Chapter 2. Common configuration properties

Use the replicas property to configure replicas.

The type of replication depends on the resource.

Use the bootstrapServers property to configure a list of bootstrap servers.

The bootstrap server lists can refer to Kafka clusters that are not deployed in the same OpenShift cluster. They can also refer to a Kafka cluster not deployed by Streams for Apache Kafka.

If on the same OpenShift cluster, each list must ideally contain the Kafka cluster bootstrap service which is named CLUSTER-NAME-kafka-bootstrap and a port number. If deployed by Streams for Apache Kafka but on different OpenShift clusters, the list content depends on the approach used for exposing the clusters (routes, ingress, nodeports or loadbalancers).

When using Kafka with a Kafka cluster not managed by Streams for Apache Kafka, you can specify the bootstrap servers list according to the configuration of the given cluster.

You can incorporate SSL configuration and cipher suite specifications to further secure TLS-based communication between your client application and a Kafka cluster. In addition to the standard TLS configuration, you can specify a supported TLS version and enable cipher suites in the configuration for the Kafka broker. You can also add the configuration to your clients if you wish to limit the TLS versions and cipher suites they use. The configuration on the client must only use protocols and cipher suites that are enabled on the broker.

A cipher suite is a set of security mechanisms for secure connection and data transfer. For example, the cipher suite TLS_AES_256_GCM_SHA384 is composed of the following mechanisms, which are used in conjunction with the TLS protocol:

The combination is encapsulated in the TLS_AES_256_GCM_SHA384 cipher suite specification.

The ssl.enabled.protocols property specifies the available TLS versions that can be used for secure communication between the cluster and its clients. The ssl.protocol property sets the default TLS version for all connections, and it must be chosen from the enabled protocols. Use the ssl.endpoint.identification.algorithm property to enable or disable hostname verification (configurable only in components based on Kafka clients - Kafka Connect, MirrorMaker 1/2, and Kafka Bridge).

# ...
config:
  ssl.cipher.suites: TLS_AES_256_GCM_SHA384, TLS_ECDHE_RSA_WITH_AES_256_GCM_SHA384 1
  ssl.enabled.protocols: TLSv1.3, TLSv1.2 2
  ssl.protocol: TLSv1.3 3
  ssl.endpoint.identification.algorithm: HTTPS 4
# ...

Having set tls to configure TLS encryption, use the trustedCertificates property to provide a list of secrets with key names under which the certificates are stored in X.509 format.

You can use the secrets created by the Cluster Operator for the Kafka cluster, or you can create your own TLS certificate file, then create a Secret from the file:

oc create secret generic MY-SECRET \
--from-file=MY-TLS-CERTIFICATE-FILE.crt

tls:
  trustedCertificates:
    - secretName: my-cluster-cluster-cert
      certificate: ca.crt
    - secretName: my-cluster-cluster-cert
      certificate: ca2.crt

If certificates are stored in the same secret, it can be listed multiple times.

If you want to enable TLS encryption, but use the default set of public certification authorities shipped with Java, you can specify trustedCertificates as an empty array:

tls:
  trustedCertificates: []

For information on configuring mTLS authentication, see the KafkaClientAuthenticationTls schema reference.

Configure resource requests and limits to control resources for Streams for Apache Kafka containers. You can specify requests and limits for memory and cpu resources. The requests should be enough to ensure a stable performance of Kafka.

How you configure resources in a production environment depends on a number of factors. For example, applications are likely to be sharing resources in your OpenShift cluster.

For Kafka, the following aspects of a deployment can impact the resources you need:

The values specified for resource requests are reserved and always available to the container. Resource limits specify the maximum resources that can be consumed by a given container. The amount between the request and limit is not reserved and might not be always available. A container can use the resources up to the limit only when they are available. Resource limits are temporary and can be reallocated.

If you set limits without requests or vice versa, OpenShift uses the same value for both. Setting equal requests and limits for resources guarantees quality of service, as OpenShift will not kill containers unless they exceed their limits.

You can configure resource requests and limits for one or more supported resources.

apiVersion: kafka.strimzi.io/v1beta2
kind: Kafka
metadata:
  name: my-cluster
spec:
  kafka:
    #...
    resources:
      requests:
        memory: 64Gi
        cpu: "8"
      limits:
        memory: 64Gi
        cpu: "12"
  entityOperator:
    #...
    topicOperator:
      #...
      resources:
        requests:
          memory: 512Mi
          cpu: "1"
        limits:
          memory: 512Mi
          cpu: "1"

Resource requests and limits for the Topic Operator and User Operator are set in the Kafka resource.

If the resource request is for more than the available free resources in the OpenShift cluster, the pod is not scheduled.

Use the image property to configure the container image used by the component.

Overriding container images is recommended only in special situations where you need to use a different container registry or a customized image.

For example, if your network does not allow access to the container repository used by Streams for Apache Kafka, you can copy the Streams for Apache Kafka images or build them from the source. However, if the configured image is not compatible with Streams for Apache Kafka images, it might not work properly.

A copy of the container image might also be customized and used for debugging.

