Koordinator

Koordinator is an open-source workload scheduling and resource management project for Kubernetes clusters that optimizes mixed workloads and resource utilization across nodes.

• Hybrid workload-aware scheduling and descheduling for Kubernetes clusters (container orchestration)
• Fine-grained Central Processing Unit (CPU), memory, and NUMA-aware resource management to improve node utilization (infrastructure resource management)
• Quality of Service (QoS) based scheduling for batch, online, and latency-sensitive workloads (workload management)
• Plugins and extensions that integrate with native Kubernetes schedulers and CRDs (platform extensibility)
• Support for multi-tenant environments with workload isolation and prioritization policies (multi-tenancy management)

More About Koordinator

Koordinator is an open-source project under the Cloud Native Computing Foundation (CNCF) that focuses on scheduling and resource management for Kubernetes (container orchestration). It targets clusters that run mixed types of workloads, such as online services, batch jobs, and latency-sensitive applications, and aims to improve overall resource utilization without rewriting applications. Koordinator works with existing Kubernetes constructs and enhances how compute resources are allocated, isolated, and coordinated across nodes.

The project introduces workload-aware scheduling capabilities (workload management) by extending Kubernetes with custom resource definitions (CRDs) and scheduler plugins. It can classify workloads by priority and QoS requirements and place them on nodes based on resource availability and policies. This includes mechanisms for co-locating online and batch workloads while attempting to avoid resource contention. Koordinator integrates with the native Kubernetes scheduler and can run as an add-on component in existing clusters.

At the node level, Koordinator provides fine-grained resource control (infrastructure resource management), including CPU binding, memory management, and NUMA-aware placement where supported. It uses Linux cgroup features and related kernel mechanisms, exposed through Kubernetes, to control CPU shares, CPU sets, and memory limits. This allows enterprises to configure resource pools, reserve capacity for high-priority workloads, and allocate burst capacity to lower-priority jobs when spare resources exist. The system can also perform descheduling or rescheduling when cluster conditions change.

In multi-tenant or shared clusters (multi-tenancy management), Koordinator offers policies for workload isolation and prioritization. Administrators can define profiles and strategies that govern how different tenants or workload classes share nodes, including protections for critical services. By leveraging CRDs, configuration is declarative and can be managed via standard Kubernetes workflows and GitOps pipelines.

Enterprises use Koordinator alongside Kubernetes distributions and cloud-managed Kubernetes services (platform integration). It fits in the category of cluster-level resource optimization and workload orchestration, complementing monitoring and autoscaling tools. Koordinator’s extensible architecture (platform extensibility) allows integration with observability systems that provide metrics about resource pressure and workload performance, which can inform scheduling decisions. Its role in the ecosystem is to enhance the default Kubernetes scheduling and resource management behavior for heterogeneous workloads in production environments.