Chibisafe on Cloud Run — Lab Guide

Overview

Estimated time: 45–90 minutes

Chibisafe is a self-hosted file and image uploader with drag-and-drop uploads, albums, and a public API. This module deploys the chibisafe-server backend only (port 8000) as a single custom-built Cloud Run v2 service with no external database — SQLite, uploads, and logs all live on one Cloud Storage bucket mounted via GCS Fuse. This lab takes you through the full operational lifecycle of the Chibisafe on Cloud Run module: 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 Chibisafe 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 backend through its health endpoint.
Perform day-2 operations — inspect revisions, manage the optional admin secret, and understand why the service is pinned to a single instance.
Inspect the SQLite/uploads/logs state on the Cloud Storage-backed volume.
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, 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 Chibisafe (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 and pushes the custom chibisafe-server image (pinned to v6.5.5 unless you set a specific version), provisions the Cloud Run v2 service, and always provisions a storage Cloud Storage bucket mounted at /data via GCS Fuse. No Cloud SQL instance is created — database_type is fixed to NONE. If enable_api_key = true, a random admin-password secret is also created in Secret Manager. There is no database to provision, so first deploys typically take 10–20 minutes (the custom image build 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="$REGION" \
  --filter="metadata.name~chibisafe" --format="value(metadata.name)" --limit=1)
SERVICE_URL=$(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 backend is healthy. Chibisafe's backend serves all routes under an /api prefix and has no root route — do not expect anything useful from $SERVICE_URL/. Use the dedicated health endpoint instead:
```
curl -s "$SERVICE_URL/api/health"   # expect HTTP 200, {"status":"yes"}
curl -s -o /dev/null -w '%{http_code}\n' "$SERVICE_URL/"   # expect 404 — this is normal, not a bug
```
This module deploys the backend API only — Chibisafe's separate SvelteKit front-end and Caddy reverse proxy are not part of this module, so there is no bundled dashboard to browse to at $SERVICE_URL. Administer the instance through the backend's REST API, or point a separately hosted Chibisafe front-end at $SERVICE_URL as its API base.
Admin credential: by default (enable_api_key = false) the backend seeds its first-run administrator account with Chibisafe's well-known upstream default credential (consult upstream Chibisafe documentation for the exact value) — change it immediately after first login. To avoid the well-known default entirely, redeploy with enable_api_key = true; the module then generates a random value and injects it as ADMIN_PASSWORD. Retrieve it with:
```
gcloud secrets list --project="$PROJECT" --filter="name~chibisafe AND name~api-key"
gcloud secrets versions access latest --secret=<api-key-secret-name> --project="$PROJECT"
```

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"

Do not scale beyond one instance. min_instance_count = max_instance_count = 1 by default and this is a hard requirement, not a tunable default: Chibisafe is a single-writer SQLite application sharing one GCS Fuse mount, and GCS Fuse's POSIX file-locking semantics are weaker than a real filesystem. A second concurrent writer risks corrupting the SQLite database. If you need durable, safely-scalable storage, use Chibisafe_GKE (block PVC) instead.
Update the application version by changing the application_version input in the RAD platform and applying it via Update; the image is rebuilt with the pinned CHIBISAFE_VERSION build arg and a new revision rolls out.

Manage the optional admin secret:

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

Inspect the stored state directly — there is no database client to connect with; SQLite, uploads, and logs live on the mounted bucket:

BUCKET=$(gcloud storage buckets list --project="$PROJECT" --filter="name~chibisafe" --format="value(name)" --limit=1)
gcloud storage ls "gs://${BUCKET}/database" "gs://${BUCKET}/uploads" "gs://${BUCKET}/logs"

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, instance count, and CPU / memory utilisation (expect a flat single instance under normal use). An uptime check is available but disabled by default (uptime_check_config.enabled = false) — enable it once you have a stable public URL, then confirm it 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 Chibisafe releases.

Revision unhealthy / restart loop: the startup and liveness probes correctly target /api/health on this module by default — if you have overridden startup_probe / liveness_probe to / (matching the inert startup_probe_config / health_check_config variables, or the GKE variant's default), the backend 404s there and the container restart-loops. Revert the path to /api/health.
```
gcloud run revisions list --service="$SERVICE" --project="$PROJECT" --region="$REGION"
gcloud run services logs read "$SERVICE" --project="$PROJECT" --region="$REGION" --limit=100
```
Uploads or the database appear to reset or corrupt: GCS Fuse's POSIX file-locking semantics are not fully safe for sustained/concurrent SQLite writes. Confirm max_instance_count = 1 has not been changed, and treat this Cloud Run variant as suited to light/low-traffic use — move to Chibisafe_GKE (block PVC) for heavier or production workloads.
Service unreachable despite passing health checks: confirm ingress_settings = "all" (public) — this module was historically swept up in a fleet-wide bug that defaulted some modules' ingress to internal; the current source default is correctly all, but verify your deployed configuration.
403 / permission errors: verify the runtime service account's IAM roles.
Image build failed: review Cloud Build history for the failed build's log.

See the Configuration Guide's Configuration Pitfalls section for setting-specific gotchas (including the persistence-model risk, the enable_api_key security trade-off, and the inert startup_probe_config / health_check_config / enable_redis / enable_cloudsql_volume variables).

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, the Cloud Storage data bucket (SQLite database, uploads, and logs), and the optional admin-password secret. There is no Cloud SQL database to remove — none was ever created. Resources owned by Services_GCP (the VPC, Artifact Registry) are managed separately and are not removed here.

Summary

Task	Type	Outcome
1 — Deploy	Automated	Module builds the custom image and provisions Cloud Run, a GCS data bucket (`/data` via GCS Fuse), and an optional admin secret — no Cloud SQL
2 — Access & verify	Manual	Health check at `/api/health` passes (`/` correctly 404s); administer via the API or an external front-end
3 — Operate	Manual	Inspect revisions, update version, manage the admin secret, inspect SQLite/uploads/logs on the bucket; never scale past 1 instance
4 — Observe	Manual	Query Cloud Logging; review Cloud Monitoring metrics and optional uptime check
5 — Troubleshoot	Manual	Diagnose probe-path, GCS Fuse write-safety, ingress, IAM, and build issues
6 — Tear down	Automated	Delete (Trash) removes the service, bucket, and optional secret

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​