Cal.com on GKE Autopilot — Lab Guide

Overview

Estimated time: 45–90 minutes

Cal.com is an open-source scheduling platform — the self-hosted Calendly alternative — built with Next.js and Prisma on PostgreSQL. This lab takes you through the full operational lifecycle of the Cal.com 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 Cal.com 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.
Access and verify the running workload and complete Cal.com's onboarding.
Perform day-2 operations — inspect, scale, update, and manage secrets and the database.
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, 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 Cal.com (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 (PostgreSQL 15) database with its Secret Manager secrets (auto-generated NEXTAUTH_SECRET and CALENDSO_ENCRYPTION_KEY, plus the database password), builds/mirrors the Cal.com image, and runs a one-shot db-init job that creates the empty database and role. No GCS bucket is created — Cal.com keeps all state in PostgreSQL. The job does not create the application schema; Cal.com runs prisma migrate deploy on every start, so the schema is created on the pod's first boot. First deploys take roughly 20–35 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 calcom | 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. Cal.com's health path is /, which returns HTTP 200 once the app has finished running its Prisma migrations on first boot — the schema is created on boot, not by the init job, so allow several minutes on a fresh deploy (the startup probe window is generous — up to ~15 minutes — for exactly this reason):
```
curl -s -o /dev/null -w "%{http_code}\n" "http://${EXTERNAL_IP}/"
```
Open http://${EXTERNAL_IP} in a browser and complete Cal.com's onboarding to create the initial administrator/owner account, then connect at least one calendar. Immediate hardening note: self-hosted Cal.com allows self-service sign-up by default — restrict it (or front the service with IAP) if the instance should not be public.
URL discipline: NEXT_PUBLIC_WEBAPP_URL / NEXTAUTH_URL default to the runtime cluster URL. Before sharing booking links (or once a custom domain is assigned), set webapp_url to the LoadBalancer IP or custom-domain address and apply it via Update — this URL is baked into every booking and OAuth link, so a wrong or unset value breaks them.

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

Inspect the workload — deployment, pods, and the horizontal autoscaler:
```
kubectl get deploy,pods,hpa -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). Cal.com is stateless (workload_type = Deployment); session affinity (ClientIP) is set by default to keep a client's requests on the same pod. Enabling enable_redis requires either redis_host or enable_nfs = true for the co-located NFS Redis endpoint.
Update the application version by changing the version input in the RAD platform and applying it via Update; a new image builds/mirrors and a rolling update replaces the pods, applying any pending Prisma migrations on their first boot.
Manage secrets and jobs — and know which secrets are immutable:
```
kubectl get secrets -n "$NS"
gcloud secrets list --project="$PROJECT" --filter="name~calcom"
kubectl get jobs -n "$NS"          # db-init job
```
CALENDSO_ENCRYPTION_KEY encrypts stored calendar/OAuth credentials and NEXTAUTH_SECRET signs sessions — never rotate either after first boot outside a planned maintenance window (rotation orphans every connected calendar integration or logs out every user, respectively).

Open a database session for inspection or maintenance:

INSTANCE=$(gcloud sql instances list --project="$PROJECT" --format="value(name)" --limit=1)
gcloud sql connect "$INSTANCE" --user=calcom --project="$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 against / (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 Cal.com releases.

Pod not Ready / CrashLoopBackOff: inspect events and logs first — the startup probe targets / and allows a generous window for first-boot Prisma migrations:

kubectl describe pod -n "$NS" <pod>          # Events section shows scheduling/probe/mount errors
kubectl logs -n "$NS" <pod> --previous       # logs from the crashed container

OOM crash at startup: memory_limit must be ≥ 2 GiB — Next.js 16 OOM-crashes below it and the pod never becomes Ready.
Database connection errors: confirm the Cloud SQL (PostgreSQL 15) instance is RUNNABLE, the DB password secret materialised into the namespace, and enable_cloudsql_volume = true (the Auth Proxy sidecar gives Cal.com its 127.0.0.1 PostgreSQL endpoint — disabling it with a real database is blocked by a plan-time guard).
Initialisation job failed: inspect the job and its pod logs (it only creates the empty database/role — it does not build the schema):
```
kubectl get jobs -n "$NS"
kubectl logs -n "$NS" job/<job-name>
```
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.
Wrong or broken booking/OAuth links: verify webapp_url (or the injected runtime default) resolves to the actual external address — the image's localhost:3000 default produces broken links.
403 / permission errors: verify the workload service account's IAM roles; if IAP is enabled, remember it blocks all unauthenticated requests — including public booking pages and embeds.

See the Configuration Guide's Configuration Pitfalls section for setting-specific gotchas (including the critical rule never to rotate CALENDSO_ENCRYPTION_KEY or NEXTAUTH_SECRET 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 (all users, event types, and bookings), Secret Manager secrets (including NEXTAUTH_SECRET and CALENDSO_ENCRYPTION_KEY), 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 (PostgreSQL 15), secrets, mirrors the image, and runs DB init (no GCS bucket)
2 — Access & verify	Manual	Connect to the cluster; health check passes; complete onboarding, restrict open sign-up, set `webapp_url`
3 — Operate	Manual	Inspect workload, scale, update version, respect immutable secrets, DB access
4 — Observe	Manual	Query Cloud Logging; review Cloud Monitoring metrics and uptime check
5 — Troubleshoot	Manual	Diagnose pod, OOM, database, init-job, scheduling, URL, 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​