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Planka on GKE Autopilot — Lab Guide

📖 Configuration Guide

Overview​

Estimated time: 30–60 minutes

Planka is an open-source, self-hosted, Trello-like kanban board application for team and personal project management. This lab takes you through the full operational lifecycle of the Planka on GKE Autopilot module on Google Cloud: deploy it, access and verify it, run it day-to-day, observe it, diagnose common problems, and tear it down.

The lab focuses on operating the GKE module and the Google Cloud platform, not on Planka product features. For the complete list of provisioned services and every configuration input (organised by group), see the Configuration Guide — this lab deliberately does not duplicate that detail so it stays accurate over time.

Objectives​

By the end of this lab you will be able to:

  • Deploy the module from the RAD platform and locate the resources it provisions.
  • Access and verify the running workload, and log in with the generated admin credential.
  • Perform day-2 operations — inspect, scale, update, and manage backups.
  • Observe the workload with Cloud Logging and Cloud Monitoring.
  • Diagnose and resolve the most common deployment and runtime issues.
  • Tear the deployment down cleanly.

Prerequisites​

  • Services_GCP deployed in the target project (provides the VPC, GKE Autopilot cluster, Cloud SQL, Artifact Registry, and shared service accounts this module depends on).
  • A Google Cloud project with billing enabled.
  • gcloud CLI authenticated: gcloud auth login and gcloud auth application-default login.
  • Project Owner (or equivalent) IAM on the project.
  • RAD platform access with permission to deploy modules into the project.

Set these shell variables once; every task below reuses them:

export PROJECT="<your-gcp-project-id>"
export REGION="us-central1"          # the region you deploy into
export NAMESPACE="<deployment-namespace>"   # reported in the deployment Outputs
gcloud container clusters get-credentials <cluster-name> --region "$REGION" --project "$PROJECT"

Task 1 — Deploy the module [Automated]​

  1. In the RAD platform, open Planka (GKE), set project_id, and review the inputs. Configure only what you need — the Configuration Guide documents every input by group, with defaults. Review the estimated cost (if credits are enabled) and click Deploy, which opens the deployment status page with real-time logs.

  2. The platform builds the custom Planka image (thin wrapper FROM ghcr.io/plankanban/planka), provisions the Kubernetes workload, a Cloud SQL (PostgreSQL) database with its Secret Manager password secret, the SECRET_KEY and DEFAULT_ADMIN_PASSWORD secrets, a storage GCS bucket, and runs a one-shot database-initialisation Job. First deploys take roughly 15–25 minutes.

  3. When it completes, discover the resources with name-agnostic filters:

    SERVICE=$(kubectl get svc -n "$NAMESPACE" -o name | grep planka | head -1 | cut -d/ -f2)
    EXTERNAL_IP=$(kubectl get svc "$SERVICE" -n "$NAMESPACE" -o jsonpath='{.status.loadBalancer.ingress[0].ip}')
    echo "Service: $SERVICE"
    echo "IP:      $EXTERNAL_IP"

Task 2 — Access & verify [Manual]​

  1. Confirm the pod is healthy and serving:

    kubectl get pods -n "$NAMESPACE" -l app="$SERVICE"    # expect N/N Running, 0 restarts
    curl -s "http://$EXTERNAL_IP/" -o /dev/null -w '%{http_code} %{size_download}\n'

  2. Retrieve the generated admin password — unlike a fixed, publicly-known default credential, Planka's DEFAULT_ADMIN_PASSWORD is a real, per-deployment generated secret:

    PASSWORD_SECRET=$(gcloud secrets list --project="$PROJECT" \
      --filter="name~planka AND name~default-admin-password" \
      --format="value(name)" | head -1)
    gcloud secrets versions access latest --secret="$PASSWORD_SECRET" --project="$PROJECT"

  3. Open http://$EXTERNAL_IP/ in a browser and log in with admin@example.com and the password retrieved above. Planka does not force a password reset on first login — change the password immediately via Planka's own account settings. Then create a board, list, and card to confirm the database write path.

