openkruise/kruise

Automated management of large-scale applications on Kubernetes (incubating project under CNCF)

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Summary Information

Updated 17 minutes ago
Added to GitGenius on September 12th, 2026
Created on May 30th, 2019
Open Issues & Pull Requests: 88 (+0)
GitHub issues: Enabled
Number of forks: 918
Total Stargazers: 5,340 (+0)
Total Subscribers: 85 (+0)

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Detailed Description

OpenKruise is a Kubernetes operator that extends the core Kubernetes controllers to provide advanced workload and application management capabilities for large-scale deployments.

The project addresses limitations in Kubernetes' native workload controllers by introducing specialized controllers for different application types. For stateless applications, CloneSet provides in-place updates and configurable scaling strategies. For stateful workloads, Advanced StatefulSet adds similar capabilities. Advanced DaemonSet handles daemon applications, while BroadcastJob and AdvancedCronJob manage job-type workloads. Beyond workloads, the tool simplifies sidecar container management through SidecarSet, enabling in-place sidecar updates and enhanced startup and termination control. For multi-domain scenarios, WorkloadSpread and UnitedDeployment help distribute applications across node pools, availability zones, and different architectures. The project also provides operational enhancements like container recreation requests, image pre-downloading, resource distribution across namespaces, and persistent pod state management.

Adoption suits teams running large-scale Kubernetes clusters that need finer control over application lifecycle management, particularly those managing mixed workload types or operating across heterogeneous infrastructure. The tool is most valuable for organizations requiring in-place updates to minimize disruption, sophisticated deployment strategies beyond Kubernetes defaults, or complex sidecar injection patterns. Teams already comfortable with Kubernetes custom resources and operators will find the extension model natural, though the learning curve increases with the number of custom resource types deployed.

The project maintains active development with regular updates to its workload controllers and operational features. The codebase shows ongoing refinement of existing capabilities rather than frequent breaking changes. Documentation is comprehensive with dedicated guides for each major feature area. The project operates as a CNCF incubating initiative, indicating community backing and a commitment to cloud-native standards.