Azimutt on GKE Autopilot

Azimutt is an open-source, next-generation database-schema explorer and ERD (entity relationship diagram) tool for real-world databases, built with Elixir/Phoenix. It lets teams explore, document, and design large schemas (thousands of tables), search across columns and relations, and share diagrams. This module deploys Azimutt on GKE Autopilot on top of the App_GKE foundation, which provisions and manages the shared Google Cloud and Kubernetes infrastructure.

This guide focuses on the cloud services Azimutt uses and how to explore and operate them from the Google Cloud Console and the command line. For the mechanics that are common to every GKE application — Workload Identity, ingress, autoscaling, CI/CD, Cloud Armor, IAP, Binary Authorization, VPC Service Controls, backups, and the deployment lifecycle — refer to the App_GKE foundation guide rather than repeating them here.

1. Overview

Azimutt runs as a single Elixir/Phoenix web workload listening on port 4000. The deployment wires together a focused set of Google Cloud services:

Capability	Google Cloud service	Notes
Compute	GKE Autopilot	Phoenix pods, horizontally autoscaled; bills for requested CPU/memory
Database	Cloud SQL for PostgreSQL 15	Required — Azimutt does not support MySQL or other engines
File storage	Cloud Filestore (NFS)	`enable_nfs = true` by default — Azimutt attachment storage survives pod restarts
Object storage	Cloud Storage	A bucket is provisioned (available for an S3-compatible file adapter)
Secrets	Secret Manager	Auto-generated Phoenix `SECRET_KEY_BASE`; database password
Image build	Cloud Build + Artifact Registry	Thin wrapper FROM `ghcr.io/azimuttapp/azimutt`, mirrored into Artifact Registry
Ingress	Cloud Load Balancing	External LoadBalancer, optional custom domain + managed certificate

Sensible defaults worth knowing up front:

PostgreSQL 15 is mandatory. The database engine is fixed by the shared application layer; selecting any other engine breaks startup. All Azimutt project data lives in Postgres.
Azimutt connects to Postgres over the Auth Proxy loopback (no SSL). Ecto cannot parse the Cloud SQL socket DSN, so on GKE the entrypoint builds DATABASE_URL against 127.0.0.1 (the Cloud SQL Auth Proxy sidecar, which terminates TLS) with DATABASE_ENABLE_SSL=false. enable_cloudsql_volume = true is required.
container_port and probes must be 4000. On GKE the platform does not auto-inject PORT, so the entrypoint defaults PORT=4000; the Service port and probes must match or the pod never becomes Ready even though the app is healthy.
NFS is enabled by default (enable_nfs = true) for Azimutt attachment storage, so uploads survive pod restarts and rescheduling.
SECRET_KEY_BASE is generated automatically and stored in Secret Manager. Rotating it after first boot signs out every active session; only rotate in a maintenance window.
Minimum 1 replica is maintained (min_instance_count = 1) — GKE does not support scale-to-zero, keeping Azimutt always reachable.
Migrations run automatically on every boot (/app/bin/migrate && /app/bin/server); allow extra time on the first boot.
application_version = "latest" maps to Azimutt's main tag. Pin to a specific release in production.
Sign-up is open by default. Restrict access after creating your first account.

2. Google Cloud Services & How to Explore Them

All commands assume you have run gcloud container clusters get-credentials <cluster> --region <region> --project <project> and that PROJECT, REGION, and NAMESPACE are set. The namespace and other identifiers are reported in the deployment Outputs.

A. GKE Autopilot — the Azimutt workload

Azimutt pods are scheduled on Autopilot, which bills for the CPU/memory the pods actually request. Horizontal Pod Autoscaling sizes the deployment between the minimum and maximum replica counts.

Console: Kubernetes Engine → Workloads → select the Azimutt workload to see pods, revisions, and events. Kubernetes Engine → Services & Ingress shows the external IP.

CLI:

kubectl get pods,svc,hpa -n "$NAMESPACE"
kubectl logs -n "$NAMESPACE" deploy/<service-name> --tail=100
kubectl logs -n "$NAMESPACE" deploy/<service-name> | grep cloud-entrypoint  # resolved DB wiring

See App_GKE for how Autopilot, scaling, and the workload type (Deployment vs StatefulSet) are managed.

B. Cloud SQL for PostgreSQL 15

Azimutt stores all application data (schemas, diagrams, layouts, users, sources) in a managed Cloud SQL for PostgreSQL 15 instance. Pods reach it through the Cloud SQL Auth Proxy sidecar on 127.0.0.1 (TLS terminated by the proxy, so DATABASE_ENABLE_SSL=false). On first deploy an initialization Job creates the application database and role; Azimutt then runs its own Ecto migrations on boot.

Console: SQL → select the instance for connections, backups, flags, metrics.

