Deployment and Operations #

Stateful Functions runtime, which manages state and messaging for an application, is built on top of Apache Flink, which means it inherits Flink’s deployment and operations model. Read through the official Apache Flink documentation to learn how to run and maintain an application in production. The following pages outline Stateful Functions' specific concepts, configurations, and metrics.

Images #

The recommended deployment mode for Stateful Functions runtime is to use the official Docker image. This way, user code does not need to package any Apache Flink components. The provided image allows teams to package their applications with all the necessary runtime dependencies quickly.

The community provides images containing the entire Stateful Functions runtime: apache/flink-statefun:3.0.0. All you need to do is attach your module configurations to the container.

Deployment #

The packaged image can then be deployed as a standalone Flink cluster on Kubernetes.

After creating the below cluster components, the application can be launched using the kubectl command.

# Configuration and service definition
$ kubectl create -f application-module.yaml
$ kubectl create -f flink-config.yaml
$ kubectl create -f jobmanager-service.yaml

# Deploy the StateFun runtime
$ kubectl create -f jobmanager-job.yaml
$ kubectl create -f taskmanager-job-deployment-yaml

To terminate the cluster, simply delete the deployments.

$ kubectl delete -f taskmanager-job-deployment-yaml
$ kubectl delete -f jobmanager-job.yaml
$ kubectl delete -f jobmanager-service.yaml
$ kubectl delete -f flink-config.yaml
$ kubectl delete -f application-module.yaml

Cluster Components #

application-module.yaml

The application function and io module configuration. See the full documentation for more details.

apiVersion: v1
kind: ConfigMap
metadata:
  name: application-module
  namespace: statefun
  labels:
    app: statefun
data:
  module.yaml: |+
    version: "3.0"
    module:
      meta:
        type: remote
      spec:
        endpoints:
        ingresses:
        egresses:

flink-config.yaml

flink-config.yaml contains all Flink runtime configurations for the cluster, including both Apache Flink configurations and StatFun specific configurations. In the Apache Flink documentation, you will often see this referred to as the flink-conf.yaml file.

apiVersion: v1
kind: ConfigMap
metadata:
  name: flink-config
  labels:
    app: statefun
data:
  flink-conf.yaml: |+
    jobmanager.rpc.address: statefun-master
    taskmanager.numberOfTaskSlots: 1
    blob.server.port: 6124
    jobmanager.rpc.port: 6123
    taskmanager.rpc.port: 6122
    classloader.parent-first-patterns.additional: org.apache.flink.statefun;org.apache.kafka;com.google.protobuf
    state.checkpoints.dir: s3://my-checkpoint-bucket
    state.backend: rocksdb
    state.backend.rocksdb.timer-service.factory: ROCKSDB
    state.backend.incremental: true
    execution.checkpointing.interval: 10sec
    execution.checkpointing.mode: EXACTLY_ONCE
    restart-strategy: fixed-delay
    restart-strategy.fixed-delay.attempts: 2147483647
    restart-strategy.fixed-delay.delay: 1sec
    jobmanager.memory.process.size: 1g
    taskmanager.memory.process.size: 1g
    parallelism.default: 3    
  log4j-console.properties: |+
    rootLogger.level = INFO
    rootLogger.appenderRef.console.ref = ConsoleAppender
    rootLogger.appenderRef.rolling.ref = RollingFileAppender
    logger.akka.name = akka
    logger.akka.level = INFO
    logger.kafka.name= org.apache.kafka
    logger.kafka.level = INFO
    logger.hadoop.name = org.apache.hadoop
    logger.hadoop.level = INFO
    logger.zookeeper.name = org.apache.zookeeper
    logger.zookeeper.level = INFO
    appender.console.name = ConsoleAppender
    appender.console.type = CONSOLE
    appender.console.layout.type = PatternLayout
    appender.console.layout.pattern = %d{yyyy-MM-dd HH:mm:ss,SSS} %-5p %-60c %x - %m%n
    appender.rolling.name = RollingFileAppender
    appender.rolling.type = RollingFile
    appender.rolling.append = false
    appender.rolling.fileName = ${sys:log.file}
    appender.rolling.filePattern = ${sys:log.file}.%i
    appender.rolling.layout.type = PatternLayout
    appender.rolling.layout.pattern = %d{yyyy-MM-dd HH:mm:ss,SSS} %-5p %-60c %x - %m%n
    appender.rolling.policies.type = Policies
    appender.rolling.policies.size.type = SizeBasedTriggeringPolicy
    appender.rolling.policies.size.size=100MB
    appender.rolling.strategy.type = DefaultRolloverStrategy
    appender.rolling.strategy.max = 10
    logger.netty.name = org.apache.flink.shaded.akka.org.jboss.netty.channel.DefaultChannelPipeline
    logger.netty.level = OFF

