Debugging Streamlets

Debugging runLocal

By default Cloudflow runs on debug mode when runLocal. In the output we can see the listening port for each Streamlet.

[info] listening for debugging '[streamlet-name]' at 'localhost:[port]'

We can attach to this process by adding a remote configuration in the IDE of our choice. This Run/Debug configuration for the JVM must have the same port of the Streamlet we want to debug. See the following for an example configuration:

-agentlib:jdwp=transport=dt_socket,server=y,suspend=n,address=*:[port]

Debugging Remote

Debugging a remote application is possible just by applying the standard configuration to debugging a remote JVM. That is, adding a conf like this to JAVA_OPTS through our configuration model before we deploy or configure our Cloudflow app.

-agentlib:jdwp=transport=dt_socket,server=y,suspend=n,address=5005

As we’ve seen in the Configuration model, adding these parameters to JAVA_OPTS can be done at the Streamlet level or runtime level. In this example, we are adding it to all Akka streamlets.

cloudflow.akka.runtime {
  kubernetes.pods.pod {
    containers.container {
      env = [
            { name = "JAVA_OPTS"
              value = "-agentlib:jdwp=transport=dt_socket,server=y,suspend=n,address=5005"
            }
          ]
    }
  }
}

Once this is added, and the application is deployed or configured, we’ll need to do two things:

Add a remote configuration in the IDE of our choice. This remote Run/Debug configuration for the remote JVM must have the same arguments, except for the address set in JAVA_OPTS. The address can be different because it belongs to the environment where the IDE is running, typically will be local. See the following for an example configuration:
```
-agentlib:jdwp=transport=dt_socket,server=y,suspend=n,address=*:4004
```
Port-forward a local address to the selected streamlet/pod in the Kubernetes cluster. Let’s say our application is called 'example-application' and we picked the above parameters for the IDE debug configuration. Then we will need to port-forward like the following:
```
kubectl port-forward pod/[some-streamlet-pod-name] 4004:5005 -n example-application
```