Debug Dapr control plane on Kubernetes

    Sometimes it is necessary to understand what’s going on in Dapr control plane (aka, Kubernetes services), including , dapr-operator, dapr-placement, and dapr-sentry, especially when you diagnose your Dapr application and wonder if there’s something wrong in Dapr itself. Additionally, you may be developing a new feature for Dapr on Kubernetes and want to debug your code.

    This guide will cover how to use Dapr debugging binaries to debug the Dapr services on your Kubernetes cluster.

    • Familiarize yourself with to learn how to deploy Dapr to your Kubernetes cluster.
    • Helm

    In order to debug Dapr Kubernetes services, it’s required to rebuild all Dapr binaries and Docker images to disable compiler optimization. To do this, execute the following commands:

    In the above command, ‘DEBUG’ is specified to ‘1’ to disable compiler optimization. ‘GOOS=linux’ and ‘GOARCH=amd64’ are also necessary since the binaries will be packaged into Linux-based Docker image in the next step.

    Use the following commands to package the debugging binaries into Docker images. Before this, you need to login your docker.io account, and if you don’t have it yet, you may need to consider registering one from “.

    1. export DAPR_TAG=dev
    2. export DAPR_REGISTRY=<your docker.io id>
    3. docker login

    Once the Dapr Docker images are built and pushed onto Docker hub, then you are ready to re-install Dapr in your Kubernetes cluster.

    If Dapr has already been installed in your Kubernetes cluster, uninstall it first:

    We will use ‘helm’ to install Dapr debugging binaries. In the following sections, we will use Dapr operator as an example to demonstrate how to configure, install, and debug Dapr services in a Kubernetes environment.

    First configure a values file with these options:

    1. global:
    2.    registry: docker.io/<your docker.io id>
    3.    tag: "dev-linux-amd64"
    4. dapr_operator:
    5.   debug:
    6.     initialDelaySeconds: 3000

    Notice

    Then step into ‘dapr’ directory which’s cloned from GitHub in the beginning of this guide if you haven’t, and execute the following command:

    To debug the target Dapr service (Dapr operator in this case), its pre-configured debug port needs to be visible to your IDE. In order to achieve this, we need to find the target Dapr service’s pod first:

    3. NAME                                     READY   STATUS    RESTARTS   AGE   IP            NODE       NOMINATED NODE   READINESS GATES
    4. dapr-dashboard-64b46f98b6-dl2n9          1/1     Running   0          61s   172.17.0.9    minikube   <none>           <none>
    5. dapr-operator-7878f94fcd-6bfx9           1/1     Running   1          61s   172.17.0.7    minikube   <none>           <none>
    6. dapr-placement-server-0                  1/1     Running   1          61s   172.17.0.8    minikube   <none>           <none>
    7. dapr-sentry-68c7d4c7df-sc47x             1/1     Running   0          61s   172.17.0.6    minikube   <none>           <none>
    8. dapr-sidecar-injector-56c8f489bb-t2st9   1/1     Running   0          61s   172.17.0.10   minikube   <none>           <none>

    Then use kubectl’s port-forward command to expose the internal debug port to the external IDE:

    All done. Now you can point to port 40000 and start a remote debug session from your favorite IDE.

    Last modified March 18, 2022: Fix quickstart links path (bc69f26c)