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testkube

☸️ The Open Testing Platform for AI-Driven Engineering Teams

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创建于 2021-07-01 · 更新于 2026-10-16 · 今日第 9733 名
主要开发者

kubeshop/testkube 排名第 9,733,有 1,669 个星标。

同类别比较

kubeshop/testkube 排名第 9,733,此处有 8 个同类条目;plasticityai/magnitude 排名第 9,718。

同类别比较
名称排名指标
Lam1360/YOLOv3-model-pruning9,708
语言:
Python
星标数:
1,676
分叉数:
426
简介:
在 oxford hand 数据集上对 YOLOv3 做模型剪枝(network slimming)
NVIDIA/nccl-tests9,710
语言:
Cuda
星标数:
1,675
分叉数:
412
简介:
NCCL Tests
YanWenKun/ComfyUI-Docker9,712
语言:
Dockerfile
星标数:
1,675
分叉数:
236
简介:
🐳Dockerfile for 🎨ComfyUI. | 容器镜像与启动脚本
plasticityai/magnitude9,718
语言:
Python
星标数:
1,674
分叉数:
123
简介:
A fast, efficient universal vector embedding utility package.
LlamaEdge/LlamaEdge9,753
语言:
Rust
星标数:
1,658
分叉数:
148
简介:
The easiest & fastest way to run customized and fine-tuned LLMs locally or on the edge
amir-abdi/keras_to_tensorflow9,792
语言:
Python
星标数:
1,645
分叉数:
524
简介:
General code to convert a trained keras model into an inference tensorflow model
pixeltable/pixeltable9,806
语言:
Python
星标数:
1,640
分叉数:
227
简介:
The backend agents build with - Multimodal database, orchestration, and serving in one file
jina-ai/langchain-serve9,818
语言:
Python
星标数:
1,634
分叉数:
131
简介:
⚡ Langchain apps in production using Jina & FastAPI
关键参数与规格
关键参数与规格
参数值
语言Go
类别Infrastructure
子类别Orchestration,Observability
关键词Automated testing, Containers, DevOps, MCP
星标数1,669
分叉数180
贡献者100
创建日期2021-07-01
更新日期2026-10-16
1 天星标数0
7 天星标数4
排名9,733
上次排名9,772
排名变化39
7 天星标排名6,117
上次 7 天星标排名5,549
7 天星标排名变化-568
总星标排名7,410
上次总星标排名7,402
总星标排名变化-8
README 摘录

The Open Testing Platform for AI-driven Engineering Teams Testkube provides a single platform for defining, running and analyzing automated tests, using your existing testing tools/scripts, running in your Kubernetes infrastructure. **Run any Tests** : Execute _any_ tests/tools/scripts at scale; API, E2E, Performance, Security, Infrastructure, etc. **Trigger Tests whenever needed**: Trigger tests manually, on schedules, from CI/CD/GitOps pipelines, on Kubernetes Events, via the REST API, through MCP, etc. **See Everything**: All test results, artifacts, logs and

resource-metrics are aggregated for centralized troubleshooting and reporting - Read More. **Integrate Natively**: Testkube integrates with existing tools and infrastructure using Webhooks, the Testkube REST API or the MCP Server - see Integration Examples. **Testkube AI**: Use the Testkube MCP Server or native AI Agents for troubleshooting, analysis, remediation, etc - Read More **Enterprise Ready**: SSO/SCIM, RBAC, Teams, Resource-Groups, Audit-logs, etc. **See it in action:** Open the interactive TestWorkflows showcase to see how a workflow builds up from a

single test to a fully orchestrated pipeline. Two ways to run Testkube Open Source Agent - this repo. MIT-licensed, runs standalone in your Kubernetes cluster, no control plane required. Great for single-cluster setups, self-managed environments, and evaluating Testkube. The Helm or CLI Installation will make it easy to deploy the agent into your target cluster. The Quickstart is the easiest way to set up Testkube and run your first tests. Check out the Testkube Open Source Overview to

learn more about the open source deployment architecture. Commercial Control Plane The control plane connects every Testkube agent across clusters, teams, and environments into a single dashboard: **One control plane, unlimited clusters** - orchestrate and analyze tests across clusters and regions **Testkube AI** - workflow generation, failure investigation, remediation PRs **Enterprise-grade** - SSO/SCIM, RBAC, audit logs, SLA-backed support Check out the Installation Overview to learn more about different ways to deploy and run the Testkube Control Plane. The online Trial

is the easiest way to try the commercial Testkube offering - Get Started Marketplace The Testkube Marketplace provides an open and ready-to-use catalog of Testkube Workflows for Infrastructure Testing - Read More. Documentation Extensive documentation is available at docs. Contributing Check out our Contributors Guide and the Agent Architecture to find your way around our codebase and process. If you want to contribute code, this reading order works well: 1. md - contribution workflow, coding standards, and PR process 2. md

