SnipeIT on GKE Autopilot — Lab Guide

Overview

Estimated time: 45–90 minutes

Snipe-IT is a free, open-source IT asset and inventory management system for tracking hardware, software licences, accessories, and consumables, with asset check-in/out, audit logging, depreciation, and a full REST API. This lab takes you through the full operational lifecycle of the Snipe-IT 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 Snipe-IT 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, including its first-run /setup wizard.
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 (provides the VPC, GKE Autopilot cluster, Cloud SQL, Artifact Registry, and shared service accounts this module depends on). You do not need to deploy this yourself first — the platform automatically detects whether it already exists in the target project and provisions it before this module if not (see Task 1).
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.
Bringing your own project? Before the first deploy into it, the deployment confirmation dialog asks you to prove you control it (Get verification code, run the commands it shows as a project Owner, then Verify) and to give the RAD deployment service account the Owner role. A project RAD creates for you needs neither.
Advanced mode for later changes. The create form asks only for the first page of inputs (and, in a project RAD creates for you, little more than the tenant name and region). Every other input in the Configuration Guide — including the scaling and version inputs in the Day-2 tasks — is changed afterwards with Update on the deployment's page after ticking Enable advanced mode, which needs a credit balance that covers the update's estimated build cost (updates never carry a module fee). On a lab environment only an administrator can use Advanced mode.
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]

Open Solutions → Solution Catalog → RAD modules in the RAD platform top navigation, open Snipe-IT (GKE) from the Platform Modules list to start configuration, choose Configuration Form under How would you like to configure this deployment? (the form opens on the Conversational Assistant if you hold purchased credits or are a partner or administrator), set project_id, and review the inputs. Configure only what you need — the Configuration Guide documents every input by group, with defaults. Click Deploy Module, review the estimated cost in the Deployment Confirmation dialog when it appears and click Submit (if the dialog then adds a confirmation step, such as verifying a project you bring, complete it and click Confirm), which opens the deployment status page with real-time logs.
The platform deploys the workload into the GKE Autopilot cluster running the official snipe/snipe-it PHP/Apache image (no custom build), provisions a Cloud SQL for MySQL 8.0 database with its Secret Manager secrets (the Laravel APP_KEY and the database password), a Cloud Filestore (NFS) instance mounted at /var/lib/snipeit for uploaded asset images/signatures/barcodes, a Cloud Storage snipeit-uploads bucket, and runs two ordered initialisation jobs (db-init then migrate). 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"

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

Task 2 — Access & verify [Manual]

Confirm the workload is running and find its external address:

kubectl get pods,svc -n "$NAMESPACE"
EXTERNAL_IP=$(kubectl get svc -n "$NAMESPACE" \
  -o jsonpath='{.items[?(@.spec.type=="LoadBalancer")].status.loadBalancer.ingress[0].ip}')
echo "External IP: $EXTERNAL_IP"

Confirm the service is healthy. Snipe-IT serves its login/setup page at / unauthenticated, so a 200 there confirms the PHP application and the MySQL connection (reached via the Cloud SQL Auth Proxy sidecar on 127.0.0.1:3306) are both healthy:
```
curl -s -o /dev/null -w "%{http_code}\n" "http://${EXTERNAL_IP}/"   # expect 200
```
Open http://${EXTERNAL_IP} in a browser. On a fresh install, Snipe-IT redirects / to the /setup installation wizard rather than offering a self-serve sign-up form. Walk through the wizard to create the first administrator account. If the redirect loops or lands on the wrong host, confirm APP_URL matches the address you're browsing to (Snipe-IT derives it automatically from the predicted GKE service URL, but a custom domain added after deploy needs APP_URL updated via environment_variables).

