Maybe Finance on Cloud Run — Lab Guide

Overview

Estimated time: 45–90 minutes

Maybe (Maybe Finance) is an open-source, self-hosted alternative to Mint/Monarch for personal finance and wealth management — budgeting, net-worth tracking, transaction categorization, and multi-account aggregation, built on Ruby on Rails. This lab takes you through the full operational lifecycle of the Maybe Finance 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 Maybe's 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 its mandatory PostgreSQL and Redis dependencies.
Perform day-2 operations — inspect, scale, update, and manage secrets and backups.
Understand why scale-to-zero affects the co-located Sidekiq background-job worker, and how to keep it running continuously.
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, Filestore NFS/Redis, 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]

In the RAD platform, open Maybe Finance (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.
The platform builds a thin custom wrapper image FROM ghcr.io/maybe-finance/maybe:stable, provisions the Cloud Run service, a Cloud SQL (PostgreSQL 15) database, mounts the shared Filestore NFS volume at /opt/maybefinance/storage (also the default source of the Redis host), creates the SECRET_KEY_BASE secret in Secret Manager, provisions a storage data bucket, and runs two chained one-shot jobs — db-init (creates the database/user/grants and pre-creates pgcrypto) followed by maybefinance-migrate (rails db:prepare). First deploys take roughly 20–35 minutes (Cloud SQL creation dominates).

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="$REGION" \
  --filter="metadata.name~maybefinance" --format="value(metadata.name)" --limit=1)
SERVICE_URL=$(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]

Confirm the service is healthy. Maybe's Rails app exposes a public, unauthenticated health endpoint that the platform's own startup/liveness probes also target:
```
curl -s -o /dev/null -w "%{http_code}\n" "$SERVICE_URL/up"   # expect 200
```
Open $SERVICE_URL in a browser. Maybe runs with SELF_HOSTED = "true", so the first visitor to reach the deployment registers the initial administrator account through the web UI — there is no pre-seeded admin credential in Secret Manager. Register the admin account promptly; anyone with the URL who gets there first claims that role.
Confirm the background worker is alive — Sidekiq runs in-process inside the same container as Rails/Puma, started only if Redis was reachable at boot:
```
gcloud run services logs read "$SERVICE" --project="$PROJECT" --region="$REGION" \
  --limit=50 | grep -i sidekiq
```

Task 3 — Operate & keep it running (Day-2) [Manual]

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"

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). By default min_instance_count = 0 and cpu_always_allocated = false (cost-first): the co-located Sidekiq worker only runs while an instance happens to be alive, so account syncing, import processing, and notifications silently stop firing during scale-to-zero windows. For continuous background-job processing, set min_instance_count = 1 and cpu_always_allocated = true, matching the GKE variant's defaults.
Update the application version by changing the version input in the RAD platform and applying it via Update; a new image builds FROM ghcr.io/maybe-finance/maybe:<tag> (via the app-specific MAYBE_VERSION build ARG) and a new revision rolls out.

Manage secrets and backups:

gcloud secrets list --project="$PROJECT" --filter="name~maybefinance"
gcloud run jobs list --project="$PROJECT" --region="$REGION"   # db-init, maybefinance-migrate, scheduled backup jobs

Never rotate the SECRET_KEY_BASE secret after first boot — it invalidates every active session and makes ActiveRecord-encrypted columns permanently unreadable.

Open a database session for inspection or maintenance:

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

Task 4 — Observe: Logging & Monitoring [Manual]

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>".
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 combined Rails + Sidekiq process is memory-hungry under import/sync workloads. The uptime_check_config is disabled by default; enable it via the RAD platform and confirm it turns 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 Maybe releases.

Revision unhealthy / service won't serve: inspect the latest revision and its logs for startup errors. The startup probe targets /up and allows roughly 8 minutes on first boot (initial_delay_seconds=60, failure_threshold=30).
```
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. Cloud Run reaches it over the instance's private IP with sslmode=require by default (enable_cloudsql_volume=false, since Rails' pg driver cannot parse the Cloud SQL socket DSN) — check that PGSSLMODE=require resolved correctly and the db-init job completed.

Initialisation/migration job failed: list executions and read the failed one's logs, checking db-init before maybefinance-migrate (the latter depends on the former):

gcloud run jobs executions list --job="${SERVICE}-db-init" \
  --project="$PROJECT" --region="$REGION"
gcloud run jobs executions list --job="${SERVICE}-maybefinance-migrate" \
  --project="$PROJECT" --region="$REGION"

Background jobs (account sync, imports, notifications) not firing: usually means Sidekiq never started — check REDIS_URL resolved non-empty in the container env, and that the instance hasn't scaled to zero between requests (see Task 3, item 2).
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 the critical rules never to rotate SECRET_KEY_BASE after first boot, and that database_type and enable_redis are enforced by plan-time preconditions that reject anything but PostgreSQL and a working Redis host).

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, and the storage/data GCS buckets. Resources owned by Services_GCP (the VPC, the shared Filestore NFS/Redis VM, shared Cloud SQL host, Artifact Registry) are managed separately and are not removed here.

Summary

Task	Type	Outcome
1 — Deploy	Automated	Module builds a custom wrapper image, provisions Cloud Run, Cloud SQL (PostgreSQL 15), NFS/Redis wiring, secrets, storage buckets, and runs `db-init` + `maybefinance-migrate`
2 — Access & verify	Manual	`/up` health check passes; register the initial admin account in the UI; confirm Sidekiq started
3 — Operate	Manual	Inspect revisions, scale (mind the Sidekiq/scale-to-zero trade-off), update version, manage secrets/backups, DB access
4 — Observe	Manual	Query Cloud Logging; review Cloud Monitoring metrics and (optional) uptime check
5 — Troubleshoot	Manual	Diagnose revision, database (SSL mode), init/migration-job, background-job, build, and IAM issues
6 — Tear down	Automated	Delete (Trash) removes all module resources; shared NFS/Redis and Cloud SQL host are untouched

By Dr Shiyghan Emmanuel Navti · Google Cloud certified: ACE · PCA · PCD · PDE · PSE · CDL

Overview​

Objectives​

Prerequisites​

Task 1 — Deploy the module [Automated]​

Task 2 — Access & verify [Manual]​

Task 3 — Operate & keep it running (Day-2) [Manual]​

Task 4 — Observe: Logging & Monitoring [Manual]​

Task 5 — Troubleshoot & debug [Manual]​

Task 6 — Tear down [Automated]​

Summary​