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Unleash on Cloud Run — Lab Guide

📖 Configuration Guide

Overview​

Estimated time: 45–90 minutes

Unleash is an open-source feature-flag and toggle-management platform for progressive delivery, A/B testing, and gradual rollouts, driven by a REST API and admin UI. This lab takes you through the full operational lifecycle of the Unleash on Cloud Run module on Google Cloud: deploy it, access and verify it, create and evaluate a feature flag, 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 Unleash 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 log in to the admin UI.
  • Create a feature flag and evaluate it via the Unleash API with a token.
  • 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. In the RAD platform, open Unleash (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 bootstrap admin API token and the database password), builds the container image, and runs a one-shot database-initialisation job that creates the unleash database and user. 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="$REGION" \
      --filter="metadata.name~unleash" --format="value(metadata.name)" --limit=1)
    SERVICE_URL=$(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. Unleash exposes a public health endpoint that returns 200 only when the server is fully initialised and PostgreSQL is reachable:

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

  2. Open $SERVICE_URL in a browser. Log in to the admin UI with the well-known first-run credentials admin / unleash4all and change the password immediately under Admin → Users.

Task 3 — Worked example: create and evaluate a feature flag [Manual]​

Unleash stores every flag in PostgreSQL and evaluates it through its API. This task creates a flag and evaluates it with an API token — the same flow an application SDK uses.

  1. Retrieve the bootstrap admin API token the module seeded into Secret Manager. It has all-access (*:*) admin rights:

    ADMIN_SECRET=$(gcloud secrets list --project="$PROJECT" \
      --filter="name~admin-token" --format="value(name)" --limit=1)
    ADMIN_TOKEN=$(gcloud secrets versions access latest --secret="$ADMIN_SECRET" --project="$PROJECT")
    echo "Admin token: $ADMIN_TOKEN"

  2. Create a feature flag in the default project via the Admin API (or do this in the UI under Projects → default → New feature flag):

    curl -s -X POST "$SERVICE_URL/api/admin/projects/default/features" \
      -H "Authorization: $ADMIN_TOKEN" -H "Content-Type: application/json" \
      -d '{"name":"welcome-banner","type":"release"}'

  3. Enable the flag in the development environment:

    curl -s -X POST \
      "$SERVICE_URL/api/admin/projects/default/features/welcome-banner/environments/development/on" \
      -H "Authorization: $ADMIN_TOKEN"

  4. Create a client API token scoped to the development environment — this is the credential an SDK would use (never ship the admin token to clients):

    curl -s -X POST "$SERVICE_URL/api/admin/api-tokens" \
      -H "Authorization: $ADMIN_TOKEN" -H "Content-Type: application/json" \
      -d '{"tokenName":"lab-client","type":"client","environment":"development","projects":["default"]}'
    # copy the "secret" field from the response into CLIENT_TOKEN:
    export CLIENT_TOKEN="<secret-from-response>"

  5. Evaluate the flag via the API using the client token — the Client API returns the flag definitions an SDK evaluates against its context:

    curl -s "$SERVICE_URL/api/client/features" -H "Authorization: $CLIENT_TOKEN" \
      | python3 -c "import sys,json; [print(f['name'], f['enabled']) for f in json.load(sys.stdin)['features']]"
    # expect: welcome-banner True

    You have now created a flag and evaluated it through the same API path your applications 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. 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). Unleash is stateless, so any instance can serve any request — scaling out needs no Redis or session affinity.

  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. Unleash applies any schema migrations on startup.

  4. Manage secrets and backups:

    gcloud secrets list --project="$PROJECT" --filter="name~unleash"
    gcloud run jobs list --project="$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 "$INSTANCE" --user=unleash --project="$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 (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 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 Unleash 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 generous headroom for first-boot migrations. 
    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. Check the injected DATABASE_URL/DB_* on the running revision: 
    gcloud run services describe "$SERVICE" --region="$REGION" \
      --format='value(spec.template.spec.containers[0].env)'
  • 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 / permission errors: verify the runtime service account's IAM roles.

See the Configuration Guide's Configuration Pitfalls section for setting-specific gotchas (including keeping probe paths on /health and never enabling IAP when SDK clients must reach the API directly).

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 (it makes RAD forget the project). 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 to the admin UI as admin / unleash4all
3 — Worked exampleManualCreate a feature flag and evaluate it via the Unleash API with a token
4 — OperateManualInspect revisions, scale, 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 IAM issues
7 — Tear downAutomatedDelete (Trash) removes all module resources

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

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