The documentation you are viewing is for Dapr v1.10 which is an older version of Dapr. For up-to-date documentation, see the latest version.
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-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.
Debugging Dapr Kubernetes services
- Familiarize yourself with this guide to learn how to deploy Dapr to your Kubernetes cluster.
- Setup your dev environment
1. Build Dapr debugging binaries
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:
git clone https://github.com/dapr/dapr.git cd dapr make release GOOS=linux GOARCH=amd64 DEBUG=1
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.
The binaries could be found under ‘dist/linux_amd64/debug’ sub-directory under the ‘dapr’ directory.
2. Build Dapr debugging Docker images
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 “https://hub.docker.com/".
export DAPR_TAG=dev export DAPR_REGISTRY=<your docker.io id> docker login make docker-push DEBUG=1
Once the Dapr Docker images are built and pushed onto Docker hub, then you are ready to re-install Dapr in your Kubernetes cluster.
3. Install Dapr debugging binaries
If Dapr has already been installed in your Kubernetes cluster, uninstall it first:
dapr uninstall -k
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:
global: registry: docker.io/<your docker.io id> tag: "dev-linux-amd64" dapr_operator: debug: enabled: true initialDelaySeconds: 3000
NoticeIf you need to debug the startup time of Dapr services, you need to consider configuring
initialDelaySecondsto a very long time value, e.g. “3000” seconds. If this is not the case, configure it to a short time value, e.g. “3” seconds.
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:
helm install dapr charts/dapr --namespace dapr-system --values values.yml --wait
4. Forward debugging port
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:
$ kubectl get pods -n dapr-system -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES dapr-dashboard-64b46f98b6-dl2n9 1/1 Running 0 61s 172.17.0.9 minikube <none> <none> dapr-operator-7878f94fcd-6bfx9 1/1 Running 1 61s 172.17.0.7 minikube <none> <none> dapr-placement-server-0 1/1 Running 1 61s 172.17.0.8 minikube <none> <none> dapr-sentry-68c7d4c7df-sc47x 1/1 Running 0 61s 172.17.0.6 minikube <none> <none> 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:
$ kubectl port-forward dapr-operator-7878f94fcd-6bfx9 40000:40000 -n dapr-system Forwarding from 127.0.0.1:40000 -> 40000 Forwarding from [::1]:40000 -> 40000
All done. Now you can point to port 40000 and start a remote debug session from your favorite IDE.
Was this page helpful?
Glad to hear it! Please tell us how we can improve.
Sorry to hear that. Please tell us how we can improve.