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Alpakkeer

Note: The project is under active development and not ready for use yet.

Alpakkeer is an opinionated toolkit to build, run and operate light-weight integration applications based on Akka Streams and Alpakka.

Alpakkeer can be used with a Java or a Scala DSL.

public class HelloWorld {
   public static void main(String[] args) {
      Alpakkeer
       .create()
       .withJob(builder -> builder
          .create("sample-job")
          .runGraph((id, sb) -> SampleStreams
             .tweets()
             .via(sb.createCheckpointMonitor("tweet-count"))
             .to(Sink.ignore()))
          .withPrometheusMonitor()
          .withScheduledExecution(CronExpression.everyMinute())
          .build())
       .start();     
   }
}

This small application starts a server with a REST API to control your Akka Streams based jobs including metrics to monitor the stream with Prometheus and Grafana. Run the application and visit http://localhost:8042 to see all available endpoints and functions.

Continue with Tutorials or see the detailed Docs to discover more.

Main Features

Alpakkeer bundles various libraries and components to quickly build, run and operate light-weight integration applications:

  • A Web Server based on Javalin to provide simple access via REST APIs to manage Akka Streams processes and expose metrics to Prometheus and Grafana.

  • Configuration Management based on Lightbend Config plus some extensions for environment-based configurations and automatic mapping to POJOs.

  • Prometheus Client to record application and stream metrics. Alpakkeer also provides custom FlowStages to argument your stream with Akka Streams specific metrics. More Details ...

All components are made simply composable and accessible via an easy to use DSL for Java or Scala. Most components can also be easily replaced with different implementations or extended with custom logic.

Use Cases

Alternatives to Alpakkeer

Contribute

License

Building the Documentation

The documentation is based on MkDocs and MkDocs Material. To build and run the documentation Python is required.

pip install mkdocs mkdocs-material
mkdocs gh-deploy