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Ghostfolio on GKE Autopilot — Lab Guide

📖 Configuration Guide

Overview​

Estimated time: 45–90 minutes

Ghostfolio is an open-source wealth management application for tracking net worth, investment portfolios, and asset allocation across multiple brokerage accounts. This lab takes you through the full operational lifecycle of the Ghostfolio on GKE Autopilot 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 GKE module and the Google Cloud platform, not on Ghostfolio 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 workload, including its combined DB+Redis health check.
  • Perform day-2 operations — inspect, scale, update, and manage secrets and backups.
  • Observe the workload 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 GKE Autopilot cluster, 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
export NAMESPACE="<deployment-namespace>"   # from the deployment outputs

gcloud container clusters get-credentials <cluster-name> --region "$REGION" --project "$PROJECT"

Task 1 — Deploy the module [Automated]​

  1. In the RAD platform, open Ghostfolio (GKE), set project_id, and review the inputs. Configure only what you need — the Configuration Guide documents every input by group, with defaults. Note that enable_redis defaults to true and is REQUIRED — do not disable it. 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 GKE Deployment + Service, a Cloud SQL (PostgreSQL 15) database with its Secret Manager secrets (ACCESS_TOKEN_SALT, JWT_SECRET_KEY, and the database password), builds the container image, and runs a one-shot database-initialisation Job. First deploys take roughly 20–35 minutes (Cloud SQL creation dominates).

  3. When it completes, discover the resources with name-agnostic filters:

    kubectl get deployment -n "$NAMESPACE" | grep -i ghostfolio
    kubectl get svc -n "$NAMESPACE" | grep -i ghostfolio
    SERVICE_IP=$(kubectl get svc -n "$NAMESPACE" -l app=ghostfolio \
      -o jsonpath='{.items[0].status.loadBalancer.ingress[0].ip}')
    echo "Service IP: $SERVICE_IP"

Task 2 — Access & verify [Manual]​

  1. Confirm the pod is healthy and connected to BOTH its database AND Redis. Ghostfolio's health endpoint checks both dependencies and returns 503 until both are reachable:

    curl -s -o /dev/null -w '%{http_code}\n' "http://$SERVICE_IP/api/v1/health"   # expect 200
    curl -s "http://$SERVICE_IP/api/v1/health"                                    # expect {"status":"OK"}
    kubectl get pods -n "$NAMESPACE" -l app=ghostfolio   # expect N/N Running, 0 restarts

  2. Open http://$SERVICE_IP (or your configured custom domain) in a browser. Ghostfolio has no email/password login form — click Get Started and the app mints a random anonymous "Security Token" as your account owner credential. Save this token; it is your only credential for this account.

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

  1. Inspect the workload and its rollout history:

    kubectl describe deployment <deployment-name> -n "$NAMESPACE"
    kubectl rollout history deployment/<deployment-name> -n "$NAMESPACE"

  2. Scale by changing the min/max instance inputs and clicking Update on the deployment details page — the module owns the Deployment spec, so scaling is a configuration change, not a manual kubectl scale (a manual scale would be reverted on the next apply, though kubectl scale --replicas=0 is the documented way to temporarily park a verified deployment).

  3. Update the application version tag by changing the version input in the RAD platform and applying it via Update; a new image builds and the Deployment rolls out.

  4. Manage secrets and backups:

    gcloud secrets list --project="$PROJECT" --filter="name~ghostfolio"
    kubectl get jobs -n "$NAMESPACE"   # init 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 "$INSTANCE" --user=ghostfolio --project="$PROJECT"

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

  1. Logs — from the CLI or the Logs Explorer:

    kubectl logs -n "$NAMESPACE" -l app=ghostfolio --tail=100

    Logs Explorer filter: resource.type="k8s_container" AND resource.labels.namespace_name="<namespace>".

  2. Monitoring — review pod CPU/memory utilisation and restart counts. The module can provision an uptime check (when uptime_check_config.enabled = true — it defaults to false); 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 Ghostfolio releases.

  • Pod not Ready / crash-looping: inspect pod events and logs for startup errors. The startup probe targets /api/v1/health, which fails until BOTH the database AND Redis are reachable — a 503 here often means Redis is not yet reachable, not a database problem. 
    kubectl describe pod -n "$NAMESPACE" -l app=ghostfolio
    kubectl logs -n "$NAMESPACE" -l app=ghostfolio --previous
  • Database connection errors: confirm the Cloud SQL instance is RUNNABLE and the cloud-sql-proxy sidecar is running in the pod (kubectl get pod <pod> -o jsonpath='{.spec.containers[*].name}'). On GKE, Ghostfolio's cloud entrypoint expects DB_IP to resolve to 127.0.0.1 (the proxy loopback) with sslmode=disable.
  • Redis connection errors: if redis_host was left empty, confirm the platform NFS server VM is RUNNING; otherwise REDIS_HOST is empty and the health check never passes.
  • Initialisation Job failed: 
    kubectl get jobs -n "$NAMESPACE"
    kubectl logs -n "$NAMESPACE" job/<job-name>
  • Image build failed: review Cloud Build history for the failed build's log.
  • Unreachable from a browser: confirm service_type = "LoadBalancer" (the default) and that an external IP has been assigned (kubectl get svc -n "$NAMESPACE").

See the Configuration Guide's Configuration Pitfalls section for setting-specific gotchas (including the critical rule never to rotate ACCESS_TOKEN_SALT 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). Delete removes everything the module created — the GKE Deployment and Service, Cloud SQL database, Secret Manager secrets, and Artifact Registry images. Resources owned by Services_GCP (the GKE cluster, VPC, shared Cloud SQL, registry, NFS Redis host) are managed separately and are not removed here.

Summary​

TaskTypeOutcome
1 — DeployAutomatedModule provisions GKE Deployment/Service, Cloud SQL (PostgreSQL 15), secrets, and runs DB init
2 — Access & verifyManualHealth check passes (DB + Redis); mint an anonymous Security Token via "Get Started"
3 — OperateManualInspect rollout, scale, update version, manage secrets/backups, DB access
4 — ObserveManualQuery Cloud Logging; review Cloud Monitoring metrics and uptime check
5 — TroubleshootManualDiagnose pod, database, Redis, init-job, build, and networking issues
6 — Tear downAutomatedDelete (Trash) removes all module resources

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

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