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Gotify on Cloud Run — Lab Guide

📖 Configuration Guide

Overview​

Estimated time: 45–90 minutes

Gotify is an open-source, self-hosted server for real-time push notifications: applications send messages over a simple REST API and clients receive them instantly over WebSocket. This lab takes you through the full operational lifecycle of the Gotify on Cloud Run module on Google Cloud: deploy it, access and verify it, send and receive a live notification, 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 Gotify 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 retrieve the generated admin password.
  • Send a message via the REST API and receive it over the WebSocket stream.
  • Perform day-2 operations — inspect, 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.
  • A WebSocket client for the worked example — websocat (recommended) or curl 8.x.

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 Gotify (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 (the admin password and the database password), builds the custom container image (wrapping ghcr.io/gotify/server), and runs a one-shot database-initialisation 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="$REGION" \
      --filter="metadata.name~gotify" --format="value(metadata.name)" --limit=1)
    SERVICE_URL=$(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. Gotify exposes a public health endpoint that reports both the server and the database:

    curl -s "$SERVICE_URL/health"    # expect {"health":"green","database":"green"}

  2. Retrieve the generated admin password from Secret Manager:

    ADMIN_SECRET=$(gcloud secrets list --project="$PROJECT" \
      --filter="name~gotify-admin-password" --format="value(name)" --limit=1)
    gcloud secrets versions access latest --secret="$ADMIN_SECRET" --project="$PROJECT"

  3. Open $SERVICE_URL in a browser and log in as admin with that password. Change the password immediately under Users — the bootstrap password is applied only on the first database initialisation and is not reset by later deploys.

Task 3 — Send and receive a notification [Manual]​

This is the core Gotify workflow: an application token sends messages; a client token subscribes to them.

  1. Create an application (in the UI: Apps → Create Application), or via the REST API using HTTP basic auth as the admin user. Capture the returned app token:

    ADMIN_PASS='<paste-the-admin-password>'
    APP_TOKEN=$(curl -s -u "admin:$ADMIN_PASS" \
      -H "Content-Type: application/json" \
      -d '{"name":"lab-app","description":"lab notifications"}' \
      "$SERVICE_URL/application" | python3 -c 'import sys,json;print(json.load(sys.stdin)["token"])')
    echo "App token: $APP_TOKEN"

  2. Create a client to receive messages, and capture its token:

    CLIENT_TOKEN=$(curl -s -u "admin:$ADMIN_PASS" \
      -H "Content-Type: application/json" \
      -d '{"name":"lab-client"}' \
      "$SERVICE_URL/client" | python3 -c 'import sys,json;print(json.load(sys.stdin)["token"])')
    echo "Client token: $CLIENT_TOKEN"

  3. Subscribe to the stream in one terminal (leave it running). Gotify streams new messages over WebSocket at /stream:

    WS_URL="${SERVICE_URL/https:/wss:}/stream?token=$CLIENT_TOKEN"
    websocat "$WS_URL"          # or: curl --include -N "$SERVICE_URL/stream?token=$CLIENT_TOKEN"

  4. Send a message from another terminal using the app token. It should appear in the stream terminal within a second:

    curl -s "$SERVICE_URL/message?token=$APP_TOKEN" \
      -F "title=Deploy complete" -F "message=Gotify is live on Cloud Run" -F "priority=5"

    The stream terminal prints the JSON message. That end-to-end path — REST in, WebSocket out — is exactly what your applications and clients will use.

Task 4 — 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. Do not scale beyond one instance. Gotify's message bus is in-process, so a client only receives messages delivered to the instance it is connected to. The module fixes min = max = 1; changing that without an external fan-out layer drops messages for some subscribers.

  3. Update the application version by changing the version input in the RAD platform and applying it via Update; a new image builds and a new revision rolls out. Gotify runs its GORM auto-migration on startup, so schema changes apply automatically.

  4. Manage secrets and backups:

    gcloud secrets list --project="$PROJECT" --filter="name~gotify"
    gcloud run jobs list --project="$PROJECT" --region="$REGION"   # init + scheduled backup jobs

  5. Open a database session for inspection or maintenance:

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

Task 5 — Observe: Logging & Monitoring [Manual]​

  1. Logs — from the CLI or the Logs Explorer:

    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, 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 6 — 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 Gotify 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 /health and allows ~5 minutes on first boot. 
    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 initialisation job completed successfully. Gotify logs the DB host/port/name on startup.
  • 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 for the failed build's log.
  • 403 invalid API token on send/receive: re-check the token — app tokens send (/message), client tokens subscribe (/stream); they are not interchangeable.
  • 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 max_instance_count must stay at 1).

Task 7 — 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. This removes everything the module created — the Cloud Run service, Cloud SQL database, Secret Manager secrets, 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, and runs DB init
2 — Access & verifyManualHealth check passes; log in as admin with the generated password
3 — Send & receiveManualCreate app + client tokens, POST a message, receive it over WebSocket
4 — OperateManualInspect revisions, update version, manage secrets/backups, DB access
5 — ObserveManualQuery Cloud Logging; review Cloud Monitoring metrics and uptime check
6 — TroubleshootManualDiagnose revision, database, init-job, build, and token issues
7 — Tear downAutomatedDelete (Trash) removes all module resources

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

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