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Prerequisites

  • Google Cloud CLI (gcloud), authenticated with gcloud auth login.
  • A GCP project with billing enabled and permissions to create GKE clusters, node pools, and firewall rules.
  • kubectl, helm, and base64 on the machine that runs the installer.
  • At least 3 worker nodes with 4 CPU and 16 GB of memory each.
  • Outbound access from the cluster to pull images: registry.falkordb.cloud (Enterprise images, credentials required), docker.io, apecloud-registry.cn-zhangjiakou.cr.aliyuncs.com, registry.k8s.io, and ghcr.io — or registry.falkordb.cloud alone, since every image is also mirrored there (see Private registries).
Select the project and enable the required API:

Required infrastructure

A production GKE install needs: Set common variables used by the commands below:

1. Create the GKE cluster

Create a regional Standard cluster with a small system node pool:
Notes:
  • --release-channel regular pins the cluster to a supported, tested Kubernetes version.
  • The Compute Engine persistent disk CSI driver and VolumeSnapshot support ship enabled by default on current GKE versions.

2. Create a node pool for databases

Size this pool for your FalkorDB memory footprint. Memory-optimized n2-highmem machines are a good fit for graph workloads.

3. Get cluster credentials

4. Verify storage and snapshot support

FalkorDB Enterprise uses persistent volumes for databases and the Admin Server, and volume snapshots for backups. Verify GKE defaults:
GKE ships the standard-rwo (balanced persistent disk) and premium-rwo (SSD persistent disk) storage classes, with standard-rwo marked default. Use premium-rwo for database volumes in production. If the volumesnapshots CRD already exists and a snapshot controller is active, skip the installer’s bundled one with --skip-snapshot-controller. Otherwise leave the default enabled.

Install FalkorDB Enterprise

Quick install

With the GKE context active, run the installer:
The installer keeps the Admin UI inside the Kubernetes cluster and prints the kubectl port-forward command to reach it, along with how to read the generated admin password. For an evaluation, --quick-access on a first install instead exposes the Admin UI and Admin Server API on the ingress controller’s address over plain HTTP. It uses the cluster’s default IngressClass, an IngressClass named nginx, or the only IngressClass in the cluster, in that order, and installs ingress-nginx only when none of these exists. The installer does not manage an ingress controller it did not install. The address is public only if that controller provides a public external address; an internal controller gives an internal one. See Quickstart for what the installer does and how to validate it.

Production install

For production, prepare a values file with TLS ingress, a stable JWT secret, and a bootstrap admin user as described in Production install. A ready-to-edit GKE example ships inside the chart at examples/values-gke.yaml — extract it with helm registry login registry.falkordb.cloud --username '<username>' (it prompts for your access token), then helm pull oci://registry.falkordb.cloud/falkordb/falkordb-enterprise --untar. Example GKE-specific values:
These values use className: nginx, so the cluster needs the ingress-nginx controller. The installer installs it only for --quick-access, so install it yourself first:
Then install:

DNS

Point your Admin UI hostname at the ingress public IP:
Create an A record for admin.example.com pointing at the ADDRESS shown, either in your DNS provider or in Cloud DNS:

Validate the install

With the production values file, open the Admin UI hostname. After a default install there is no Ingress: use the kubectl port-forward command the installer printed. Sign in with the bootstrap admin user; Open the Admin UI shows how to read its generated password. For OAuth sign-in, see Google OAuth setup.

Pod security admission

The installer labels falkordb-system with enforce=baseline. baseline is also enough for kb-system and for database namespaces. See Pod Security Admission levels for the measured level of each namespace and the workloads that cap it.

Clean up

Delete the Enterprise release first (see uninstall), then remove the GKE cluster:
Deleting the cluster removes its node pools, disks, and load balancers.