster2 spec: class: org.apache.kafka.connect.file.FileStreamSourceConnector3 tasksMax: 24 config:5 file: "/opt/kafka/LICENSE"6 topic: my-topic7 # ...- 1
- Name of the KafkaConnector resource, which is used as the name of the connector. Use any name that is valid for an OpenShift resource.
- 2
- Name of the Kafka Connect cluster to create the connector instance in. Connectors must be deployed to the same namespace as the Kafka Connect cluster they link to.
- 3
- Full name or alias of the connector class. This should be present in the image being used by the Kafka Connect cluster.
- 4
- Maximum number of Kafka Connect
Tasksthat the connector can create. - 5
- Connector configuration as key-value pairs.
- 6
- This example source connector configuration reads data from the
/opt/kafka/LICENSEfile. - 7
- Kafka topic to publish the source data to.
Create the source
KafkaConnectorin your OpenShift cluster:oc apply -f examples/connect/source-connector.yamlCreate an
examples/connect/sink-connector.yamlfile:touch examples/connect/sink-connector.yamlPaste the following YAML into the
sink-connector.yamlfile:apiVersion: kafka.strimzi.io/v1beta2 kind: KafkaConnector metadata: name: my-sink-connector labels: strimzi.io/cluster: my-connect spec: class: org.apache.kafka.connect.file.FileStreamSinkConnector1 tasksMax: 2 config:2 file: "/tmp/my-file"3 topics: my-topic4 - 1
- Full name or alias of the connector class. This should be present in the image being used by the Kafka Connect cluster.
- 2
- Connector configuration as key-value pairs.
- 3
- Temporary file to publish the source data to.
- 4
- Kafka topic to read the source data from.
Create the sink
KafkaConnectorin your OpenShift cluster:oc apply -f examples/connect/sink-connector.yamlCheck that the connector resources were created:
oc get kctr --selector strimzi.io/cluster=MY-CONNECT-CLUSTER -o name my-source-connector my-sink-connectorReplace MY-CONNECT-CLUSTER with your Kafka Connect cluster.
In the container, execute
kafka-console-consumer.shto read the messages that were written to the topic by the source connector:oc exec MY-CLUSTER-kafka-0 -i -t -- bin/kafka-console-consumer.sh --bootstrap-server MY-CLUSTER-kafka-bootstrap.NAMESPACE.svc:9092 --topic my-topic --from-beginning
Source and sink connector configuration options
The connector configuration is defined in the spec.config property of the KafkaConnector resource.
The FileStreamSourceConnector and FileStreamSinkConnector classes support the same configuration options as the Kafka Connect REST API. Other connectors support different configuration options.
| Name | Type | Default value | Description |
|---|---|---|---|
|
| String | Null | Source file to write messages to. If not specified, the standard input is used. |
|
| List | Null | The Kafka topic to publish data to. |
| Name | Type | Default value | Description |
|---|---|---|---|
|
| String | Null | Destination file to write messages to. If not specified, the standard output is used. |
|
| List | Null | One or more Kafka topics to read data from. |
|
| String | Null | A regular expression matching one or more Kafka topics to read data from. |
5.2.6. Performing a restart of a Kafka connector Copia collegamentoCollegamento copiato negli appunti!
This procedure describes how to manually trigger a restart of a Kafka connector by using an OpenShift annotation.
Prerequisites
- The Cluster Operator is running.
Procedure
Find the name of the
KafkaConnectorcustom resource that controls the Kafka connector you want to restart:oc get KafkaConnectorTo restart the connector, annotate the
KafkaConnectorresource in OpenShift. For example, usingoc annotate:oc annotate KafkaConnector KAFKACONNECTOR-NAME strimzi.io/restart=trueWait for the next reconciliation to occur (every two minutes by default).
The Kafka connector is restarted, as long as the annotation was detected by the reconciliation process. When Kafka Connect accepts the restart request, the annotation is removed from the
KafkaConnectorcustom resource.
