N8N_AI on Cloud Run — Lab Guide

📖 Configuration Guide

Overview

Estimated time: 45–90 minutes

n8n AI is an open-source workflow automation platform extended with integrated AI capabilities. Alongside the core n8n service it deploys two companion Cloud Run services — Qdrant (a vector database for embeddings and semantic search) and Ollama (a local LLM inference server) — enabling AI agent workflows, RAG pipelines, and intelligent chatbots on your own infrastructure with no external AI API dependencies. This lab takes you through the full operational lifecycle of the N8N_AI 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 n8n 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 n8n, Qdrant, and Ollama services.
• Perform day-2 operations — inspect, scale, update, and manage secrets and backups.
• Observe the services 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

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Task 1 — Deploy the module [Automated]

1. Click Deploy in the RAD platform top navigation, open N8N AI (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 three Cloud Run services (n8n, Qdrant internal, Ollama internal), a Cloud SQL (PostgreSQL) database with its Secret Manager secrets, Filestore NFS, a GCS bucket for AI data persistence, 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 (so the commands keep working regardless of the deployment suffix):

   SERVICE=$(gcloud run services list --project="$PROJECT" --region="$REGION" \
     --filter="metadata.name~n8nai" --format="value(metadata.name)" \
     --sort-by="metadata.creationTimestamp" --limit=1)
   SERVICE_URL=$(gcloud run services describe "$SERVICE" \
     --project="$PROJECT" --region="$REGION" --format="value(status.url)")
   echo "Service: $SERVICE"
   echo "URL:     $SERVICE_URL"
   
   # List all three services (n8n, Qdrant, Ollama)
   gcloud run services list --project="$PROJECT" --region="$REGION" \
     --filter="metadata.name~n8nai"

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Task 2 — Access & verify [Manual]

1. Confirm n8n is healthy and has connected to its database:

   curl -s "${SERVICE_URL}/"

   A redirect or the n8n login page indicates a healthy service. Cloud Run will not route traffic until the startup probe (targeting GET / on port 5678) succeeds, so a response here confirms a healthy revision.

2. Confirm the Qdrant and Ollama companion services are ready:

   QDRANT_SVC=$(gcloud run services list --project="$PROJECT" --region="$REGION" \
     --filter="metadata.name~qdrant" --format="value(metadata.name)" --limit=1)
   OLLAMA_SVC=$(gcloud run services list --project="$PROJECT" --region="$REGION" \
     --filter="metadata.name~ollama" --format="value(metadata.name)" --limit=1)
   gcloud run services describe "$QDRANT_SVC" \
     --project="$PROJECT" --region="$REGION" --format="value(status.conditions)"
   gcloud run services describe "$OLLAMA_SVC" \
     --project="$PROJECT" --region="$REGION" --format="value(status.conditions)"

3. Open $SERVICE_URL in a browser. On first launch, n8n prompts you to create an owner account. The n8n encryption key is auto-generated and stored in Secret Manager — back it up before destroying the module, as all saved credentials are encrypted with it.

   ENC_SECRET=$(gcloud secrets list --project="$PROJECT" \
     --filter="name~n8nai AND name~encryption" --format="value(name)" --limit=1)
   gcloud secrets versions access latest --secret="$ENC_SECRET" --project="$PROJECT"

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

1. Inspect the services and their 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.

4. Manage secrets and backups:

   gcloud secrets list --project="$PROJECT" --filter="name~n8nai"
   gcloud run jobs list --project="$PROJECT" --region="$REGION"   # db-init + scheduled backup 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 "$INSTANCE" --user=n8n_user --database=n8n_db --project="$PROJECT"

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Task 4 — Observe: Logging & Monitoring [Manual]

1. Logs — from the CLI or the Logs Explorer (all three services):

   # n8n service logs
   gcloud run services logs read "$SERVICE" --project="$PROJECT" --region="$REGION" --limit=50
   
   # Qdrant service logs
   gcloud run services logs read "$QDRANT_SVC" --project="$PROJECT" --region="$REGION" --limit=30
   
   # Ollama service logs
   gcloud run services logs read "$OLLAMA_SVC" --project="$PROJECT" --region="$REGION" --limit=30

   Logs Explorer filter for all n8nai services: resource.type="cloud_run_revision" AND resource.labels.service_name=~"n8nai".

2. Monitoring — open the Cloud Run dashboard and review request count, request latency (P50/P95/P99), instance count (scaling behaviour), and CPU/memory utilisation for each service. The module provisions an uptime check for the n8n service; 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 n8n 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 waits up to 120 seconds for n8n to connect to PostgreSQL before declaring failure.

  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.
• Initialisation job failed: list executions and read the failed one's logs:

  gcloud run jobs list --project="$PROJECT" --region="$REGION" --filter="name~n8nai"
  gcloud run jobs executions list --job="${SERVICE}-db-init" \
    --project="$PROJECT" --region="$REGION"

• Qdrant or Ollama unreachable from n8n: confirm the companion services have a healthy revision and that QDRANT_URL / OLLAMA_HOST are injected correctly into the n8n service env vars.

  gcloud run services describe "$SERVICE" --project="$PROJECT" --region="$REGION" \
    --format='value(spec.template.spec.containers[0].env)'

• 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 N8N_ENCRYPTION_KEY and enable_redis notes.

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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 — all three Cloud Run services (n8n, Qdrant, Ollama), the Cloud SQL database, Secret Manager secrets, GCS buckets, Filestore NFS, and Artifact Registry images. Resources owned by Services_GCP (the VPC, shared Cloud SQL, registry) are managed separately and are not removed here.

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Summary

Task	Type	Outcome
1 — Deploy	Automated	Module provisions n8n, Qdrant, and Ollama Cloud Run services, Cloud SQL, secrets, and runs DB init
2 — Access & verify	Manual	Health check passes; companion services ready; n8n account created; encryption key backed up
3 — Operate	Manual	Inspect revisions, scale, update version, manage secrets/backups, DB access
4 — Observe	Manual	Query Cloud Logging for all three services; review Cloud Monitoring metrics and uptime check
5 — Troubleshoot	Manual	Diagnose revision, database, init-job, AI companion, build, and IAM issues
6 — Tear down	Automated	Delete (Trash) removes all module resources