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AFFiNE on Cloud Run — Lab Guide

📖 Configuration Guide

Overview​

Estimated time: 45–90 minutes

AFFiNE is an open-source knowledge base that unifies docs, whiteboards, and databases in one workspace — a self-hostable alternative to Notion and Miro. This lab takes you through the full operational lifecycle of the AFFiNE 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 AFFiNE 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 complete AFFiNE's first-run setup.
  • Perform day-2 operations — inspect revisions, resize, 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, NFS/Redis host, 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 AFFiNE (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, a Cloud SQL (PostgreSQL 15) database with its Secret Manager password secret, an NFS share for blob storage (whose host also serves as the default Redis endpoint), a dedicated storage GCS bucket, builds the custom container image (thin wrapper over ghcr.io/toeverything/affine), and runs two one-shot jobs: db-init (database + user) and affine-migrate (AFFiNE's self-host-predeploy schema migration and signing-key generation). 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="$REGION" \
      --filter="metadata.name~affine" --format="value(metadata.name)" --limit=1)
    SERVICE_URL=$(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. AFFiNE's health path is /, which returns HTTP 200 once the server is ready (the startup probe allows a generous window, but a healthy instance typically answers within a minute or two of a fresh deploy):

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

  2. Open $SERVICE_URL in a browser and create the first account — on a fresh AFFiNE self-host instance the first registered user becomes the server administrator (the admin panel is at ${SERVICE_URL}/admin). Do this immediately after deploying: until an admin account exists, anyone who reaches the URL can register it. The database password (the only credential in Secret Manager) can be retrieved if needed:

    DB_SECRET=$(gcloud secrets list --project="$PROJECT" \
      --filter="name~affine" --format="value(name)" --limit=1)
    gcloud secrets versions access latest --secret="$DB_SECRET" --project="$PROJECT"

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. Scaling is vertical, not horizontal. AFFiNE is pinned to a single always-on instance (min = max = 1, cpu_always_allocated = true) because collaboration blobs live on the NFS filesystem and real-time editing state is per-process. To give it more headroom, raise cpu_limit / memory_limit and click Update on the deployment details page — the module owns the service spec, so this is a configuration change, not a manual gcloud edit (a manual edit would be reverted on the next apply). Do not raise max_instance_count.

  3. Update the application version by changing the application_version input (e.g. stable → a pinned release tag) via Update on the deployment details page; a new image builds and a new revision rolls out. The affine-migrate job re-runs idempotently.

  4. Manage secrets, storage, and jobs:

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

  5. Open a database session for inspection or maintenance (PostgreSQL 15):

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

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

  1. Logs — from the CLI or the Logs Explorer. The [cloud-entrypoint] lines show which database host and Redis endpoint the container resolved at startup:

    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 (expect a flat 1 — the instance is always-on), and CPU / memory utilisation. If you enabled uptime_check_config, confirm the check 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 AFFiNE releases.

  • Revision unhealthy / service won't serve: inspect the latest revision and its logs. The [cloud-entrypoint] startup lines confirm whether the DB host and Redis endpoint resolved: 
    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, and the db-init job completed. Note AFFiNE connects over the instance private IP with sslmode=require (not the Auth Proxy socket) — VPC egress must be intact.
  • Initialisation job failed: list executions and read the failed one's logs. affine-migrate retries up to 3 times and must succeed before the server has a schema: 
    gcloud run jobs executions list --job="${SERVICE}-affine-migrate" \
      --project="$PROJECT" --region="$REGION"
    gcloud run jobs executions list --job="${SERVICE}-db-init" \
      --project="$PROJECT" --region="$REGION"
  • Real-time collaboration not syncing: Redis is mandatory. Verify the NFS/Redis host VM is RUNNING (the NFS server IP is the default Redis endpoint) and that logs show a non-empty REDIS_SERVER_HOST.
  • Image build failed: review Cloud Build history for the failed build's log. container_image_source must be custom — the upstream image lacks the entrypoint that assembles DATABASE_URL / REDIS_SERVER_*. A nonexistent image tag (e.g. a literal latest) fails the base-image pull; the module maps latest → stable.
  • 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, Cloud SQL database, Secret Manager secrets, GCS buckets (including the storage bucket), the NFS share, 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, Cloud SQL (PostgreSQL 15), NFS/Redis, GCS bucket, secrets, and runs db-init + affine-migrate
2 — Access & verifyManualHealth check passes; first registered account becomes the server admin
3 — OperateManualInspect revisions, resize vertically, update version, manage secrets/backups/storage, DB access
4 — ObserveManualQuery Cloud Logging; review Cloud Monitoring metrics and uptime check
5 — TroubleshootManualDiagnose revision, database, init-job, Redis, 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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