Azure Kubernetes Fleet Manager with Arc-enabled Kubernetes clusters (preview)

This article provides a conceptual overview of how Azure Kubernetes Fleet Manager integrates with Azure Arc-enabled Kubernetes clusters to enable unified multi-cluster management across hybrid and multicloud environments.

If you're unfamiliar with Azure Kubernetes Fleet Manager, start with the Azure Kubernetes Fleet Manager overview.

What does the integration solve?

The integration between Azure Kubernetes Fleet Manager and Azure Arc-enabled Kubernetes clusters extends centralized multi-cluster resource management beyond Azure-native AKS clusters, including many of the most popular Kubernetes distributions running anywhere:

• Supported distributions: EKS (Amazon Elastic Kubernetes Service), K3s (Lightweight Kubernetes), OCP (Red Hat OpenShift), and Rancher (RKE).

Key benefits and capabilities

Azure Kubernetes Fleet Manager integration with Arc-enabled Kubernetes clusters enables unified, intelligent, policy-driven multi-cluster resource management across hybrid and multicloud environments.

Centralized policy-driven fleet governance

Azure Kubernetes Fleet Manager utilizes a hub-spoke architecture that creates a single control plane for the fleet. It allows fleet administrators to apply uniform cloud native policies on every member cluster, whether they reside in public clouds, private data centers, or edge locations. The hub-spoke architecture greatly simplifies governance across large, geographically distributed fleets spanning hybrid and multicloud environments.

Progressive Rollouts with Safeguards

Azure Kubernetes Fleet Manager provides a cloud native progressive rollout plans sequence updates across the entire fleet with health verification at each step. The application owner can stop a rollout or rollback to any previous versions when they observe failures, limiting blast radius. Progressive rollouts keep multi-cluster application deployments reliable and predictable spanning edge, on-premises, and cloud environments.

Powerful Multi-Cluster Scheduling

Azure Kubernetes Fleet Manager scheduler evaluates member cluster properties, available capacity, and declarative placement policies to select optimal destinations for workloads. It supports cluster affinity and anti-affinity rules, topology spread constraints to distribute workloads across failure domains, and resource-based placement to ensure sufficient compute, memory, and storage. The scheduler continuously reconciles as fleet conditions change, automatically adapting to cluster additions, removals, or capacity shifts across edge, on-premises, and cloud environments. For more details on the various scheduling capabilities see the multi-cluster workload management section.

Supported capabilities, prerequisites, and considerations

Before integrating Arc-enabled Kubernetes clusters with Fleet Manager, review these important considerations noted within the member cluster types documentation.

Architecture overview

The Fleet Manager and Azure Arc integration uses the same hub-and-spoke architecture as AKS clusters:

When you join an Arc-enabled Kubernetes cluster to a Fleet Manager, the Fleet Manager Arc extension is installed on your Arc-Enabled Kubernetes cluster, deploying the Fleet's member agents onto your underlying cluster. These agents communicate directly with the Fleet's hub cluster.

Key components:

• Hub cluster: Centralized control plane for managing the entire fleet.
• Fleet extension: Deployed to Arc-enabled clusters to enable Fleet Manager integration via the Fleet Arc Extension.
• Member cluster representation: Arc-enabled clusters appear as MemberCluster resources in the hub.

Getting started

To begin using Fleet Manager with Arc-enabled Kubernetes clusters:

1. Connect clusters to Azure Arc: Connect your Kubernetes clusters to Azure Arc. For instructions, see Connect an existing Kubernetes cluster to Azure Arc.
2. Create or upgrade your fleet: Create (or upgrade) a fleet resource with a hub cluster, then join your Arc-enabled clusters. For instructions, see Create a fleet and join member clusters.
3. Configure workload placement: Create ClusterResourcePlacement resources for your applications. For guidance, see Kubernetes resource propagation concepts.