Kubernetes
Coming from another cloud?
▸AWS·Amazon EKS Cluster
Amazon EKS Cluster
- EKS control plane fully AWS-managed, single-tenant, across 3 AZs with auto scale/replace; on Quake AI you run the control plane on Nova instances, provisioned through Magnum or self-managed with OpenTofu, and you operate it.
- EKS regional API endpoint with SLA; Quake AI exposes the kube API via Neutron LB with floating IP.
- EKS charges a per-hour cluster platform fee on top of the underlying compute; Quake AI charges only for underlying Nova/Neutron/Cinder resources with no K8s platform fee.
- EKS managed nodes auto AMI updates, Spot integration; Quake AI self-managed nodes require manual OS image selection and update management.
▸Azure·AKS Cluster
AKS Cluster
- Azure automatically provisions and manages the control plane at no additional cost (Free tier) or fixed fee (Standard tier with SLA), offloading health monitoring and upgrades; on Quake AI you provision a cluster through Magnum (openstack coe cluster create) or self-managed Kubernetes on Nova instances (OpenTofu plus kubeadm, k3s, or RKE2), and you operate the cluster after creation.
- No OpenStack integration; uses Azure Resource Manager for cluster lifecycle.
- Pre-configured with Azure-specific defaults and add-ons like application routing.
- Managed via Azure Virtual Machine Scale Sets (VMSS) with auto-scaling and upgrades; Quake AI uses Nova instances provisioned via OpenTofu with user-managed scaling and upgrades.
▸DigitalOcean·Doks
This Quake AI feature maps to DigitalOcean’s Doks.
▸Google Cloud·GKE Cluster
GKE Cluster
- GKE provides Autopilot mode with fully managed node provisioning and scaling by Google; on Quake AI you provision clusters through Magnum or self-managed Kubernetes on Nova instances and manage node scaling yourself.
- Control plane is fully managed with automatic upgrades through release channels; Quake AI requires user-provisioned and user-managed control plane nodes.
- Cluster creation uses gcloud CLI vs OpenStack CLI (openstack coe cluster create).
- Custom machine types, spot VMs, accelerators in node pools; Quake AI K8s nodes use standard Nova flavors.
▸Hetzner·Kubernetes
This Quake AI feature maps to Hetzner’s Kubernetes.
Kubernetes
The Kubernetes service automates cluster provisioning on Quake AI. You define the node sizes, network driver, and Kubernetes version through a reusable template, and the platform provisions master nodes, worker nodes, and the networking between them using existing Compute, Network, and Storage infrastructure.
OpenStack Magnum backs Kubernetes. For details on how Quake AI implements OpenStack, see How Quake AI uses OpenStack.
What you can do#
Create a Kubernetes cluster
Deploy a production-ready Kubernetes cluster with master and worker nodes from a cluster template.
Define a cluster template
Create a reusable blueprint that specifies Kubernetes version, node flavors, network settings, and scaling policies.
Scale and manage clusters
Add or remove worker nodes, update configurations, and manage the lifecycle of running clusters.
How it works#
A cluster template defines the blueprint: which Kubernetes version to run, the compute flavor for master and worker nodes, the network driver, volume driver for persistent storage, and optional settings like auto-scaling and TLS. You create the template once and reuse it for multiple clusters.
When you create a cluster from a template, the platform provisions the underlying infrastructure: master VMs running the Kubernetes API server, scheduler, and controller manager; worker VMs running the kubelet and container runtime; and the networking that connects them. The cluster integrates with Quake AI's Compute service for VM provisioning, Network service for pod and service networking, and Storage service for persistent volumes.
Once the cluster is running, you interact with it through standard Kubernetes tools. Use kubectl to deploy workloads, manage pods, and configure services. The Quake AI console, CLI, and API handle cluster-level operations: scaling the node pool, upgrading Kubernetes versions, and deleting clusters when no longer needed.
Get started#
To deploy your first cluster, start with Create a cluster template, then Create a Kubernetes cluster.
Key concepts#
Concepts
- Cloud-native Computing on Quake AI: Traditional application deployment is straightforward: install software on a server, configure it, run it. That model works until you need to scale to multiple instances, deploy updates without...
- Kubernetes on Quake AI: The Quake AI Kubernetes service (OpenStack Magnum) automates cluster provisioning on top of existing Compute, Network, and Storage infrastructure. You define the cluster shape through a reusable...
Security considerations#
Cluster security starts with the cluster template: it defines the network driver, TLS settings, and node image. Beyond that, harden workloads with Kubernetes-native controls: RBAC for API access, network policies for pod-to-pod traffic, and secrets management for credentials. The underlying VMs inherit compute and network security from the platform. See Security for cross-service security documentation.
Guides and reference#
Console guides#
How-to guides#
- How to Create a Cluster Template: Create a cluster template that defines the blueprint for Kubernetes clusters: Kubernetes version, node flavor, network driver, volume driver, and the label set that drives boot volume sizing...
- How to Create a Kubernetes Cluster: Deploy a Kubernetes cluster with master and worker nodes from an existing cluster template. The Kubernetes service provisions the VMs, networking, and stable control-plane endpoints, giving you a...
- How to Deploy a Helm Chart on a Kubernetes Cluster: Install the Helm CLI, point it at a Quake AI Kubernetes cluster (OpenStack Magnum), and deploy a chart with a values file. This guide covers adding a chart repository, running helm upgrade --install...
- How to Deploy to a Quake AI Kubernetes Cluster from Ci: Apply manifests or Helm releases from GitHub Actions or GitLab CI to a Magnum cluster. Fetch a fresh kubeconfig at job start with application credentials. Do not commit kubeconfig files to the...
- How to Manage a Kubernetes Cluster: Scale worker nodes, view cluster status, retrieve the kubeconfig for kubectl access, and delete clusters when no longer needed. The Clusters list page exposes a filter input on the far right of the...
- How to Use a Container Registry with Quake AI: Pull private container images into Quake AI workloads from a third-party registry. Quake AI does not run a managed container registry. Push images to GitHub Container Registry (GHCR), GitLab Container...
CLI reference#
API reference#
Related services#
Kubernetes clusters run on Compute instances and use Network for pod connectivity and floating IPs. Kubernetes Services with type: LoadBalancer receive public endpoints through the cluster's cloud controller. Storage block volumes back the persistent volumes attached to Kubernetes pods. For infrastructure-as-code cluster provisioning, see Automation.
Quick answers
- Why does `openstack coe cluster create` fail with a Keystone trust or unauthorized error when I use an application credential?CLIAPITerraform
- Why does a Kubernetes LoadBalancer service stay `<pending>` for several minutes?CLI
- Why does my GitHub Actions or GitLab CI job fail to run `openstack coe` or `kubectl` on a Magnum cluster?CLI
- Why does my Magnum cluster create fail with "Only volume-backed servers" or "Quota exceeded for compute_units"?CLIAPI