jobmanager-service.yaml

apiVersion: v1
kind: Service
metadata:
  name: flink-jobmanager
spec:
  type: ClusterIP
  ports:
  - name: rpc
    port: 6123
  - name: blob-server
    port: 6124
  - name: webui
    port: 8081
  selector:
    app: statefun
    component: jobmanager

jobmanager-rest-service.yaml

An optional service that exposes the jobmanager rest port as a public Kubernetes nodes port.

apiVersion: v1
kind: Service
metadata:
  name: statefun-jobmanager-rest
spec:
  type: NodePort
  ports:
  - name: rest
    port: 8081
    targetPort: 8081
    nodePort: 30081
  selector:
    app: statefun
    component: jobmanager

jobmanager-application.yaml

apiVersion: apps/v1
kind: Deployment
metadata:
  name: statefun-jobmanager
spec:
  replicas: 1
  selector:
    matchLabels:
      app: statefun
      component: jobmanager
  template:
    metadata:
      labels:
        app: statefun
        component: master
    spec:
      containers:
        - name: master
          image: apache/flink-statefun:3.0.0
          imagePullPolicy: Always
          env:
            - name: ROLE
              value: master
            - name: MASTER_HOST
              value: statefun-jobmanager
          resources:
            requests:
              memory: "1.5Gi"
          ports:
            - containerPort: 6123
              name: rpc
            - containerPort: 6124
              name: blob
            - containerPort: 8081
              name: ui
          livenessProbe:
            tcpSocket:
              port: 6123
            initialDelaySeconds: 30
            periodSeconds: 60
          volumeMounts:
            - name: flink-config-volume
              mountPath: /opt/flink/conf
            - name: application-module
              mountPath: /opt/statefun/modules/application-module
      volumes:
        - name: flink-config-volume
          configMap:
            name: flink-config
            items:
              - key: flink-conf.yaml
                path: flink-conf.yaml
              - key: log4j-console.properties
                path: log4j-console.properties
        - name: application-module
          configMap:
            name: application-module
            items:
              - key: module.yaml
                path: module.yaml

taskmanager-job-deployment.yaml

apiVersion: apps/v1
kind: Deployment
metadata:
  name: statefun-worker
  namespace: statefun
spec:
  replicas: 3
  selector:
    matchLabels:
      app: statefun
      component: worker
  template:
    metadata:
      labels:
        app: statefun
        component: worker
    spec:
      containers:
        - name: worker
          image: apache/flink-statefun:3.0.0
          imagePullPolicy: Always
          env:
            - name: ROLE
              value: worker
            - name: MASTER_HOST
              value: statefun-jobmanager
          resources:
            requests:
              memory: "1.5Gi"
          ports:
            - containerPort: 6122
              name: rpc
            - containerPort: 6124
              name: blob
            - containerPort: 8081
              name: ui
          livenessProbe:
            tcpSocket:
              port: 6122
            initialDelaySeconds: 30
            periodSeconds: 60
          volumeMounts:
            - name: flink-config-volume
              mountPath: /opt/flink/conf
            - name: greeter-module
              mountPath: /opt/statefun/modules/greeter
      volumes:
        - name: flink-config-volume
          configMap:
            name: flink-config
            items:
              - key: flink-conf.yaml
                path: flink-conf.yaml
              - key: log4j-console.properties
                path: log4j-console.properties
        - name: application-module
          configMap:
            name: application-module
            items:
              - key: module.yaml
                path: module.yaml