Zammad on Cloud Run — Lab Guide

📖 Configuration Guide

Overview

Estimated time: 45–90 minutes

Zammad is an open-source helpdesk and customer support ticketing platform. This lab takes you through the full operational lifecycle of the Zammad 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 Zammad 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 and backups.
• 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

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Task 1 — Deploy the module [Automated]

1. Click Deploy in the RAD platform top navigation, open Zammad (Cloud Run) from the Platform Modules list to start configuration, 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, a Filestore NFS share for ticket attachments, a GCS bucket, Redis, builds the container image via Cloud Build, and runs a one-shot database-initialisation job. First deploys take roughly 20–40 minutes (Cloud SQL creation dominates; Zammad schema migrations run on first container start).

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="$REGION" \
     --filter="metadata.name~zammad" --format="value(metadata.name)" --limit=1)
   SERVICE_URL=$(gcloud run services describe "$SERVICE" \
     --project="$PROJECT" --region="$REGION" --format="value(status.url)")
   echo "Service: $SERVICE"
   echo "URL:     $SERVICE_URL"

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Task 2 — Access & verify [Manual]

1. Confirm the service is healthy and that Zammad has finished its schema migration:

   curl -s "$SERVICE_URL/api/v1/ping"   # expect {"pong":"PONG"}

   If you receive a non-200 response, wait 60–90 seconds and retry — Zammad runs its database migrations synchronously on first container start before the health endpoint becomes available.

2. Open $SERVICE_URL in a browser. Zammad displays a first-run setup wizard on the initial visit; follow the wizard to create the administrator account and set the organisation name. There is no pre-generated admin credential — the admin account is created through the wizard.

3. Retrieve the database password from Secret Manager (useful for direct DB access):

   DB_SECRET=$(gcloud secrets list --project="$PROJECT" \
     --filter="name~zammad" --format="value(name)" --limit=1)
   gcloud secrets versions access latest --secret="$DB_SECRET" --project="$PROJECT"

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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).

3. Update the application version by changing the version input via Update on the deployment details page; a new image builds and a new revision rolls out. Zammad applies any pending schema migrations automatically on container start.

4. Manage secrets, backups, and init jobs:

   gcloud secrets list --project="$PROJECT" --filter="name~zammad"
   gcloud run jobs list --project="$PROJECT" --region="$REGION" --filter="metadata.name~zammad"
   gcloud run jobs executions list --job="$(gcloud run jobs list \
     --project="$PROJECT" --region="$REGION" \
     --filter="metadata.name~db-init" --format="value(metadata.name)" --limit=1)" \
     --project="$PROJECT" --region="$REGION"

5. Open a database session for inspection or maintenance:

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

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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>".

   Look for the Zammad is running log line which confirms the railsserver started successfully after schema migration.

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. The module provisions an uptime check targeting /api/v1/ping; confirm it is green under Monitoring → Uptime checks, and review Alerting → Policies.

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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 Zammad releases.

• Revision unhealthy / service won't serve: inspect the latest revision and its logs for startup errors. Zammad's startup probe allows up to ~510 seconds for schema migration; if a revision is rejected sooner, check env vars and secret resolution.

  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 initialisation job completed successfully. The custom entrypoint uses DB_IP (Cloud SQL private IP) for the TCP readiness check — verify it is set correctly.
• Redis not available: Zammad requires Redis for ActionCable and Sidekiq; if Redis is unreachable the service will not start. Check redis_host and confirm vpc_egress_setting = "ALL_TRAFFIC" if using Memorystore.
• Initialisation job failed: list executions and read the failed one's logs:

  DBJOB=$(gcloud run jobs list --project="$PROJECT" --region="$REGION" \
    --filter="metadata.name~db-init" --format="value(metadata.name)" --limit=1)
  gcloud run jobs executions list --job="$DBJOB" --project="$PROJECT" --region="$REGION"

• 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.

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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, Filestore NFS share, GCS bucket, Secret Manager secrets, and Artifact Registry images. Resources owned by Services_GCP (the VPC, shared infrastructure) are managed separately and are not removed here.

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Summary

Task	Type	Outcome
1 — Deploy	Automated	Module provisions Cloud Run, Cloud SQL (PostgreSQL 15), NFS, Redis, secrets, GCS bucket, and runs DB init
2 — Access & verify	Manual	Health check passes at /api/v1/ping; complete first-run wizard to create admin account
3 — Operate	Manual	Inspect revisions, scale, update version, manage secrets/backups, DB access
4 — Observe	Manual	Query Cloud Logging; review Cloud Monitoring metrics and uptime check
5 — Troubleshoot	Manual	Diagnose revision, database, Redis, init-job, build, and IAM issues
6 — Tear down	Automated	Delete (Trash) removes all module resources