You can specify which container image to use for a component using the image property in the following resources:

Configuring the image property for Kafka, Kafka Connect, and Kafka MirrorMaker

Kafka, Kafka Connect, and Kafka MirrorMaker support multiple versions of Kafka. Each component requires its own image. The default images for the different Kafka versions are configured in the following environment variables:

These environment variables contain mappings between Kafka versions and corresponding images. The mappings are used together with the image and version properties to determine the image used:

The image and version for the components can be configured in the following properties:

Configuring the image property in other resources

For the image property in the custom resources for other components, the given value is used during deployment. If the image property is not set, the container image specified as an environment variable in the Cluster Operator configuration is used. If an image name is not defined in the Cluster Operator configuration, then a default value is used.

For more information on image environment variables, see Configuring the Cluster Operator.

apiVersion: kafka.strimzi.io/v1beta2
kind: Kafka
metadata:
  name: my-cluster
spec:
  kafka:
    # ...
    image: my-org/my-image:latest
    # ...
  zookeeper:
    # ...

Use the livenessProbe and readinessProbe properties to configure healthcheck probes supported in Streams for Apache Kafka.

Healthchecks are periodical tests which verify the health of an application. When a Healthcheck probe fails, OpenShift assumes that the application is not healthy and attempts to fix it.

For more details about the probes, see Configure Liveness and Readiness Probes.

Both livenessProbe and readinessProbe support the following options:

# ...
readinessProbe:
  initialDelaySeconds: 15
  timeoutSeconds: 5
livenessProbe:
  initialDelaySeconds: 15
  timeoutSeconds: 5
# ...

For more information about the livenessProbe and readinessProbe options, see the Probe schema reference.

Use the metricsConfig property to enable and configure Prometheus metrics.

The metricsConfig property contains a reference to a ConfigMap that has additional configurations for the Prometheus JMX Exporter. Streams for Apache Kafka supports Prometheus metrics using Prometheus JMX exporter to convert the JMX metrics supported by Apache Kafka and ZooKeeper to Prometheus metrics.

To enable Prometheus metrics export without further configuration, you can reference a ConfigMap containing an empty file under metricsConfig.valueFrom.configMapKeyRef.key. When referencing an empty file, all metrics are exposed as long as they have not been renamed.

kind: ConfigMap
apiVersion: v1
metadata:
  name: my-configmap
data:
  my-key: |
    lowercaseOutputName: true
    rules:
    # Special cases and very specific rules
    - pattern: kafka.server<type=(.+), name=(.+), clientId=(.+), topic=(.+), partition=(.*)><>Value
      name: kafka_server_$1_$2
      type: GAUGE
      labels:
       clientId: "$3"
       topic: "$4"
       partition: "$5"
    # further configuration

apiVersion: kafka.strimzi.io/v1beta2
kind: Kafka
metadata:
  name: my-cluster
spec:
  kafka:
    # ...
    metricsConfig:
      type: jmxPrometheusExporter
      valueFrom:
        configMapKeyRef:
          name: my-config-map
          key: my-key
    # ...
  zookeeper:
    # ...

When metrics are enabled, they are exposed on port 9404.

When the metricsConfig (or deprecated metrics) property is not defined in the resource, the Prometheus metrics are disabled.

For more information about setting up and deploying Prometheus and Grafana, see Introducing Metrics to Kafka.

The following Streams for Apache Kafka components run inside a Java Virtual Machine (JVM):

To optimize their performance on different platforms and architectures, you configure the jvmOptions property in the following resources:

You can specify the following options in your configuration:

Specify heap size to have more control over the memory allocated to your JVM. Heap sizes should make the best use of a container’s memory limit (and request) without exceeding it. Heap size and any other memory requirements need to fit within a specified memory limit. If you don’t specify heap size in your configuration, but you configure a memory resource limit (and request), the Cluster Operator imposes default heap sizes automatically. The Cluster Operator sets default maximum and minimum heap values based on a percentage of the memory resource configuration.

The following table shows the default heap values.

If a memory limit (and request) is not specified, a JVM’s minimum heap size is set to 128M. The JVM’s maximum heap size is not defined to allow the memory to increase as needed. This is ideal for single node environments in test and development.

Setting an appropriate memory request can prevent the following:

In this example, the JVM uses 2 GiB (=2,147,483,648 bytes) for its heap. Total JVM memory usage can be a lot more than the maximum heap size.

# ...
jvmOptions:
  "-Xmx": "2g"
  "-Xms": "2g"
# ...

Setting the same value for initial (-Xms) and maximum (-Xmx) heap sizes avoids the JVM having to allocate memory after startup, at the cost of possibly allocating more heap than is really needed.

jvmOptions:
  "-XX":
    "UseG1GC": "true"
    "MaxGCPauseMillis": "20"
    "InitiatingHeapOccupancyPercent": "35"
    "ExplicitGCInvokesConcurrent": "true"

-XX:+UseG1GC -XX:MaxGCPauseMillis=20 -XX:InitiatingHeapOccupancyPercent=35 -XX:+ExplicitGCInvokesConcurrent -XX:-UseParNewGC

jvmOptions:
  javaSystemProperties:
    - name: javax.net.debug
      value: ssl

For more information about the jvmOptions, see the JvmOptions schema reference.

The jvmOptions property also allows you to enable and disable garbage collector (GC) logging. GC logging is disabled by default. To enable it, set the gcLoggingEnabled property as follows:

# ...
jvmOptions:
  gcLoggingEnabled: true
# ...