Karmada is a Kubernetes management system that enables you to run your cloud-native applications across multiple Kubernetes clusters and clouds, with no changes to your applications.
Karmada solves the problem of orchestrating workloads across multiple Kubernetes clusters and cloud providers by providing a centralized control plane that speaks Kubernetes-native APIs. It works through a control plane consisting of an API server, controller manager, and scheduler that manage the lifecycle of attached clusters and propagate resources to them. The system uses a policy-driven approach where PropagationPolicy objects define how resources should be distributed, and a series of controllers handle cluster attachment, resource selection, binding creation, and execution across member clusters.
Organizations managing applications across multiple clouds or on-premises infrastructure should consider Karmada if they want to avoid vendor lock-in and maintain a consistent Kubernetes experience without rewriting applications. The tool suits hybrid cloud and multi-cloud scenarios where centralized management, automatic failover, cross-cluster load balancing, and multi-dimensional high availability across regions, availability zones, and clusters are required. Built-in policy sets address common patterns including active-active deployments, remote disaster recovery, and geo-redundant configurations. Karmada integrates with mainstream cloud providers and supports clusters in public clouds, on-premises environments, and edge locations.
The project maintains active development across its core components with regular updates to the control plane architecture and scheduling capabilities. The codebase shows ongoing refinement of the policy and binding controllers that form the foundation of resource distribution. Work continues on expanding cluster management features and the execution layer that delivers resources to member clusters. The project benefits from contributions across multiple organizations and maintains focus on the multi-cluster scheduling and orchestration capabilities that differentiate it from single-cluster Kubernetes management.
