kcp-dev/kcp

Kubernetes-like control planes for form-factors and use-cases beyond Kubernetes and container workloads.

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Summary Information

Updated 8 minutes ago
Added to GitGenius on June 1st, 2026
Created on March 31st, 2021
Open Issues & Pull Requests: 151 (+0)
GitHub issues: Enabled
Number of forks: 459
Total Stargazers: 2,818 (+0)
Total Subscribers: 33 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 17.0 hours
Mean response time: 21.4 days
90th percentile: 41.8 days
Tracked items: 345

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 68% of open issues come from outside the core team, a mix of external reports and the maintainers' own roadmap. Work labelled "kind/bug" is answered fastest, typically in about 10 hours, while "kind/feature" waits about 4 days. 51% of tracked open issues have had no activity in three months. Only 4% of issues opened in the past year have been closed.

Charts & Analytics

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Issue Activity (beta)

Open issues: 84
New in 7 days: 4
Closed in 7 days: 1
Avg open age: 176 days
Stale 30+ days: 64
Stale 90+ days: 48

Recent activity

Opened in 7 days: 3
Closed in 7 days: 1
Comments in 7 days: 4
Events in 7 days: 23

Top labels

  • kind/bug (130)
  • kind/feature (108)
  • lifecycle/rotten (82)
  • good first issue (39)
  • kind/documentation (21)
  • kind/flake (20)
  • epic (14)
  • area/apiexports (12)

Detailed Description

kcp is a Kubernetes-like control plane designed to serve use cases beyond traditional container orchestration. Written in Go, the project provides a multi-tenant platform architecture where a single control plane manages many independent, isolated "workspaces" rather than traditional clusters. This design enables API service providers to offer centralized APIs to large numbers of fully isolated tenants using Kubernetes-native interfaces, making it particularly valuable for SaaS platforms and enterprise IT departments that need to provide APIs within their organizations.

The core functionality centers on workspace management and API aggregation. kcp allows users to consume APIs within their isolated workspaces while operators can deploy multi-tenant implementations that serve many customers from a single control plane. The project explicitly targets scenarios where Kubernetes itself is inappropriate, focusing instead on declarative API platforms and control plane use cases that don't require container workload scheduling. This represents a significant architectural departure from standard Kubernetes, stripping away container runtime concerns to focus purely on API service delivery and resource isolation.

This decision reflects the project's refined focus on control plane and API aggregation rather than distributed workload management. Users interested in the previous architecture can reference the main-pre-tmc-removal branch.

GitGenius activity data reveals a healthy, responsive development community.

The project maintains active overlapping contributor relationships with crossplane/crossplane, kubernetes/website, and llm-d/llm-d, suggesting integration points and shared community involvement across related cloud-native projects. kcp is classified within the multi-tenancy, Kubernetes API, virtual clusters, workspace management, control plane, cluster federation, resource isolation, cloud-native, API aggregation, and scalability domains, reflecting its broad applicability across platform engineering scenarios.

Community engagement occurs through multiple channels including dedicated Kubernetes Slack channels for users and developers, Google Groups mailing lists, bi-weekly community meetings with recorded sessions on YouTube, and shared documentation via Google Drive. The project maintains comprehensive documentation at docs.kcp.io and provides getting started guides for both users and developers. Multiple conference presentations from KubeCon, ContainerDays, and other venues demonstrate the project's visibility and adoption within the cloud-native ecosystem, with recent talks addressing platform engineering applications and comparisons of kcp with Kubernetes for control plane scenarios.