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Firefly III on Cloud Run — Lab Guide

📖 Configuration Guide

Overview​

Estimated time: 45–90 minutes

Firefly III is a free, open-source self-hosted personal-finance manager for tracking accounts, transactions, budgets, bills, and recurring transactions. This lab takes you through the full operational lifecycle of the Firefly III 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 Firefly III 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 create the first admin account.
  • Perform day-2 operations — inspect, scale, update, manage secrets and backups, and wire the cron endpoint.
  • 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 Firefly III (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 Laravel APP_KEY, the STATIC_CRON_TOKEN, and the database password), a Cloud Storage uploads bucket, an NFS/Filestore volume for attachments, and runs a one-shot db-init job (create role + database). First deploys take roughly 20–35 minutes (Cloud SQL creation dominates). The schema itself is created on the container's first boot, not by a separate migrate job.

  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="$REGION" \
      --filter="metadata.name~fireflyiii" --format="value(metadata.name)" --limit=1)
    SERVICE_URL=$(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. Firefly III exposes an unauthenticated /health endpoint that returns 200 once the app is up and connected to PostgreSQL:

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

  2. Open $SERVICE_URL in a browser. On first visit Firefly III shows the /register page. Fill in your email and a password and submit — the first account created becomes the site owner/administrator; no pre-seeded admin credential exists in Secret Manager. After creating it, open Administration → Settings and disable further registration to prevent unauthorised account creation.

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). Set min_instance_count = 1 if you want to avoid cold starts.

  3. Update the application version by changing the version input in the RAD platform and applying it via Update; a new revision rolls out and the image self-migrates the schema on boot.

  4. Wire the cron endpoint so recurring transactions, bill reminders, and auto-budgets fire. Read the token and trigger it manually to verify, then create a daily Cloud Scheduler job (or use the cron_jobs input):

    CRON_SECRET=$(gcloud secrets list --project="$PROJECT" \
      --filter="name~cron-token" --format="value(name)" --limit=1)
    TOKEN=$(gcloud secrets versions access latest --secret="$CRON_SECRET" --project="$PROJECT")
    curl -s "$SERVICE_URL/api/v1/cron/$TOKEN"

  5. Manage secrets and backups:

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

  6. Open a database session for inspection or maintenance:

    INSTANCE=$(gcloud sql instances list --project="$PROJECT" --format="value(name)" --limit=1)
    gcloud sql connect "$INSTANCE" --user=fireflyiii --project="$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 (P50/P95/P99), instance count (scaling behaviour), and CPU / memory utilisation. If you enabled uptime_check_config, 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 Firefly III 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 is TCP on port 8080 and allows a generous first-boot window while migrations run. 
    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 db-init job completed. On Cloud Run the connection is private-IP TCP with PGSQL_SSL_MODE = require — a plaintext/disable mode fails.
  • 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"
  • Recurring transactions not firing: verify a daily Cloud Scheduler job hits /api/v1/cron/<STATIC_CRON_TOKEN> — Firefly does no scheduling on its own.
  • Uploaded attachments disappearing: confirm enable_nfs = true and the NFS volume is mounted at /var/lib/fireflyiii; without it, files land on ephemeral disk.
  • 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 critical rule never to rotate APP_KEY after first boot).

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, NFS volume, 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, uploads bucket, NFS, and runs DB init
2 — Access & verifyManual/health returns 200; create the owner account at /register
3 — OperateManualInspect revisions, scale, update version, wire cron, manage secrets/backups, DB access
4 — ObserveManualQuery Cloud Logging; review Cloud Monitoring metrics and uptime check
5 — TroubleshootManualDiagnose revision, database, init-job, cron, NFS, 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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