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AdGuardHome on GKE Autopilot — Lab Guide

📖 Configuration Guide

⚠️ CRITICAL — this module does not serve DNS. AdGuard Home's core value (network-wide DNS ad/tracker blocking) requires clients to query it on port 53 (TCP+UDP), which this module's standard HTTP(S) Gateway pattern cannot expose. This lab deploys and verifies AdGuard Home's web admin console only — do not expect it to act as a working DNS resolver for real clients.

Overview​

Estimated time: 45–60 minutes

AdGuard Home is an open-source, network-wide DNS ad- and tracker-blocking server with a web admin console for managing filter lists, custom rules, and per-client settings. This lab takes you through the full operational lifecycle of the AdGuard Home on GKE Autopilot module — deploying its web admin console, verifying it, running it day-to-day, observing it, diagnosing common problems, and tearing it down.

The lab focuses on operating the GKE module and the Google Cloud platform, not on AdGuard Home's DNS-filtering features (which are not reachable in this deployment shape). 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.
  • Connect to the GKE cluster and access the running admin console (and understand what it cannot do — serve real DNS).
  • Perform day-2 operations — inspect, scale, update, and manage storage.
  • 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 VPC, GKE Autopilot cluster, Artifact Registry, and shared service accounts this module depends on).
  • A Google Cloud project with billing enabled.
  • gcloud CLI and kubectl installed; gcloud auth login and gcloud auth application-default login completed.
  • 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 AdGuard Home (GKE) 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 deploys the workload into the GKE Autopilot cluster, provisions two Cloud Storage buckets (conf and work, mounted via GCS Fuse CSI), and builds the custom container image. There is no database and no init job, so this deploy is faster than most modules in this catalogue — typically 5–10 minutes.

  3. Connect to the cluster and discover the namespace with name-agnostic filters:

    CLUSTER=$(gcloud container clusters list --project="$PROJECT" --format="value(name)" --limit=1)
    gcloud container clusters get-credentials "$CLUSTER" --region="$REGION" --project="$PROJECT"

    NS=$(kubectl get ns -o name | grep adguardhome | head -1 | cut -d/ -f2)
    echo "Cluster: $CLUSTER   Namespace: $NS"
    kubectl get all -n "$NS"

Task 2 — Access & verify [Manual]​

  1. Confirm the workload is running and find its external address:

    kubectl get pods,svc -n "$NS"
    EXTERNAL_IP=$(kubectl get svc -n "$NS" \
      -o jsonpath='{.items[?(@.spec.type=="LoadBalancer")].status.loadBalancer.ingress[0].ip}')
    echo "External IP: $EXTERNAL_IP   (web admin console ONLY — not a DNS resolver)"

  2. Confirm the service responds:

    curl -s -o /dev/null -w '%{http_code}\n' "http://${EXTERNAL_IP}/"   # expect 200

  3. Open http://${EXTERNAL_IP} in a browser. On first visit, AdGuard Home serves its own setup wizard (not a RAD-managed login) on port 3000: choose the admin web UI port (keep it 3000 — see the Pitfalls note below), set the admin username and password, and select upstream DNS servers. Complete the wizard to reach the dashboard.

  4. Confirm the setup persisted by refreshing the page — you should land on the login page (not the setup wizard again), proving the configuration was written to the persistent conf GCS volume rather than lost on a pod restart.

  5. Remember: this deployment's DNS server function is not reachable — only the web admin console you just configured is. Do not configure real devices to use this service's IP as their DNS server.

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

  1. Inspect the workload:

    kubectl get deploy,pods -n "$NS"
    kubectl describe deploy -n "$NS"

  2. Scale by changing the min/max instance inputs and clicking Update on the deployment details page — the module owns the workload spec, so scaling is a configuration change, not a manual kubectl scale (a manual edit would be reverted on the next apply).

  3. Update the application version by changing the version input in the RAD platform and applying it via Update; a new image builds and a rolling update replaces the pod.

  4. Inspect storage:

    gcloud storage buckets list --project="$PROJECT" --filter="name~adguardhome"
    kubectl describe pod -n "$NS" -l app=adguardhome | grep -A5 Mounts

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

  1. Logs — from kubectl or the Logs Explorer:

    kubectl logs -n "$NS" deploy/"$(kubectl get deploy -n "$NS" -o jsonpath='{.items[0].metadata.name}')" --tail=50

    Look for the entrypoint's DNS-scope reminder banner near the start of a fresh pod's logs. Logs Explorer filter: resource.type="k8s_container" AND resource.labels.namespace_name="<namespace>".

  2. Monitoring — open the GKE / Kubernetes dashboards and review pod CPU and memory utilisation and restart counts. The module can provision an uptime check (when enabled); review Monitoring → Uptime checks.

Task 5 — Troubleshoot & debug [Manual]​

Durable techniques for the failure modes you are most likely to hit.

  • Pod not Ready / CrashLoopBackOff: inspect events and logs. 
    kubectl describe pod -n "$NS" <pod>          # Events section shows scheduling/probe/mount errors
    kubectl logs -n "$NS" <pod> --previous       # logs from the crashed container
  • Pod stops becoming Ready after you changed the web UI port in the setup wizard: this is the module's #1 known pitfall — the platform's health probe and public URL are fixed at container_port (3000). If you changed AdGuard Home's own web UI port away from 3000 during setup, revert it (edit AdGuardHome.yaml on the conf bucket, or re-run setup) or set container_port to match.
  • Configuration not persisting across pod restarts: confirm the conf and work GCS buckets exist and are mounted (kubectl describe pod → Mounts section) — check gcs_volumes was not overridden to something that omits them.
  • "Is this actually blocking ads on my network?" No — this deployment's DNS server is not reachable from outside the cluster's Service (which only forwards the admin console's HTTP port). This is expected; see the CRITICAL note at the top of this guide.
  • Pending pod / no external IP: check kubectl describe pod events for resource or quota issues, and confirm the LoadBalancer Service has an assigned IP.
  • Image pull errors: confirm the image exists in Artifact Registry and the node service account can pull it.

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 Kubernetes workload and namespace, GCS buckets (conf, work), and Artifact Registry images. Resources owned by Services_GCP (the VPC, GKE cluster, registry) are managed separately and are not removed here.

Summary​

TaskTypeOutcome
1 — DeployAutomatedModule deploys the GKE workload, two GCS buckets (conf, work), and builds the container image
2 — Access & verifyManualConnect to the cluster; health check passes; complete AdGuard Home's own setup wizard; confirm config persists
3 — OperateManualInspect workload, scale, update version, inspect storage
4 — ObserveManualQuery Cloud Logging; review Cloud Monitoring metrics and uptime check
5 — TroubleshootManualDiagnose pod, port-mismatch, storage, and scheduling issues
6 — Tear downAutomatedDelete (Trash) removes all module resources

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