CLI:

gcloud sql instances list --project "$PROJECT"
gcloud sql instances describe <instance-name> --project "$PROJECT"
gcloud sql connect <instance-name> --user=<db-user> --database=<db-name> --project "$PROJECT"

The instance name, database, user, and password secret are all surfaced in the Outputs. For the connection model, backups, and password rotation, see App_GKE.

C. Cloud Filestore (NFS) & Cloud Storage

NFS is enabled by default (enable_nfs = true) so Azimutt's attachment storage persists across pod restarts and rescheduling; it is mounted at nfs_mount_path. A Cloud Storage bucket is also provisioned (available if you switch Azimutt to an S3-compatible file adapter). Project data itself lives in Postgres.

Console: Filestore → Instances; Cloud Storage → Buckets.

CLI:

gcloud filestore instances list --project "$PROJECT"
gcloud storage buckets list --project "$PROJECT"
kubectl get pvc -n "$NAMESPACE"

See App_GKE for NFS provisioning, CMEK options, and GCS Fuse mounts.

D. Secret Manager

The Phoenix SECRET_KEY_BASE is generated automatically and stored in Secret Manager (used to sign and encrypt session cookies). The database password is managed separately by the foundation.

Console: Security → Secret Manager.

CLI:

gcloud secrets list --project "$PROJECT" --filter="name~secret-key-base"
gcloud secrets versions access latest --secret=<secret-name> --project "$PROJECT"

See App_GKE for the Secret Store CSI integration and rotation.

E. Cloud Build & Artifact Registry

Azimutt's image is a thin wrapper built FROM ghcr.io/azimuttapp/azimutt; Cloud Build produces the wrapped image and it is mirrored into Artifact Registry (enable_image_mirroring = true). Because it is a rebuilt/mirrored image, App_GKE sets imagePullPolicy = Always so nodes never serve a stale cached layer.

Console: Cloud Build → History; Artifact Registry → Repositories.

CLI:

gcloud builds list --project "$PROJECT" --limit 5
gcloud artifacts docker images list <region>-docker.pkg.dev/$PROJECT/<repo> --include-tags

F. Networking & ingress

By default the workload is exposed through an external Cloud Load Balancing IP (service_type = LoadBalancer). A custom domain with a Google-managed certificate can be enabled, and a static IP can be reserved so the address survives redeploys. session_affinity = ClientIP keeps a client pinned to one pod.

Console: Network services → Load balancing; VPC network → IP addresses.

CLI:

kubectl get ingress,svc -n "$NAMESPACE"
gcloud compute addresses list --project "$PROJECT"

See App_GKE for custom domains, Cloud CDN, and static IP details.

G. Cloud Logging & Monitoring

Pod stdout/stderr flow to Cloud Logging; GKE and Cloud SQL metrics flow to Cloud Monitoring. Optional uptime checks and alert policies are available. The cloud-entrypoint lines show the resolved DATABASE_URL path, PHX_HOST, and PORT.

Console: Logging → Logs Explorer; Monitoring → Dashboards / Alerting.

CLI:

gcloud logging read 'resource.type="k8s_container" AND resource.labels.namespace_name="'"$NAMESPACE"'"' \
  --project "$PROJECT" --limit 50

3. Azimutt Application Behaviour

First-deploy database setup. An initialization Job runs db-init.sh using postgres:15-alpine. It idempotently creates the application role (LOGIN CREATEDB) and database, grants ALL on the database and the public schema, and ALTERs the schema owner — Azimutt needs full DDL rights because it runs its own migrations. The job then signals the Auth Proxy sidecar to shut down (/quitquitquit) so the Job pod completes. Safe to re-run.
Migrations run on start. The container command is /app/bin/migrate && /app/bin/server, so Ecto applies pending migrations on every boot before the Phoenix endpoint binds. Upgrading application_version applies schema changes automatically.
Runtime DB wiring is composed by the entrypoint. On GKE DATABASE_URL is built against the Auth Proxy loopback (127.0.0.1) with DATABASE_ENABLE_SSL=false, and PORT is defaulted to 4000 (GKE does not auto-inject it). PHX_HOST is derived from the injected service URL.
SECRET_KEY_BASE is stable and effectively immutable. Rotating it invalidates every active session cookie — all users are signed out. Only rotate in a maintenance window.
Health path. The startup and liveness probes target the Phoenix root / with a 60-second initial delay. The probes and container_port must both be 4000 or the pod never becomes Ready.
First-run setup. Reach the service via its external LoadBalancer IP (or custom domain) and create the first Azimutt account through the sign-up page. Sign-up is open by default — restrict access afterwards.

Inspect the init job execution:

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

4. Configuration Variables

Variables are grouped exactly as they appear on the deployment platform. Only settings specific to or notable for Azimutt are listed; every other input is inherited from App_GKE with its standard behaviour and defaults.