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

Inspect the workload — deployment, pods, and persistent volume claims:

kubectl get deploy,pods,pvc -n "$NAMESPACE"
kubectl describe deploy -n "$NAMESPACE"

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). min_instance_count and max_instance_count both default to 1; scaling beyond one replica without verified shared-NFS/session-driver behaviour risks split sessions and lock contention. Session affinity (ClientIP) is set by default so a client's requests reach the same pod.
Update the application version by changing the version input in the RAD platform and applying it via Update; a new image is pulled and a rolling update replaces the pods. Pin application_version to a specific snipe/snipe-it release tag in production rather than tracking v8-latest.
Manage secrets, storage, and jobs:
```
kubectl get secrets -n "$NAMESPACE"
gcloud secrets list --project="$PROJECT" --filter="name~snipeit"
kubectl get jobs -n "$NAMESPACE"          # db-init and migrate
```
Never rotate the APP_KEY secret after first boot — it invalidates every active session and any application data Snipe-IT encrypted with the old key.

Open a database session for inspection or maintenance:

INSTANCE=$(gcloud sql instances list --project="$PROJECT" --format="value(name)" --limit=1)
# Role and database are tenant-prefixed (e.g. snipeitdemo426161cf) — not the bare app name.
DB_USER=$(gcloud sql users list --instance="$INSTANCE" --project="$PROJECT" \
  --format="value(name)" --filter="name~^snipeit" --limit=1)
DB_NAME=$(gcloud sql databases list --instance="$INSTANCE" --project="$PROJECT" \
  --format="value(name)" --filter="name~^snipeit" --limit=1)
gcloud sql connect "$INSTANCE" --user="$DB_USER" --database="$DB_NAME" --project="$PROJECT"

Task 4 — Observe: Logging & Monitoring [Manual]

Logs — from kubectl or the Logs Explorer:
```
kubectl logs -n "$NAMESPACE" deploy/"$(kubectl get deploy -n "$NAMESPACE" -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. uptime_check_config is disabled by default for this module — enable it in the deployment inputs if you want a provisioned uptime check and check-failure alert under Monitoring → Uptime checks / 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 Snipe-IT releases.

Pod not Ready / CrashLoopBackOff: inspect events and logs. The startup probe is TCP on the container port (30 s initial delay, ~5-minute failure window) to allow first-boot DB setup; the liveness probe is HTTP GET / (300 s initial delay) — a connection failure to MySQL will keep the pod from becoming Ready.
```
kubectl describe pod -n "$NAMESPACE" <pod>          # Events section shows scheduling/probe/mount errors
kubectl logs -n "$NAMESPACE" <pod> --previous       # logs from the crashed container
```
Database connection errors: confirm the Cloud SQL instance is RUNNABLE. This variant reaches Cloud SQL via the Auth Proxy sidecar on 127.0.0.1:3306 (enable_cloudsql_volume = true); confirm the sidecar container is running alongside the app container in the pod.

Initialisation job failed: inspect the job and its pod logs for either job in the chain (db-init runs first, then migrate):

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

/setup wizard loops or 404s: almost always an APP_URL mismatch — confirm the injected APP_URL matches the host you're browsing to.
Uploads/asset images disappear after a restart: confirm enable_nfs = true, network_tags still includes nfsserver, and the Filestore instance is reachable — removing the tag while NFS is enabled breaks pod-to-Filestore connectivity.
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 (including the critical rule never to rotate APP_KEY after first boot, and the upload_max_filesize ≤ post_max_size / min_instance_count ≤ max_instance_count plan-time guards).

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 (from the same Delete dialog) — it removes the deployment from RAD's records without destroying the cloud resources (it makes RAD forget the deployment). This removes everything the module created — the Kubernetes workload and namespace, Cloud SQL database, Filestore (NFS) instance, 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), NFS, secrets, storage bucket, and runs `db-init` → `migrate`
2 — Access & verify	Manual	Connect to the cluster; health check passes; complete the `/setup` wizard to create the first administrator account
3 — Operate	Manual	Inspect workload, scale, update version, manage secrets/storage, DB access
4 — Observe	Manual	Query Cloud Logging; review Cloud Monitoring metrics and (optional) uptime check
5 — Troubleshoot	Manual	Diagnose pod, database, init-job, `/setup`, and NFS/scheduling issues
6 — Tear down	Automated	Delete (Trash) removes all module resources

Need RAD to do something it does not do yet? Request it on the roadmap, or vote on what is already there.

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​