Spring Cloud Data Flow is a toolkit for building data integration and real-time data processing pipelines.
Pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. This makes Spring Cloud Data Flow suitable for a range of data processing use cases, from import/export to event streaming and predictive analytics.
This chart will provision a fully functional and fully featured Spring Cloud Data Flow installation that can deploy and manage data processing pipelines in the cluster that it is deployed to.
MySQL is used as the data store for Spring Cloud Data Flow state and either RabbitMQ or Kafka is used as the messaging layer for streaming apps to communicate with one another.
For more information on Spring Cloud Data Flow and its capabilities, see it's documentation.
Assumes that serviceAccount credentials are available so the deployed Data Flow server can access the API server (Works on GKE and Minikube by default). See Configure Service Accounts for Pods
To install the chart with the release name my-release:
$ helm install --name my-release stable/spring-cloud-data-flowIf you are using a cluster that does not have a load balancer (like Minikube) then you can install using a NodePort:
$ helm install --name my-release --set server.service.type=NodePort stable/spring-cloud-data-flowRabbitMQ is the default messaging layer, Kafka can be enabled instead by using the following set flags to the helm command, for example:
--set kafka.enabled=true,rabbitmq.enabled=false
Only one messaging layer can be used at a given time. If RabbitMQ and Kafka are enabled, both charts will be installed with RabbitMQ being used in the deployment.
Note that this chart pulls in many different Docker images so can take a while to fully install.
The following tables list the configurable parameters and their default values.
| Parameter | Description | Default |
|---|---|---|
| rbac.create | Create RBAC configurations | true |
| Parameter | Description | Default |
|---|---|---|
| serviceAccount.create | Create ServiceAccount | true |
| serviceAccount.name | ServiceAccount name | (generated if not specified) |
| Parameter | Description | Default |
|---|---|---|
| server.version | The version/tag of the Data Flow server | 2.0.1.RELEASE |
| server.imagePullPolicy | The imagePullPolicy of the Data Flow server | IfNotPresent |
| server.service.type | The service type for the Data Flow server | LoadBalancer |
| server.platformName | The name of the configured platform account | default |
| server.service.externalPort | The external port for the Data Flow server | 80 |
| Parameter | Description | Default |
|---|---|---|
| skipper.version | The version/tag of the Skipper server | 2.0.0.RELEASE |
| skipper.imagePullPolicy | The imagePullPolicy of the Skipper server | IfNotPresent |
| skipper.platformName | The name of the configured platform account | default |
| skipper.service.type | The service type for the Skipper server | ClusterIP |
| Parameter | Description | Default |
|---|---|---|
| deployer.resourceLimits.cpu | Deployer resource limit for cpu | 500m |
| deployer.resourceLimits.memory | Deployer resource limit for memory | 1024Mi |
| deployer.readinessProbe.initialDelaySeconds | Deployer readiness probe initial delay | 120 |
| deployer.livenessProbe.initialDelaySeconds | Deployer liveness probe initial delay | 90 |
| Parameter | Description | Default |
|---|---|---|
| rabbitmq.enabled | Enable RabbitMQ as the middleware to use | true |
| rabbitmq.rabbitmqUsername | RabbitMQ user name | user |
| Parameter | Description | Default |
|---|---|---|
| kafka.enabled | Enable RabbitMQ as the middleware to use | false |
| kafka.replicas | The number of Kafka replicas to use | 1 |
| kafka.configurationOverrides | Kafka deployment configuration overrides | replication.factor=1, metrics.enabled=false |
| kafka.zookeeper.replicaCount | The number of ZooKeeper replicates to use | 1 |
| Parameter | Description | Default |
|---|---|---|
| mysql.mysqlDatabase | MySQL database name | dataflow |