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Clusters Console

Reference · Updated Sep 2026

Coming from another cloud?

▸AWS·Amazon EKS Cluster

Amazon EKS Clusterhigh

  • 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.
AWS docs ↗
▸Azure·AKS Cluster

AKS Clusterhigh

  • 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.
Azure docs ↗
▸DigitalOcean·Doks

This Quake AI feature maps to DigitalOcean’s Doks.

▸Google Cloud·GKE Cluster

GKE Clusterhigh

  • 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.
Google Cloud docs ↗
▸Hetzner·Kubernetes

This Quake AI feature maps to Hetzner’s Kubernetes.

Clusters console

The Clusters page lets you deploy, inspect, scale, and delete Kubernetes clusters. Select Services > Kubernetes > Clusters (/container-infra/clusters) to access this page.

Cluster list#

The list view shows all clusters in the current project with the following columns:

ColumnDescription
NameHuman-readable cluster name. Select the name to open cluster details.
IDUnique identifier assigned to the cluster.
StatusCurrent operational state (e.g., CREATE_COMPLETE, UPDATE_IN_PROGRESS).
Health StatusContinuous health assessment based on node and control plane checks.
Node CountNumber of worker nodes.
Master CountNumber of master nodes.
Cluster TemplateThe template used to create this cluster.
CreatedTimestamp of cluster creation.

Use the controls at the top of the list to create a new cluster or delete selected clusters.

Kubernetes Clusters console showing an empty list with the column headers and action controls visibleClick to zoom
Clusters list (empty state; a subset of columns renders until clusters exist)

The empty-state view shows a subset of column headers. Once a cluster exists, the populated list renders the full eight columns documented above (Name, ID, Status, Health Status, Node Count, Master Count, Cluster Template, Created).

Cluster details#

Select a cluster name to view its detail page. The detail view displays:

FieldDescription
NameCluster name.
IDUnique cluster identifier.
StatusCurrent state with status reason (provides detail for failures).
Health StatusCluster health based on node monitoring.
Cluster Template IDID of the template this cluster was created from.
API AddressURL of the Kubernetes API endpoint. Use this with kubectl to manage workloads.
Master CountNumber of master nodes.
Node CountCurrent number of worker nodes.
Master FlavorHardware profile of master nodes (CPU, RAM, disk).
Node FlavorHardware profile of worker nodes.
Key PairSSH key pair associated with cluster nodes.
Discovery URLURL used for node discovery during initial cluster setup.
LabelsKey-value pairs controlling cluster configuration (network policies, autoscaler, dashboard).
FaultsError information for failed operations. Useful for diagnosing creation or update failures.
CreatedCluster creation timestamp.
UpdatedLast modification timestamp.

Cluster status values#

StatusMeaning
CREATE_IN_PROGRESSCluster VMs, networking, and control-plane endpoints are being provisioned.
CREATE_COMPLETECluster is ready. The Kubernetes API is accessible.
CREATE_FAILEDProvisioning failed. Check Faults and Status Reason for details.
UPDATE_IN_PROGRESSA scaling or configuration change is being applied.
UPDATE_COMPLETECluster update finished successfully.
UPDATE_FAILEDUpdate failed. Review status reason and retry or rollback.
DELETE_IN_PROGRESSCluster and associated resources are being removed.
DELETE_COMPLETECluster and all resources have been deleted.
DELETE_FAILEDDeletion failed. Orphaned resources may need manual cleanup.

Actions#

ActionDescription
Create ClusterLaunch a new cluster from a cluster template. See How to create a Kubernetes cluster.
Resize ClusterScale the worker node count up or down. See How to manage a Kubernetes cluster.
DeleteRemove the cluster and its VMs, networks, control-plane endpoints, and Heat stack.

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