Session clusters are long-lived Apache Flink® clusters that can be used to execute multiple applications simultaneously or run short-lived, interactive jobs on demand. It is possible to execute Deployments on session clusters by using session mode.
Support for session clusters currently has some limitations compared with Deployments:
SSL/TLS: Auto-provisioned SSL/TLS for Flink intra-cluster and external communication is not supported. SSL/TLS has to be configured manually.
Autopilot: Autoscaling is not supported for session clusters and limited to Deployments running in session mode.
Session clusters are managed via namespaced SessionCluster resources which are configured similarly to Deployments. However, SessionClusters have fewer configurable options than Deployments since this resource only configures the Flink cluster itself and not the applications that will run on it.
A SessionCluster resource has a desired state specified at
spec.state. The desired state can be either:
- RUNNING when the cluster should be provisioned and kept running, or
- STOPPED when the cluster should be torn down, along with all currently running applications
All Deployments running on a session cluster must be terminated before the session cluster can be stopped.
Changing a Running SessionCluster¶
Only the desired state and number of TaskManagers of a session cluster may be changed while the cluster is in a non-terminal state non-terminal-state. A SessionCluster is in a “terminal state” when its desired state is
STOPPED and there are no in-progress operations on the cluster, such as when the cluster is starting, stopping, or being updated.
Scaling down a running session cluster (by reducing the value of
can cause applications running on the cluster to restart.
The following snippet is a complete example of a SessionCluster, including optional keys.
kind: SessionCluster apiVersion: v1 metadata: name: labels: env: testing spec: state: RUNNING deploymentTargetName: default flinkVersion: 1.12 flinkImageRegistry: registry.ververica.com/v2.4 flinkImageRepository: flink flinkImageTag: 1.12.7-stream2-scala_2.12 numberOfTaskManagers: 5 resources: jobmanager: cpu: 2 memory: 1g taskmanager: cpu: 16 memory: 32g flinkConfiguration: taskmanager.numberOfTaskSlots: 32 logging: loggingProfile: default log4jLoggers: "": INFO org.apache.flink.streaming.examples: DEBUG kubernetes: pods: envVars: - name: KEY value: VALUE