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Gatus on Cloud Run — Lab Guide

📖 Configuration Guide

Overview​

Estimated time: 45–90 minutes

Gatus is an open-source, developer-oriented status page and health-check monitor: it polls configured HTTP, TCP, DNS, and other endpoints on independent schedules, evaluates simple pass/fail conditions, and serves a live public status page plus alerting — no external database required. This lab takes you through the full operational lifecycle of the Gatus 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 Gatus 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 viewing the live status page.
  • Perform day-2 operations — inspect, scale considerations, update, and manage secrets.
  • 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, 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 Gatus (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 a single Cloud Run v2 service running the Gatus Go binary and builds the container image (which bakes in a default config.yaml with one example HTTP check). No database, cache, or object-storage bucket is provisioned — Gatus's optional history store is a local SQLite file. There is no database-initialisation job to wait for, so a first deploy is typically much faster than a database-backed module (roughly 5–10 minutes, dominated by the image build).

  3. When it completes, discover the service with a name-agnostic filter (so the command keeps working regardless of the deployment suffix):

    SERVICE=$(gcloud run services list --project="$PROJECT" --region="$REGION" \
      --filter="metadata.name~gatus" --format="value(metadata.name)" --limit=1)
    SERVICE_URL=$(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. Gatus's health endpoint responds as soon as the server binds its port — there is no database dependency to wait on:

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

  2. Open $SERVICE_URL in a browser to view the live status page — it shows the baked-in example endpoint check and its up/down history as checks accumulate.

  3. Gatus ships with no authentication on its status page by default — anyone with the URL can view it. There is no admin account to create. If the page will list sensitive endpoint names, edit modules/Gatus_Common/scripts/config.yaml's security block (basic auth or OIDC) and redeploy — this requires a rebuild, not a runtime setting.

  4. Gatus has no runtime API or UI for adding monitored endpoints. To monitor a real endpoint instead of (or alongside) the baked-in example, edit the endpoints list in modules/Gatus_Common/scripts/config.yaml and redeploy.

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. Do not scale beyond one instance. max_instance_count defaults to 1 and should stay there — Gatus's watchdog polling loop has no shared coordination between instances, so scaling out would have each instance independently poll every endpoint and duplicate alert notifications. Any change to min/max instances is made via the RAD platform's deployment details page and applied via Update, not a manual gcloud edit (which would be reverted on the next apply).

  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. Pin an explicit v5.x.y in production rather than relying on latest.

  4. Manage secrets:

    gcloud secrets list --project="$PROJECT" --filter="name~gatus"

    Gatus generates no secrets of its own at deploy time — this list is only populated if you supplied entries via secret_environment_variables.

  5. Persistent history is intentionally NOT the default on Cloud Run. Gatus hardcodes SQLite WAL journal mode for its history store, and SQLite's own documentation states WAL is unsupported on network filesystems — so enable_nfs carries a real corruption risk here. If durable check history matters, deploy Gatus_GKE with stateful_pvc_enabled = true instead (a real block device); Cloud Run has no equivalent option.

Task 4 — 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>". Gatus logs each endpoint check's result (success/failure, duration) as it runs — useful for confirming a newly-added endpoint is actually being polled.

  2. Monitoring — open the Cloud Run dashboard for the service and review request count, request latency, instance count, and CPU / memory utilisation. Because cpu_always_allocated = true by default, expect a steady CPU baseline even at low traffic — this is required to keep the watchdog polling loop running, not a misconfiguration. If a Cloud Monitoring uptime check is enabled, 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 Gatus releases.

  • Revision unhealthy / service won't serve: inspect the latest revision and its logs for startup errors. The startup and liveness probes both target /health, which should return 200 within seconds of boot — Gatus has no database to wait on, so a slow or failing probe usually points at a container build or config issue rather than a downstream dependency. 
    gcloud run revisions list --service="$SERVICE" --project="$PROJECT" --region="$REGION"
    gcloud run services logs read "$SERVICE" --project="$PROJECT" --region="$REGION" --limit=100
  • Check history "disappears" after a redeploy: this is expected with the default ephemeral storage — every restart/redeploy resets history by design (the configured endpoints themselves are unaffected, only their historical results/uptime percentages reset). See Task 3 step 5 for the durable-history options and their tradeoffs.
  • A newly-added endpoint isn't being checked: confirm you edited modules/Gatus_Common/scripts/config.yaml and redeployed — Gatus has no runtime API for adding checks, so an endpoint added anywhere else has no effect.
  • Status page is unreachable / blocked unexpectedly: check ingress_settings (must be all for public traffic) and whether enable_iap was turned on — IAP requires Google sign-in and blocks unauthenticated viewing, which is usually not what a public status page wants.
  • Image build failed: review Cloud Build history for the failed build's log.
  • 403 / permission errors: verify the runtime service account's IAM roles.

See the Configuration Guide's Configuration Pitfalls & Sensible Defaults section for setting-specific gotchas (including keeping max_instance_count = 1 and cpu_always_allocated = true for correct scheduled-check delivery, and the SQLite WAL persistence caveat).

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 and Artifact Registry images. There is no Cloud SQL database, GCS bucket, or auto-generated secret to clean up (Gatus provisions none by default). Resources owned by Services_GCP (the VPC, shared registry) are managed separately and are not removed here.

Summary​

TaskTypeOutcome
1 — DeployAutomatedModule provisions a single Cloud Run service running Gatus; no database or storage bucket
2 — Access & verifyManualHealth check passes; live status page renders with the baked-in example check
3 — OperateManualInspect revisions, keep max instances at 1, update version, manage secrets, understand the persistence tradeoff
4 — ObserveManualQuery Cloud Logging; review Cloud Monitoring metrics and uptime check
5 — TroubleshootManualDiagnose revision, config-edit, access, and build issues
6 — Tear downAutomatedDelete (Trash) removes all module resources

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

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