Version: 1.4

Deployment Manager configuration

Configuration of Deployment Manager, which is component of the Designer that deploys scenario to given Engine (e.g. Streaming-Lite runtime or Flink in Streaming-Flink mode). Type of Deployment Manager is defined with type parameter, e.g. for running scenarios with Flink streaming job we would configure:

deploymentConfig {     
  type: "flinkStreaming"
  restUrl: "http://localhost:8081"
}

Look at configuration areas to understand where Deployment Manager configuration should be placed in Nussknacker configuration.

Streaming-Lite on Kubernetes

Please remember, that K8s Deployment Manager has to be run with properly configured K8s access. If you install the Designer in K8s cluster (e.g. via Helm chart) this comes out of the box. If you want to run the Designer outside the cluster, you have to configure .kube/config properly.

streaming-lite-k8s Deployment Manager has the following configuration options:

Parameter	Type	Default value	Description
dockerImageName	string	touk/nussknacker-lite-kafka-runtime	Runtime image (please note that it's not touk/nussknacker - which is designer image)
dockerImageTag	string	current nussknacker version
scalingConfig	{fixedReplicasCount: int} or {tasksPerReplica: int}	{ tasksPerReplica: 4 }	see below
configExecutionOverrides	config	{}	see below
k8sDeploymentConfig	config	{}	see below
nussknackerInstanceName	string	{?NUSSKNACKER_INSTANCE_NAME}	see below
logbackConfigPath	string	{}	see below

Customizing K8s deployment

By default, each scenario creates K8s Deployment. By default, Nussknacker will create following deployment:

apiVersion: apps/v1
kind: Deployment
metadata:
  annotations:
    nussknacker.io/scenarioVersion: |-   
      {
        "versionId" : 2,
        "processName" : "DetectLargeTransactions",
        "processId" : 7,
        "user" : "jdoe@sample.pl",
        "modelVersion" : 2
      }
  labels:
    nussknacker.io/nussknackerInstanceName: "helm-release-name"
    nussknacker.io/scenarioId: "7"
    nussknacker.io/scenarioName: detectlargetransactions-080df2c5a7
    nussknacker.io/scenarioVersion: "2"
spec:
  minReadySeconds: 10
  selector:
    matchLabels:
      nussknacker.io/scenarioId: "7"
  strategy:
    type: Recreate
  template:
    metadata:
      labels:
        nussknacker.io/scenarioId: "7"
        nussknacker.io/scenarioName: detectlargetransactions-080df2c5a7
        nussknacker.io/scenarioVersion: "2"
      name: scenario-7-detectlargetransactions
    spec:
      containers:
      - env:
        - name: SCENARIO_FILE
          value: /data/scenario.json
        - name: CONFIG_FILE
          value: /opt/nussknacker/conf/application.conf,/data/modelConfig.conf
        - name: DEPLOYMENT_CONFIG_FILE
          value: /data/deploymentConfig.conf
        - name: LOGBACK_FILE
          value: /data/logback.xml
        - name: POD_NAME
          valueFrom:
            fieldRef:
              apiVersion: v1
              fieldPath: metadata.name
        image: touk/nussknacker-lite-kafka-runtime:1.3.0 # filled with dockerImageName/dockerImageTag 
        livenessProbe:
          httpGet:
            path: /alive
            port: 8558
            scheme: HTTP
        name: runtime
        readinessProbe:
          failureThreshold: 60
          httpGet:
            path: /ready
            port: 8558
            scheme: HTTP
          periodSeconds: 1
        volumeMounts:
        - mountPath: /data
          name: configmap
      volumes:
      - configMap:
          defaultMode: 420
          name: scenario-7-detectlargetransactions-ad0834f298
        name: configmap

You can customize it adding e.g. own volumes, deployment strategy etc. with k8sDeploymentConfig settings, e.g. add additional custom label environment variable to the container, add custom sidecar container:

spec {
 metadata: {
    labels: {
      myCustomLabel: addMeToDeployment
    }
 }
 containers: [
    {
      #`runtime` is default container executing scenario 
      name: runtime
      env: [
        CUSTOM_VAR: CUSTOM_VALUE
      ]
    },
    {
      name: sidecar-log-collector
      image: sidecar-log-collector:latest
      command: [ "command-to-upload", "/remote/path/of/flink-logs/" ]
    }
 ] 
}

This config will be merged into final deployment. Please note that you cannot override names or labels configured by Nussknacker.

