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Planka on Cloud Run — 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 Cloud Run 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 Cloud Run 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 service, and log in with the generated admin credential.
  • Perform day-2 operations — inspect, scale, update, and manage backups.
  • Observe the service 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, 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

Task 1 — Deploy the module [Automated]​

  1. In the RAD platform, open Planka (Cloud Run), 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 Cloud Run service, a Cloud SQL (PostgreSQL 15) 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 (the Cloud Build image build and Cloud SQL creation dominate).

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

    SERVICE=$(gcloud run services list --project="$PROJECT" --region="$REGION" \
      --filter="metadata.name~planka" --format="value(metadata.name)" --limit=1)
    SERVICE_URL=$(gcloud run services describe "$SERVICE" \
      --project="$PROJECT" --region="$REGION" --format="value(status.url)")
    echo "Service: $SERVICE"
    echo "URL:     $SERVICE_URL"

Task 2 — Access & verify [Manual]​

  1. Confirm the service is healthy and serving:

    curl -s "$SERVICE_URL/" -o /dev/null -w '%{http_code} %{size_download}\n'   # expect 200 and >0 bytes

  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 $SERVICE_URL 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, since the credential is a real secret worth rotating out of the initial deployment value. 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 service and its revisions:

    gcloud run services describe "$SERVICE" --project="$PROJECT" --region="$REGION"
    gcloud run revisions list --service="$SERVICE" --project="$PROJECT" --region="$REGION"

  2. Scale by changing the min/max instance inputs and clicking Update on the deployment details page — Planka has no cross-instance coordination concern (no cache, no queue; real-time updates ride Socket.io per-instance), so raising max_instance_count is safe.

  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="$PROJECT" --filter="name~planka"
    gcloud run jobs list --project="$PROJECT" --region="$REGION"

  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:

    gcloud run services logs read "$SERVICE" --project="$PROJECT" --region="$REGION" --limit=50

    Look for the [cloud-entrypoint] line — it reports which DATABASE_URL connection mode the entrypoint resolved (socket-unsupported/private-IP, loopback, or direct private-IP) and the derived BASE_URL.

  2. Monitoring — open the Cloud Run dashboard for the service and review request count, latency, instance count, and CPU/memory utilisation. The module can provision an uptime check (disabled by default); if enabled, confirm it is green under Monitoring → Uptime checks.

Task 5 — Troubleshoot & debug [Manual]​

  • Revision unhealthy / service won't serve: inspect the latest revision and its logs. 
    gcloud run revisions list --service="$SERVICE" --project="$PROJECT" --region="$REGION"
    gcloud run services logs read "$SERVICE" --project="$PROJECT" --region="$REGION" --limit=100
    If the revision 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.
  • Database connection errors: confirm the Cloud SQL instance is RUNNABLE, the DB password secret exists, and the initialisation job completed. Check the container logs for the [cloud-entrypoint] line reporting which DATABASE_URL mode was resolved.
  • Initialisation job failed: 
    gcloud run jobs executions list --job="${SERVICE}-db-init" --project="$PROJECT" --region="$REGION"
  • 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 (or reconnect to the database directly) instead.
  • 403 / permission errors: verify the runtime service account's IAM roles.

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 Cloud Run service, Cloud SQL database, Secret Manager secrets, the GCS bucket, and Artifact Registry images. Resources owned by Services_GCP (the VPC, shared Cloud SQL, registry) are managed separately and are not removed here.

Summary​

TaskTypeOutcome
1 — DeployAutomatedModule builds the custom image and provisions Cloud Run, Cloud SQL (PostgreSQL 15), secrets, a GCS bucket, and runs DB init
2 — Access & verifyManualHealth check passes; log in with the generated admin credential and create a board
3 — OperateManualInspect revisions, scale, update version, manage secrets/backups, DB access
4 — ObserveManualQuery Cloud Logging; review Cloud Monitoring metrics and uptime check
5 — TroubleshootManualDiagnose revision, 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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