OpenClaw on Cloud Run — Lab Guide

📖 Configuration Guide

Overview

Estimated time: 45–90 minutes

OpenClaw is a multi-tenant AI agent gateway for running isolated, persistent AI assistants backed by Anthropic models, with dedicated GCS-Fuse workspaces and optional Telegram or Slack channel integration. This lab takes you through the full operational lifecycle of the OpenClaw 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 OpenClaw 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, Serverless VPC Access, 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]

1. Click Deploy in the RAD platform top navigation, open OpenClaw (Cloud Run) from the Platform Modules list to start configuration, set project_id, and review the inputs. An Anthropic API key is required on the first deploy — set it in the corresponding input field. Configure only what else 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 builds a custom container image (layering entrypoint.sh onto the upstream OpenClaw image), creates a GCS workspace bucket mounted at /data via GCS Fuse, stores the Anthropic API key and gateway token in Secret Manager, and deploys the Cloud Run service. OpenClaw requires no Cloud SQL or init job — agent state lives entirely on GCS. First deploys take roughly 10–20 minutes (Cloud Build dominates).

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

   SERVICE=$(gcloud run services list --project="$PROJECT" --region="$REGION" \
     --filter="metadata.name~openclaw" --format="value(metadata.name)" --limit=1)
   SERVICE_URL=$(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]

1. By default, ingress_settings = "internal" restricts the service to VPC traffic. For direct access in this lab, use the gcloud proxy:

   gcloud run services proxy "$SERVICE" \
     --region="$REGION" --project="$PROJECT" --port=8080
   # Access at http://localhost:8080

   Alternatively, set ingress_settings = "all" in the RAD platform and apply it via Update.

2. Confirm the service is healthy:

   curl -s http://localhost:8080/health   # expect {"status":"ok"}

3. Retrieve the gateway token from Secret Manager to authenticate API calls:

   GW_SECRET=$(gcloud secrets list --project="$PROJECT" \
     --filter="name~openclaw~gateway-token" --format="value(name)" --limit=1)
   gcloud secrets versions access latest --secret="$GW_SECRET" --project="$PROJECT"

   The gateway token is the credential used by OpenClaw clients and integrations. The Anthropic API key can similarly be retrieved from its Secret Manager secret if needed (filter on ~openclaw~anthropic-api-key).

---

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). Note that OpenClaw is stateful; keep max_instance_count = 1 per tenant unless sticky routing is in place.

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="$PROJECT" --filter="name~openclaw"
   gcloud run jobs list --project="$PROJECT" --region="$REGION"   # scheduled backup jobs

5. Inspect the GCS workspace that backs all agent state:

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

---

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>".

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 also provisions an uptime check (when enabled); confirm it is 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 OpenClaw releases.

• Revision unhealthy / service won't serve: inspect the latest revision and its logs for startup errors. The startup probe targets GET /health on port 8080 and allows roughly 2 minutes for GCS Fuse mount and Node.js startup.

  gcloud run revisions list --service="$SERVICE" --project="$PROJECT" --region="$REGION"
  gcloud run services logs read "$SERVICE" --project="$PROJECT" --region="$REGION" --limit=100

• GCS Fuse mount failure: confirm the workspace bucket exists and that the runtime service account has Storage Object Admin on it. The service requires Gen2 execution environment — Gen1 does not support GCS Fuse and will silently fail.
• Anthropic API errors (401): confirm the anthropic-api-key secret has a valid version. Retrieve and verify it via Secret Manager.
• Gateway token errors: if clients receive auth failures after a secret rotation, the service must be updated to pick up the new token value.
• Skills repository clone failure: an unreachable or non-existent skills_repo_url / skills_repo_ref causes the container to fail at startup. Check Cloud Logging for skill-library entries and correct the URL/ref in the RAD platform.
• 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.

---

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

---

Summary

Task	Type	Outcome
1 — Deploy	Automated	Module builds the image, provisions the GCS workspace, stores secrets, and deploys Cloud Run
2 — Access & verify	Manual	Proxy or public access; health check passes; gateway token retrieved
3 — Operate	Manual	Inspect revisions, scale, update version, manage secrets/backups, inspect GCS workspace
4 — Observe	Manual	Query Cloud Logging; review Cloud Monitoring metrics and uptime check
5 — Troubleshoot	Manual	Diagnose revision, GCS Fuse, Anthropic API, gateway token, skills-sync, and IAM issues
6 — Tear down	Automated	Delete (Trash) removes all module resources