Overriding configuration passed to runtime.

By default, configuration of Streaming-Lite runtime consists of

application.conf from runtime image - see this for default.
the configuration from modelConfig

In some circumstances you want to change values in modelConfig without having to modify base image. E.g. different accounts/credentials should be used in Designer and in Runtime. For those cases you can use configExecutionOverrides setting:

deploymentConfig {     
  configExecutionOverrides {
    password: "sfd2323afdf" # this will be used in the Runtime
  }
}
modelConfig {
  password: "aaqwmpor909232" # this will be used in the Designer
}

Configuring replicas count

Each scenario has its own, configured parallelism. It describes how many worker threads, across all replicas, should be used to process events. With scalingConfig one can affect replicas count (each replica receives the same number of worker threads). Following options are possible:

{ fixedReplicasCount: x }
{ tasksPerReplica: y }
by default tasksPerReplica: 4

Please note that:

it's not possible to set both config options at the same time
due to rounding, exact workers count may be different from parallelism (e.g. for fixedReplicasCount = 3, parallelism = 5, there will be 2 tasks per replica, total workers = 6)

Nussknacker instance name

Value of nussknackerInstanceName will be passed to scenario runtime pods as a nussknacker.io/nussknackerInstanceName Kubernetes label. In a standard scenario, its value is taken from Nussknacker's pod app.kubernetes.io/instance label which, when installed using helm should be set to helm release name.

It can be used to identify scenario deployments and its resources bound to a specific Nussknacker helm release.

Configuring runtime logging

With logbackConfigPath you can provide path to your own logback config file, which will be used by runtime containers. This configuration is optional, if skipped default logging configuration will be used. Please mind, that apart whether you will provide your own logging configuration or use default, you can still modify it in runtime (for each scenario deployment separately) as described here

Configuring Prometheus metrics

Just like in [Designer installation](./Installation.md#Basic environment variables), you can attach JMX Exporter for Prometheus to your runtime pods. Pass PROMETHEUS_METRICS_PORT environment variable to enable agent, and simultaneously define port on which metrics will be exposed. By default, agent is configured to expose basic jvm metrics, but you can provide your own configuration file by setting PROMETHEUS_AGENT_CONFIG_FILE environment, which has to point to it.

Request-Response embedded

request-response-embedded Deployment Manager has the following configuration options:

Parameter	Type	Default value	Description
interface	string	0.0.0.0	Interface on which REST API of scenarios will be exposed
port	int	8181	Port on which REST API of scenarios will be exposed

Streaming-Flink

flinkStreaming Deployment Manager has the following configuration options:

Parameter	Type	Default value	Description
restUrl	string		The only required parameter, REST API endpoint of the Flink cluster
jobManagerTimeout	duration	1 minute	Timeout for communication with FLink cluster. Consider extending if e.g. you have long savepoint times etc.
shouldVerifyBeforeDeploy	boolean	true	By default, before redeployment of scenario with state from savepoint, verification of savepoint compatibility is performed. There are some cases when it can be too time consuming or not possible. Use this flag to disable it.
queryableStateProxyUrl	string		Some Nussknacker extensions require access to Flink queryable state. This should be comma separated list of `host:port` addresses of queryable state proxies of all taskmanagers in the cluster
shouldCheckAvailableSlots	boolean	true	When set to true, Nussknacker checks if there are free slots to run new job. This check should be disabled on Flink Kubernetes Native deployments, where Taskmanager is started on demand.

Deployment Manager configuration

Streaming-Lite on Kubernetes​

Customizing K8s deployment​

Overriding configuration passed to runtime.​

Configuring replicas count​

Nussknacker instance name​

Configuring runtime logging​

Configuring Prometheus metrics​

Request-Response embedded​

Streaming-Flink​