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Plane on Cloud Run — Lab Guide

📖 Configuration Guide

Overview​

Estimated time: 45–90 minutes

Plane is an open-source project-management platform — a Jira / Linear alternative for issues, cycles, modules, and roadmaps. This lab takes you through the full operational lifecycle of the Plane 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 Plane 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, including the RabbitMQ sidecar and first-boot migrations.
  • Perform day-2 operations — inspect, scale, update, and manage secrets and 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. Click Deploy in the RAD platform top navigation, open Plane (Cloud Run) from the Platform Modules list to start configuration, 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 provisions the Cloud Run service running Plane's all-in-one container (api + Celery worker/beat + web/space/admin frontends + live + migrator behind an internal Caddy proxy on port 80) with a RabbitMQ sidecar container, a Cloud SQL (PostgreSQL 15) database with its Secret Manager secrets (including the auto-generated SECRET_KEY and LIVE_SERVER_SECRET_KEY), Redis on the shared NFS host, a dedicated storage GCS bucket, builds the custom container image via Cloud Build, and runs a one-shot db-init job. First deploys take roughly 20–35 minutes (Cloud SQL creation dominates).

  3. When it completes, discover the resources with name-agnostic filters (so the commands keep working regardless of the deployment suffix):

    SERVICE=$(gcloud run services list --project="$PROJECT" --region="$REGION" \
      --filter="metadata.name~plane" --format="value(metadata.name)" --limit=1)
    SERVICE_URL=$(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. Plane's health path is /health, served by the internal Caddy proxy once the first-boot migrator has finished (allow several minutes on a fresh deploy — the startup probe permits up to ~5 minutes):

    curl -s -o /dev/null -w "%{http_code}\n" "$SERVICE_URL/health"

  2. Verify the entrypoint composed the three connection URLs Plane requires:

    gcloud run services logs read "$SERVICE" --project="$PROJECT" --region="$REGION" --limit=100 \
      | grep -E "Composed (DATABASE|REDIS|AMQP)_URL"

  3. Open ${SERVICE_URL}/god-mode/ in a browser — Plane's instance-admin panel — and create the instance admin account. Then open ${SERVICE_URL}/ to sign up and create your first workspace, project, and issue.

  4. Immediate hardening notes: file uploads (attachments, avatars) require an S3-compatible endpoint — supply GCS HMAC keys or external S3 credentials via the environment_variables input before relying on uploads (see the Configuration Guide). The application secrets can be retrieved if needed:

    gcloud secrets list --project="$PROJECT" --filter="name~plane"
    gcloud secrets versions access latest --secret=<secret-name> --project="$PROJECT"

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

  1. Inspect the service and its revisions (each deploy creates an immutable revision; note the two containers — the Plane all-in-one and the mq RabbitMQ sidecar):

    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 — the module owns the service spec, so scaling is a configuration change, not a manual gcloud edit (a manual edit would be reverted on the next apply). The default is scale-to-zero (min = 0, cpu_always_allocated = false); if your team relies on timely Celery notifications/webhooks/exports, set cpu_always_allocated = true and min_instance_count = 1.

  3. Update the application version by changing the version input via Update on the deployment details page; a new image builds (the wrapper Dockerfile pins makeplane/plane-aio-community:<version> — note there is no latest tag upstream, so use stable or a real release tag) and a new revision rolls out. The migrator applies schema changes automatically on startup.

  4. Manage secrets, storage, and jobs:

    gcloud secrets list --project="$PROJECT" --filter="name~plane"
    gcloud run jobs list --project="$PROJECT" --region="$REGION"   # db-init + backup jobs
    gcloud storage buckets list --project="$PROJECT" --filter="name~plane"

  5. Open a database session for inspection or maintenance:

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

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

  1. Logs — supervisord multiplexes every bundled sub-service (migrator, api, worker, beat, frontends, Caddy) plus the mq sidecar into the revision logs:

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

    Logs Explorer filter: resource.type="cloud_run_revision" AND resource.labels.service_name="<service>".

  2. Monitoring — open the Cloud Run dashboard for the service and review request count, request latency (P50/P95/P99), instance count (scaling behaviour), and CPU / memory utilisation. The module also provisions an uptime check against /health; confirm it is green under Monitoring → Uptime checks, and review Alerting → Policies.

Task 5 — Troubleshoot & debug [Manual]​

Durable techniques for the failure modes you are most likely to hit. These are platform-level diagnostics and do not change with Plane releases.

  • Revision unhealthy / service won't serve: the first boot runs Django migrations (the AIO migrator step) before Caddy answers on /health; the startup probe allows up to ~5 minutes. Inspect the latest revision and its logs before concluding the service has failed: 
    gcloud run revisions list --service="$SERVICE" --project="$PROJECT" --region="$REGION"
    gcloud run services logs read "$SERVICE" --project="$PROJECT" --region="$REGION" --limit=100
  • Database connection errors: confirm the Cloud SQL (PostgreSQL 15) instance is RUNNABLE, the DB password secret exists, the db-init job completed, and the entrypoint logged Composed DATABASE_URL ... sslmode=require.
  • Celery / broker errors (worker cannot connect): Plane requires RabbitMQ; on Cloud Run it is the in-pod mq sidecar at 127.0.0.1:5672. Check the logs for Composed AMQP_URL host=127.0.0.1:5672 and for the sidecar's own startup output. Note the broker is ephemeral — queued tasks are lost on instance recycle.
  • File uploads fail (app otherwise healthy): expected until S3-compatible storage is wired — Plane needs AWS_ACCESS_KEY_ID/AWS_SECRET_ACCESS_KEY (GCS HMAC keys or external S3) via environment_variables. This is Plane-specific and documented in the Configuration Guide's Pitfalls section.
  • Initialisation job failed: list executions and read the failed one's logs: 
    gcloud run jobs executions list --job="${SERVICE}-db-init" \
      --project="$PROJECT" --region="$REGION"
  • Image build failed: review Cloud Build history. A common cause is an invalid application_version — the upstream makeplane/plane-aio-community image has no latest tag (the module maps latest→stable, but a typo'd explicit tag 404s with MANIFEST_UNKNOWN).
  • 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 (the deployment record is retained for history). If a deployment is stuck and the RAD platform can no longer manage it (for example after manual changes that conflict with the Terraform state), use Purge instead — it removes the deployment from RAD's records without destroying the cloud resources (it makes RAD forget the project). This removes everything the module created — the Cloud Run service (including the RabbitMQ sidecar), Cloud SQL database, Secret Manager secrets, GCS buckets (including the storage bucket), and Artifact Registry images. Resources owned by Services_GCP (the VPC, shared Cloud SQL, registry, NFS/Redis host) are managed separately and are not removed here.

Summary​

TaskTypeOutcome
1 — DeployAutomatedModule provisions Cloud Run (AIO container + RabbitMQ sidecar), Cloud SQL (PostgreSQL 15), Redis, GCS bucket, secrets, and runs DB init
2 — Access & verifyManual/health passes; connection URLs composed; instance admin created via /god-mode/
3 — OperateManualInspect revisions, scale, update version, manage secrets/backups/storage, DB access
4 — ObserveManualQuery Cloud Logging; review Cloud Monitoring metrics and uptime check
5 — TroubleshootManualDiagnose revision, database, broker, upload, init-job, build, 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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