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Focalboard on Cloud Run — Lab Guide

📖 Configuration Guide

Overview​

Estimated time: 45–90 minutes

Focalboard is a self-hosted, open-source Kanban and project-board server from the Mattermost project — a Go backend serving a built React frontend for managing tasks, boards, and workflows. This lab takes you through the full operational lifecycle of the Focalboard 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 Focalboard 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.
  • Perform day-2 operations — inspect, scale, update, and manage secrets and the attachment bucket.
  • 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 Focalboard (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 provisions the Cloud Run service, a Cloud SQL (PostgreSQL 15) database with its Secret Manager secrets (FOCALBOARD_ADMIN_PASSWORD and the database password), a dedicated Cloud Storage bucket for board attachments, mirrors the mattermost/focalboard image into Artifact Registry, and runs a one-shot database-initialisation job that creates the application role and database. 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="$REGION" \
      --filter="metadata.name~focalboard" --format="value(metadata.name)" --limit=1)
    SERVICE_URL=$(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 connected to its database. Focalboard has no dedicated health API — the startup, liveness, and readiness probes all target the web UI root, which returns 200 only once the Go server has bound its port and completed its own schema migrations:

    curl -s -o /dev/null -w "%{http_code}\n" "$SERVICE_URL/"   # expect 200

  2. Open $SERVICE_URL in a browser. Focalboard runs in authMode = native with no pre-seeded admin credential in Secret Manager — register the first account through the UI (name, email, password) and it automatically becomes the workspace owner. Public shared boards are enabled by default, so boards can be shared via public links once created.

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

  1. Inspect the service and its revisions (each deploy creates an immutable revision; traffic shifts to the newest healthy one):

    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). Unlike apps that need Redis for multi-instance coordination, Focalboard keeps all board state in PostgreSQL and uses no cache or queue, so max_instance_count is safe to raise without any other prerequisite.

  3. Update the application version by changing the version input in the RAD platform and applying it via Update; a new image builds (the base image is mirrored from mattermost/focalboard) and a new revision rolls out. Focalboard applies its own schema migrations on every boot as the application database user, so upgrading the version applies schema changes automatically with no separate migration step.

  4. Manage secrets and jobs:

    gcloud secrets list --project="$PROJECT" --filter="name~focalboard"
    gcloud run jobs list --project="$PROJECT" --region="$REGION"   # db-init job

  5. Inspect the attachment bucket — uploaded files (not board data) live here:

    gcloud storage buckets list --project="$PROJECT" --filter="name~focalboard"
    gcloud storage ls gs://<attachment-bucket>/

  6. Open a database session for inspection or maintenance:

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

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

  1. Logs — from the CLI or the Logs Explorer. The entrypoint prints the resolved DB host, name, user, and sslmode at startup, which is useful for confirming the connection wiring:

    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's uptime check (uptime_check_config) is disabled by default — enable it and confirm it turns green under Monitoring → Uptime checks if you need synthetic availability monitoring.

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 Focalboard releases.

  • Revision unhealthy / service won't serve: inspect the latest revision and its logs for startup errors, and confirm env vars and secrets resolved. The startup probe targets / and allows up to ~7–8 minutes on first boot (60s initial delay, 15s period, 30 retries). 
    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 instance is RUNNABLE, the DB password secret exists, and the db-init job completed successfully. Focalboard's entrypoint regenerates /opt/focalboard/config.json from the Foundation-injected DB_* vars on every start (it has no env-var override), and on Cloud Run it prefers DB_IP over the Cloud SQL socket with sslmode=require.
  • db-init job failed: list executions and read the failed one's logs: 
    gcloud run jobs executions list --job="${SERVICE}-db-init" \
      --project="$PROJECT" --region="$REGION"
  • Attachment uploads fail but board editing still works: the gcsfuse mount at /data (enable_gcs_storage_volume) is missing or misconfigured — board content itself lives in PostgreSQL and is unaffected, only file uploads are.
  • Image build failed: review Cloud Build history for the failed mirroring/build step's log.
  • 403 / permission errors: verify the runtime service account's IAM roles.

See the Configuration Guide's Configuration Pitfalls section for setting-specific gotchas (including why application_database_name/application_database_user are effectively immutable after first deploy, and why database_type must stay POSTGRES_15).

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, Cloud SQL database, Secret Manager secrets, the attachment 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 provisions Cloud Run, Cloud SQL (PostgreSQL 15), secrets, attachment bucket, and runs DB init
2 — Access & verifyManualHealth check (/) passes; register the first account in the UI to become owner
3 — OperateManualInspect revisions, scale, update version, manage secrets/jobs, inspect attachments, DB access
4 — ObserveManualQuery Cloud Logging; review Cloud Monitoring metrics and (optional) uptime check
5 — TroubleshootManualDiagnose revision, database, init-job, upload, 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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