- local setup with Tilt and day-to-day development loop 3. md - high-level system design and key code paths Shout-out to our contributors 🎉 - you're great! ⭐️ @lreimer - K6 executor Gradle executor Maven executor ⭐️ @jdborneman-terminus - Ginkgo executor ️⭐️ @abhishek9686 ⭐️ @ancosma ⭐️ @Stupremee ⭐️ @artem-zherdiev-ingio ⭐️ @chooco13 - Playwright executor Go to contribution document to read more how can you help us 🔥 Feedback Whether Testkube helps you or not, we would love to help and hear from you. Please join us on Slack

to ask questions and let us know how we can make Testkube even better!

常见问题

记录了多少星标和分叉?

kubeshop/testkube 有 1,669 个星标和 180 个分叉。

仓库排名是多少?

kubeshop/testkube 排名第 9,733。

记录的语言和类别是什么?

kubeshop/testkube 有 1,669 个星标,语言为 Go,类别为 Infrastructure。

哪个仓库排名最接近?

kubeshop/testkube 与 plasticityai/magnitude 比较,后者排名第 9,718,有 1,674 个星标。

README

The Open Testing Platform for AI-driven Engineering Teams

Testkube provides a single platform for defining, running and analyzing automated tests, using your existing testing tools/scripts, running in your Kubernetes infrastructure.


Trusted by Engineering Teams at CoreWeave, NVidia, Siemens, T-Mobile, Harvard, SwissCom, and many more..


Website |  Docs |  Changelog |  Blog |  Slack  |  LinkedIn  |  X


Why Testkube?

  • Run any Tests : Execute any tests/tools/scripts at scale; API, E2E, Performance, Security, Infrastructure, etc. - Examples & Guides.
  • Trigger Tests whenever needed: Trigger tests manually, on schedules, from CI/CD/GitOps pipelines, on Kubernetes Events, via the REST API, through MCP, etc. - Read More.
  • See Everything: All test results, artifacts, logs and resource-metrics are aggregated for centralized troubleshooting and reporting - Read More.
  • Integrate Natively: Testkube integrates with existing tools and infrastructure using Webhooks, the Testkube REST API or the MCP Server - see Integration Examples.
  • Testkube AI: Use the Testkube MCP Server or native AI Agents for troubleshooting, analysis, remediation, etc - Read More
  • Enterprise Ready: SSO/SCIM, RBAC, Teams, Resource-Groups, Audit-logs, etc. - Read More.

See it in action: Open the interactive TestWorkflows showcase to see how a workflow builds up from a single test to a fully orchestrated pipeline.

Two ways to run Testkube

Open Source Agent - this repo.

MIT-licensed, runs standalone in your Kubernetes cluster, no control plane required. Great for single-cluster setups, self-managed environments, and evaluating Testkube.

  • The Helm or CLI Installation will make it easy to deploy the agent into your target cluster.
  • The Quickstart is the easiest way to set up Testkube and run your first tests.

Check out the Testkube Open Source Overview to learn more about the open source deployment architecture.

Commercial Control Plane

The control plane connects every Testkube agent across clusters, teams, and environments into a single dashboard:

  • One control plane, unlimited clusters - orchestrate and analyze tests across clusters and regions
  • Testkube AI - workflow generation, failure investigation, remediation PRs
  • Enterprise-grade - SSO/SCIM, RBAC, audit logs, SLA-backed support

Check out the Installation Overview to learn more about different ways to deploy and run the Testkube Control Plane.

The online Trial is the easiest way to try the commercial Testkube offering - Get Started

Marketplace

The Testkube Marketplace provides an open and ready-to-use catalog of Testkube Workflows for Infrastructure Testing - Read More.

Documentation

Extensive documentation is available at docs.testkube.io.

Contributing

Check out our Contributors Guide and the Agent Architecture to find your way around our codebase and process.

If you want to contribute code, this reading order works well:

  1. CONTRIBUTING.md - contribution workflow, coding standards, and PR process
  2. DEVELOPMENT.md - local setup with Tilt and day-to-day development loop
  3. ARCHITECTURE.md - high-level system design and key code paths

Shout-out to our contributors 🎉 - you're great!

Go to contribution document to read more how can you help us 🔥

Feedback

Whether Testkube helps you or not, we would love to help and hear from you. Please join us on Slack to ask questions and let us know how we can make Testkube even better!

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