kperf

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Published: Dec 21, 2024 License: MIT

README

kperf - a kube-apiserver benchmark tool

kperf is a benchmarking tool for the Kubernetes API server that allows users to conduct high-load testing on simulated clusters. Its primary purpose is to emulate clusters larger than the actual environment, helping to uncover potential control plane issues based on the user's workload scale. This tool provides an efficient, cost-effective way for users to validate the performance and stability of their Kubernetes API server.

Why kperf?

kperf offers unique advantages over tools like kubemark by simulating a broader range of traffic patterns found in real Kubernetes workloads. While kubemark primarily emulates kubelet traffic, kperf can replicate complex interactions typically associated with controllers, operators, and daemonsets. This includes scenarios like stale list requests from the API server cache, quorum-based list operations that directly impact etcd, and informer cache lists and watch behaviors. By covering these additional traffic types, kperf provides a more comprehensive view of control plane performance and stability, making it an essential tool for understanding how a cluster will handle high-load scenarios across diverse workload patterns.

Getting Started

See documentation on Getting-Started

Running in Cluster

The kperf commands offer low-level functions to measure that target kube-apiserver. You may need example to combine these functions to run example benchmark test.

See documentation on runkperf for more detail.

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.

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