5.2.7. Performing a restart of a Kafka connector task Copia collegamentoCollegamento copiato negli appunti!
This procedure describes how to manually trigger a restart of a Kafka connector task by using an OpenShift annotation.
Prerequisites
- The Cluster Operator is running.
Procedure
Find the name of the
KafkaConnectorcustom resource that controls the Kafka connector task you want to restart:oc get KafkaConnectorFind the ID of the task to be restarted from the
KafkaConnectorcustom resource. Task IDs are non-negative integers, starting from 0.oc describe KafkaConnector KAFKACONNECTOR-NAMETo restart the connector task, annotate the
KafkaConnectorresource in OpenShift. For example, usingoc annotateto restart task 0:oc annotate KafkaConnector KAFKACONNECTOR-NAME strimzi.io/restart-task=0Wait for the next reconciliation to occur (every two minutes by default).
The Kafka connector task is restarted, as long as the annotation was detected by the reconciliation process. When Kafka Connect accepts the restart request, the annotation is removed from the
KafkaConnectorcustom resource.
5.3. Deploy Kafka MirrorMaker Copia collegamentoCollegamento copiato negli appunti!
The Cluster Operator deploys one or more Kafka MirrorMaker replicas to replicate data between Kafka clusters. This process is called mirroring to avoid confusion with the Kafka partitions replication concept. MirrorMaker consumes messages from the source cluster and republishes those messages to the target cluster.
5.3.1. Deploying Kafka MirrorMaker to your OpenShift cluster Copia collegamentoCollegamento copiato negli appunti!
This procedure shows how to deploy a Kafka MirrorMaker cluster to your OpenShift cluster using the Cluster Operator.
The deployment uses a YAML file to provide the specification to create a KafkaMirrorMaker or KafkaMirrorMaker2 resource depending on the version of MirrorMaker deployed.
Kafka MirrorMaker 1 (referred to as just MirrorMaker in the documentation) has been deprecated in Apache Kafka 3.0.0 and will be removed in Apache Kafka 4.0.0. As a result, the KafkaMirrorMaker custom resource which is used to deploy Kafka MirrorMaker 1 has been deprecated in AMQ Streams as well. The KafkaMirrorMaker resource will be removed from AMQ Streams when we adopt Apache Kafka 4.0.0. As a replacement, use the KafkaMirrorMaker2 custom resource with the IdentityReplicationPolicy.
AMQ Streams provides example configuration files. In this procedure, we use the following example files:
-
examples/mirror-maker/kafka-mirror-maker.yaml -
examples/mirror-maker/kafka-mirror-maker-2.yaml
Prerequisites
Procedure
Deploy Kafka MirrorMaker to your OpenShift cluster:
For MirrorMaker:
oc apply -f examples/mirror-maker/kafka-mirror-maker.yamlFor MirrorMaker 2.0:
oc apply -f examples/mirror-maker/kafka-mirror-maker-2.yamlVerify that MirrorMaker was successfully deployed:
oc get deployments
5.4. Deploy Kafka Bridge Copia collegamentoCollegamento copiato negli appunti!
The Cluster Operator deploys one or more Kafka bridge replicas to send data between Kafka clusters and clients via HTTP API.
5.4.1. Deploying Kafka Bridge to your OpenShift cluster Copia collegamentoCollegamento copiato negli appunti!
This procedure shows how to deploy a Kafka Bridge cluster to your OpenShift cluster using the Cluster Operator.
The deployment uses a YAML file to provide the specification to create a KafkaBridge resource.
AMQ Streams provides example configuration files. In this procedure, we use the following example file:
-
examples/bridge/kafka-bridge.yaml
Prerequisites
Procedure
Deploy Kafka Bridge to your OpenShift cluster:
oc apply -f examples/bridge/kafka-bridge.yamlVerify that Kafka Bridge was successfully deployed:
oc get deployments