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Spoolman on Cloud Run — Lab Guide

📖 Configuration Guide

Overview​

Estimated time: 30–45 minutes

Spoolman is an open-source inventory and usage tracker for 3D-printing filament spools. This lab takes you through the full operational lifecycle of the Spoolman 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 Spoolman 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.
  • 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 Spoolman (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 and a Cloud SQL (PostgreSQL 15) database with its Secret Manager password secret, and pulls the prebuilt ghcr.io/donkie/spoolman image directly — there is no Cloud Build step and no database-initialization job to wait for (Spoolman migrates itself on boot). First deploys take roughly 15–25 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="$REGION" \
      --filter="metadata.name~spoolman" --format="value(metadata.name)" --limit=1)
    SERVICE_URL=$(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:

    curl -s "$SERVICE_URL/api/health"   # expect a 200/OK JSON status

  2. Open $SERVICE_URL in a browser. Spoolman has no login gate — the UI loads directly into the spool inventory dashboard with no admin account to create. If you need to restrict access, apply IAP or a Cloud Armor allowlist now, before sharing the URL with anyone else.

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). Spoolman has no background work, so scale-to-zero (min_instance_count = 0) is safe at any time.

  3. Update the application version tag by changing the version input in the RAD platform and applying it via Update; Cloud Run pulls the new tag directly from ghcr.io/donkie/spoolman — no rebuild is needed since this is a genuinely prebuilt image.

  4. Manage secrets:

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

  5. Open a database session for inspection or maintenance:

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

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>".

  2. Monitoring — open the Cloud Run dashboard for the service and review request count, request latency, instance count (scaling behaviour), and CPU/memory utilisation. The module can provision an uptime check (when uptime_check_config.enabled = true); if enabled, confirm it is green under Monitoring → Uptime checks.

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 Spoolman releases.

  • Revision unhealthy / service won't serve: inspect the latest revision and its logs for startup errors, and confirm the SPOOLMAN_DB_* env vars resolved. The startup probe targets /api/health with a short 10-second initial delay — Spoolman boots fast since there's no schema-migration job to wait on separately. 
    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 and the DB password secret exists. Since there is no init job, this class of failure surfaces directly in the service's own boot logs.
  • App runs but shows an empty inventory using SQLite instead of Postgres: check whether SPOOLMAN_DB_TYPE=postgres was accidentally overridden or unset in environment_variables — Spoolman silently falls back to a throwaway local SQLite file with no error if this variable is missing. 
    gcloud run revisions describe <revision> --project="$PROJECT" --region="$REGION" \
      --format='value(spec.containers[0].env)' | tr ';' '\n' | grep -i spoolman_db
  • 403 / permission errors: verify the runtime service account's IAM roles.

See the Configuration Guide's Configuration Pitfalls section for setting-specific gotchas (including the lack of built-in authentication).

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, and Secret Manager secrets. 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 and Cloud SQL (PostgreSQL 15) with its password secret; no build, no init job
2 — Access & verifyManualHealth check passes; UI loads directly with no login gate
3 — OperateManualInspect revisions, scale, update version, manage secrets, DB access
4 — ObserveManualQuery Cloud Logging; review Cloud Monitoring metrics and uptime check
5 — TroubleshootManualDiagnose revision, database, and DB-engine-fallback issues
6 — Tear downAutomatedDelete (Trash) removes all module resources

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

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