If Docker does not suit your needs, you can manually install the parts you need to run Spring Cloud Data Flow.
To begin, you need to download the server jars. To do so:
Download the Spring Cloud Data Flow Server and shell by using the following commands:
wget https://repo.spring.io/release/org/springframework/cloud/spring-cloud-dataflow-server/2.2.3.RELEASE/spring-cloud-dataflow-server-2.2.3.RELEASE.jar wget https://repo.spring.io/release/org/springframework/cloud/spring-cloud-dataflow-shell/2.2.3.RELEASE/spring-cloud-dataflow-shell-2.2.3.RELEASE.jar
Download Skipper by running the following command:
If you're interested in trying out the latest
BUILD-SNAPSHOT (aka: snapshot build from the
master branch) of SCDF and Skipper's upstream versions, please use the following
wget https://repo.spring.io/snapshot/org/springframework/cloud/spring-cloud-dataflow-server/2.2.4.BUILD-SNAPSHOT/spring-cloud-dataflow-server-2.2.4.BUILD-SNAPSHOT.jar wget https://repo.spring.io/snapshot/org/springframework/cloud/spring-cloud-dataflow-shell/2.2.4.BUILD-SNAPSHOT/spring-cloud-dataflow-shell-2.2.4.BUILD-SNAPSHOT.jar
These instructions require that RabbitMQ be running on the same machine as Skipper, Spring Cloud Data Flow server, and Shell.
To install and run the RabbitMQ docker image, use the following command:
docker run -d --hostname rabbitmq --name rabbitmq -p 15672:15672 -p 5672:5672 rabbitmq:3.7.14-management
Now you need to start the applications that comprise the server. To do so:
Start Skipper. To do so, in the directory where you downloaded Skipper, run the server by using
java -jar, as follows:
java -jar spring-cloud-skipper-server-2.1.4.RELEASE.jar
Start the Data Flow Server. To do so, in a different terminal window and in the directory where you downloaded Data Flow, run the server by using
java -jar, as follows:
java -jar spring-cloud-dataflow-server-2.2.3.RELEASE.jar
If Skipper and the Data Flow server are not running on the same host, set the
spring.cloud.skipper.client.serverUriconfiguration property to the location of Skipper, as shown in the following example:
java -jar spring-cloud-dataflow-server-2.2.3.RELEASE.jar --spring.cloud.skipper.client.serverUri=https://184.108.40.206:7577/api
If you want to use the Spring Cloud Data Flow shell, start it with the following command:
java -jar spring-cloud-dataflow-shell-2.2.3.RELEASE.jar
If the Data Flow Server and shell are not running on the same host, you can also point the shell to the Data Flow server URL by using the
dataflow config servercommand in Shell, as the following example shows:
server-unknown:>dataflow config server https://198.51.100.0 Successfully targeted https://198.51.100.0
Alternatively, you can pass in the
--dataflow.uricommand line option. The shell’s
--helpcommand line option shows what is available.
If you run Spring Cloud Data Flow Server behind a proxy server (such
as Zuul), you may also need to set
server.use-forward-headers property to
true. An example that
uses Zuul is available in the Spring Cloud Data Flow Samples
on GitHub. Additional information is also available in the Spring Boot Reference Guide.
You can now navigate to Spring Cloud Data Flow Dashboard. In your browser, navigate to the Spring Cloud Data Flow Dashboard URL.
All the prebuilt streaming applications:
- Are available as Apache Maven artifacts or Docker images.
- Use RabbitMQ or Apache Kafka.
- Support monitoring through Prometheus and InfluxDB.
- Contain metadata for application properties used in the UI and code completion in the shell.
You can register applications individually by using the
app register command or in bulk by using the
app import command.
There are also bulk-registration links that represent the group of prebuilt applications for a specific release, which are useful for getting started.
You can register stream and task applications by using the UI or the shell.
For streams, depending on whether you use Kafka or RabbitMQ, you can register the applications by using the respective URLs:
- Kafka - https://dataflow.spring.io/kafka-maven-latest
- RabbitMQ - https://dataflow.spring.io/rabbitmq-maven-latest
For tasks, you can use the following URL: https://dataflow.spring.io/task-maven-latest
From the Data Flow Shell, you can bulk import and register the applications, as the following example shows:
dataflow:>app import --uri https://dataflow.spring.io/kafka-maven-latest