Mixpost on GKE Autopilot — Lab Guide

Overview

Estimated time: 45–90 minutes

Mixpost is an open-source, self-hosted social media scheduling and management platform — a Buffer/Hootsuite alternative for composing, scheduling, publishing, and analysing posts across multiple social accounts from one dashboard. This lab takes you through the full operational lifecycle of the Mixpost 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 Mixpost 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.
Understand why this variant keeps at least one pod always running, and what that means for scheduled post publishing.
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, NFS/Redis host, 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 Mixpost (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 (the prebuilt inovector/mixpost image — no custom build), provisions a Cloud SQL (MySQL 8.0) database with its Secret Manager secrets (the Laravel APP_KEY and the database password), a Cloud Storage bucket, mirrors the prebuilt image into Artifact Registry, and runs a one-shot db-init job that creates the application database and user via the Cloud SQL Auth Proxy sidecar. First deploys take roughly 15–30 minutes (Cloud SQL creation dominates).

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 mixpost | 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"
```
The pod-level startup and liveness probes are both TCP on port 80 (Mixpost answers / with a 302 redirect that an HTTP kubelet probe would otherwise follow into a dead end at :443), so a 1/1 Running pod is the right health signal here rather than an HTTP probe result.

Confirm the service responds:

curl -s -o /dev/null -w "%{http_code}\n" "http://${EXTERNAL_IP}/"   # expect 200 or 302

Open http://${EXTERNAL_IP} in a browser and sign in. Mixpost's admin account is seeded by the image itself and is not configurable through this module — the mixpost_admin_email input is declared but not currently injected into the running container. Use the image's documented default first-login credentials (admin@example.com / changeme) and change the password immediately after first login.

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

Inspect the workload — deployment, pods, and PVCs:

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). Session affinity (ClientIP) is set by default to keep a client routed to the same pod. Because the workload is NFS-backed, updates roll out with the Recreate strategy (the old pod is terminated before the new one starts) to avoid two pods deadlocking on the shared NFS volume and database.
Understand why this variant defaults to always-on. Unlike the Cloud Run variant's cold-start default, this module keeps min_instance_count = 1 — at least one pod is always running, so the supervisord-managed Laravel scheduler and queue worker publish scheduled social posts without any external Cloud Scheduler wiring. Scaling this to 0 stops scheduled publishing entirely; do not do so if scheduled posting is in use.
Update the application version by changing the version input in the RAD platform and applying it via Update; a new image is pulled and the pod is recreated — there is no separate migration job, since the image runs php artisan migrate --force on every boot.

Manage secrets, storage, and jobs:

kubectl get secrets -n "$NS"
gcloud secrets list --project="$PROJECT" --filter="name~mixpost"
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 "$INSTANCE" --user=mixpost --project="$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. 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 Mixpost releases.

Pod not Ready / restart loop despite the app serving fine on :80: confirm startup_probe_config / health_check_config are still type = "TCP" — switching them to HTTP reintroduces the 302-redirect trap (the kubelet's HTTP probe follows Mixpost's redirect to https://<pod-ip>:443, where nothing listens).
```
kubectl describe pod -n "$NS" <pod>          # Events section shows scheduling/probe/mount errors
kubectl logs -n "$NS" <pod> --previous       # logs from the crashed container
```
db-init job hangs indefinitely: confirm enable_cloudsql_volume = true (required on GKE). Disabling it makes the job's quitquitquit shutdown POST miss the not-yet-started Auth Proxy sidecar, hanging the job forever.
```
kubectl get jobs -n "$NS"
kubectl logs -n "$NS" job/<db-init-job-name>
```
Database connection errors: confirm the Cloud SQL instance is RUNNABLE and the DB password secret materialised into the namespace via the Secret Store CSI driver.
Scheduled posts not publishing: confirm min_instance_count >= 1 — scaling to 0 stops the in-pod scheduler and queue worker.
Pending pod / no external IP: check kubectl describe pod events for resource or quota issues, and confirm the LoadBalancer Service has an assigned IP (reserve_static_ip = true keeps it stable across redeploys).
Login credentials unknown / "admin account not configured": the admin account is seeded by the image itself, not by this module's mixpost_admin_email variable — use the image's documented default credentials.
Image pull errors: confirm the mirrored 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 rule never to rotate APP_KEY after first boot, and the immutability of application_database_name / application_database_user).

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, Secret Manager secrets, GCS buckets, and Artifact Registry images. Resources owned by Services_GCP (the VPC, GKE cluster, shared Cloud SQL, NFS/Redis host, 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), secrets, storage bucket, and runs `db-init` via the Auth Proxy sidecar
2 — Access & verify	Manual	Connect to the cluster; TCP probes healthy; sign in with the image's default admin credentials and change the password
3 — Operate	Manual	Inspect workload, scale, update version, confirm always-on scheduling, manage secrets/storage, DB access
4 — Observe	Manual	Query Cloud Logging; review Cloud Monitoring metrics and (optional) uptime check
5 — Troubleshoot	Manual	Diagnose pod probe, `db-init`, database, scheduling, 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​