Task 3 — Operate & keep it running (Day-2) [Manual]​

  1. Inspect the workload and its rollout history:

    kubectl get deploy "$SERVICE" -n "$NAMESPACE"
    kubectl rollout status deploy/"$SERVICE" -n "$NAMESPACE"

  2. Scale by changing the min/max instance inputs via the RAD platform's Update flow.

  3. Update the application version tag via the RAD platform's Update flow — this re-triggers the custom image build with the new PLANKA_VERSION build ARG.

  4. Manage secrets and backups:

    gcloud secrets list --project="$PROJECT" --filter="name~planka"
    kubectl get jobs -n "$NAMESPACE"

  5. Open a database session for inspection or maintenance:

    INSTANCE=$(gcloud sql instances list --project="$PROJECT" --format="value(name)" --limit=1)
    gcloud sql connect "$INSTANCE" --user=planka --project="$PROJECT"

Task 4 — Observe: Logging & Monitoring [Manual]​

  1. Logs:

    kubectl logs -n "$NAMESPACE" deploy/"$SERVICE" --tail=100

    Look for the [cloud-entrypoint] line — it reports which DATABASE_URL connection mode the entrypoint resolved and the derived BASE_URL.

  2. Monitoring — open the GKE Workloads dashboard for the deployment and review CPU/memory utilisation and replica count.

Task 5 — Troubleshoot & debug [Manual]​

  • Pod unhealthy / CrashLoopBackOff: inspect pod events and logs. If the pod never becomes Ready, check the startup probe's configured path — Planka's own healthcheck target is the root path /, but this module's startup_probe/liveness_probe variables currently default to /api/status. If probes are failing, override the path to / and redeploy. 
    kubectl describe pod -n "$NAMESPACE" -l app="$SERVICE"
    kubectl logs -n "$NAMESPACE" deploy/"$SERVICE" --tail=200
  • Database connection errors: confirm the Cloud SQL instance is RUNNABLE and check the container logs for the [cloud-entrypoint] line — on GKE it should report the loopback (127.0.0.1) connection mode via the cloud-sql-proxy sidecar.
  • Initialisation Job failed: 
    kubectl get jobs -n "$NAMESPACE"
    kubectl logs -n "$NAMESPACE" job/<job-name>
  • Can't log in with the admin credential: DEFAULT_ADMIN_PASSWORD only seeds the account on the first (empty-database) boot — if the database was already initialised, or the password was already changed, the original seeded value no longer works; use Planka's own password-recovery flow instead.
  • Attachment links / emails point at an unreachable address: confirm reserve_static_ip = true (the module default) — without it, BASE_URL can fall back to unreachable internal *.svc.cluster.local DNS.
  • 403 / permission errors: verify the Workload Identity binding.

See the Configuration Guide's Configuration Pitfalls section for setting-specific gotchas.

Task 6 — Tear down [Automated]​

On the Deployments page, open the deployment and click the Trash icon (Delete). Delete runs terraform destroy and is irreversible. If a deployment is stuck and the RAD platform can no longer manage it, use Purge instead — it removes the deployment from RAD's records without destroying the cloud resources. This removes everything the module created — the Kubernetes workload, Service, Cloud SQL database, Secret Manager secrets, and the GCS bucket. Resources owned by Services_GCP (the VPC, GKE cluster, shared Cloud SQL, registry) are managed separately and are not removed here.

Summary​

TaskTypeOutcome
1 — DeployAutomatedModule builds the custom image and provisions the GKE workload, Cloud SQL (PostgreSQL), secrets, a GCS bucket, and runs DB init
2 — Access & verifyManualPod Ready 0 restarts; log in with the generated admin credential and create a board
3 — OperateManualInspect rollout, scale, update version, manage secrets/backups, DB access
4 — ObserveManualQuery Cloud Logging; review Cloud Monitoring metrics
5 — TroubleshootManualDiagnose pod, database, init-job, and IAM issues
6 — Tear downAutomatedDelete (Trash) removes all module resources

By · Google Cloud certified: ACE · PCA · PCD · PDE · PSE · CDL

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