Dolibarr on GKE Autopilot — Lab Guide

Overview

Estimated time: 45–90 minutes

Dolibarr is a free, open-source ERP and CRM suite covering customers and prospects, quotes, orders, invoices, products and stock, HR, projects, and accounting. This lab takes you through the full operational lifecycle of the Dolibarr on GKE Autopilot 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 GKE module and the Google Cloud platform, not on Dolibarr 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.
Connect to the GKE cluster and access the running workload.
Perform day-2 operations — inspect, scale, update, and manage secrets and 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, Cloud SQL, Cloud Filestore (NFS), 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]

Click Deploy in the RAD platform top navigation, open Dolibarr (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.
The platform deploys the workload into the GKE Autopilot cluster, provisions a Cloud SQL (MySQL 8.0) database with its Secret Manager secrets (DOLI_ADMIN_PASSWORD, DOLI_INSTANCE_UNIQUE_ID, and the database password), a Cloud Filestore (NFS) share mounted at /var/lib/dolibarr, a dolibarr-documents Cloud Storage bucket, builds the container image, and runs a one-shot database-initialisation job. Dolibarr's own installer then creates the schema on first pod start (DOLI_INSTALL_AUTO = 1) — there is no separate migration job. First deploys take roughly 20–35 minutes (Cloud SQL and Filestore creation dominate).

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 dolibarr | head -1 | cut -d/ -f2)
echo "Cluster: $CLUSTER   Namespace: $NS"
kubectl get all -n "$NS"

Task 2 — Access & verify [Manual]

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"

Confirm the service is healthy. The startup probe is TCP on port 80 and the liveness probe is HTTP GET / (the login page returns 200 with no auth). Allow several minutes on first boot for the Dolibarr installer to run:
```
curl -s -o /dev/null -w "%{http_code}" "http://${EXTERNAL_IP}/"   # expect 200
```

Retrieve the auto-generated super-admin password before your first login:

ADMIN_SECRET=$(gcloud secrets list --project="$PROJECT" \
  --filter="name~dolibarr AND name~admin-password" --format="value(name)" --limit=1)
gcloud secrets versions access latest --secret="$ADMIN_SECRET" --project="$PROJECT"

Set DOLI_URL_ROOT now that the external IP is known, so absolute links and the login redirect resolve correctly — it is not preset on GKE. Either add it to environment_variables in the RAD platform and click Update, or patch the running Deployment directly:

SVC=$(kubectl get svc -n "$NS" -o jsonpath='{.items[0].metadata.name}')
kubectl patch deploy "$SVC" -n "$NS" \
  -p '{"spec":{"template":{"spec":{"containers":[{"name":"dolibarr","env":[
    {"name":"DOLI_URL_ROOT","value":"http://'"$EXTERNAL_IP"'"}]}]}}}}'

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

Inspect the workload — Deployment, pods, PVC (Filestore-backed), and events:
```
kubectl get deploy,pods,pvc -n "$NS"
kubectl describe deploy -n "$NS"
```
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). Keep max_instance_count = 1 unless you have verified Dolibarr's shared-session and NFS-lock behaviour under multiple pods; the workload uses the Recreate update strategy specifically because it is NFS-backed (a rolling update would run two pods against the same NFS volume and DB and deadlock).
Update the application version by changing the version input in the RAD platform and applying it via Update; a new image builds and the pod is recreated, running Dolibarr's own upgrade steps at boot.

Manage secrets, storage, and jobs:

kubectl get secrets -n "$NS"
gcloud secrets list --project="$PROJECT" --filter="name~dolibarr"
gcloud storage buckets list --project="$PROJECT" --filter="name~dolibarr-documents"
gcloud filestore instances list --project="$PROJECT"
kubectl get jobs -n "$NS"          # db-init job

Open a database session for inspection or maintenance:

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

Task 4 — Observe: Logging & Monitoring [Manual]

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
```
Logs Explorer filter: resource.type="k8s_container" AND resource.labels.namespace_name="<namespace>".
Monitoring — open the GKE / Kubernetes dashboards and review pod CPU and memory utilisation, restart counts, and request metrics, plus the Cloud SQL and Filestore instance dashboards. The module can provision an uptime check (when enabled); review Monitoring → Uptime checks and 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 Dolibarr releases.

Pod not Ready / CrashLoopBackOff: inspect events and logs. The liveness probe targets GET /; a connection failure to Cloud SQL (via the Auth Proxy sidecar on 127.0.0.1:3306) will keep the pod from becoming Ready.

kubectl describe pod -n "$NS" <pod>          # Events section shows scheduling/probe/mount errors
kubectl logs -n "$NS" <pod> --previous       # logs from the crashed container
kubectl exec -n "$NS" deploy/<service-name> -- env | grep DOLI_DB

Database connection errors: confirm the Cloud SQL instance is RUNNABLE, the DB password secret materialised into the namespace, and the db-init job completed (it is safe to re-run; max_retries = 3).

Initialisation job failed: inspect the job and its pod logs:

kubectl get jobs -n "$NS"
kubectl logs -n "$NS" job/<db-init-job-name>

Installer loops or shows DB errors on first boot: confirm the db-init job ran to completion before the first browser visit — DOLI_INSTALL_AUTO = 1 needs an empty, reachable database to create the schema against.
Documents/PDFs disappear after a pod restart: confirm enable_nfs = true and that the PVC is bound to the Filestore share at /var/lib/dolibarr — a disabled or unmounted NFS volume makes uploads ephemeral.
```
kubectl get pvc -n "$NS"
gcloud filestore instances list --project="$PROJECT"
```
Rollout stuck on update (1 old replicas are pending termination): expected behaviour for the Recreate strategy — the old pod must fully terminate before the new one starts, so a brief outage during updates is normal, not a hang. If it persists well beyond a minute, check for a stuck NFS/DB lock from the old pod.
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 & Sensible Defaults section for setting-specific gotchas (including the critical rules never to change application_database_name/application_database_user or the auto-generated DOLI_INSTANCE_UNIQUE_ID after first boot).

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, Cloud SQL database, Cloud Filestore share, Secret Manager secrets, GCS buckets, and Artifact Registry images. Resources owned by Services_GCP (the VPC, GKE cluster, shared Cloud SQL, registry) are managed separately and are not removed here.

Summary

Task	Type	Outcome
1 — Deploy	Automated	Module deploys the GKE workload, Cloud SQL (MySQL 8.0), Filestore (NFS), secrets, storage bucket, and runs DB init
2 — Access & verify	Manual	Connect to the cluster; health check passes; retrieve admin password and log in; set `DOLI_URL_ROOT`
3 — Operate	Manual	Inspect workload, scale (with NFS/lock caveats), update version, manage secrets/storage, DB access
4 — Observe	Manual	Query Cloud Logging; review Cloud Monitoring metrics and uptime check
5 — Troubleshoot	Manual	Diagnose pod, database, init-job, NFS, and image-pull issues
6 — Tear down	Automated	Delete (Trash) removes all module resources

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​