kubeshop/testkube

☸️ The Open Testing Platform for AI-Driven Engineering Teams

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Summary Information

Updated 31 minutes ago
Added to GitGenius on May 1st, 2022
Created on July 1st, 2021
Open Issues & Pull Requests: 51 (+0)
Number of forks: 172
Total Stargazers: 1,647 (+0)
Total Subscribers: 12 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 956.7 days
Mean response time: 765.5 days
90th percentile: 1388.1 days
Tracked items: 402

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 95% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Work labelled "OSS User" is answered fastest, typically in under an hour, while "tech-debt 🙈" waits about 38 months. Only 3% of issues opened in the past year have been closed. Three people close 90% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 20
New in 7 days: 1
Closed in 7 days: 1
Avg open age: 1,060 days
Stale 30+ days: 17
Stale 90+ days: 17

Recent activity

Opened in 7 days: 1
Closed in 7 days: 1
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • bug 🐛 (290)
  • feature-request 🚀 (171)
  • service:dashboard 🎡 (128)
  • enhancement (90)
  • tech-debt 🙈 (55)
  • Bug (41)
  • service:kubectl-plugin 🎡 (32)
  • service:api 🎡 (27)

Most active issues this week

Detailed Description

Testkube is an open testing platform designed for AI-driven engineering teams, written in Go and available under the MIT license. It provides a unified platform for defining, running, and analyzing automated tests across any testing tools, scripts, or frameworks while leveraging Kubernetes infrastructure for execution and orchestration.

The platform supports execution of diverse test types including API tests, end-to-end tests, performance tests, security tests, and infrastructure tests. Tests can be triggered through multiple mechanisms: manual execution, scheduled runs, CI/CD and GitOps pipeline integration, Kubernetes event-based triggers, REST API calls, and through MCP (Model Context Protocol) servers. This flexibility allows teams to integrate testing into their existing workflows without requiring tool replacement.

Testkube centralizes test result management by aggregating test results, artifacts, logs, and resource metrics into a single dashboard for troubleshooting and reporting. The platform integrates with existing infrastructure and tools through webhooks, a REST API, and an MCP server, enabling native integration with external systems. The Testkube AI capability leverages the MCP server and native AI agents for workflow troubleshooting, failure analysis, and automated remediation.

The repository offers two deployment models. The open source agent, contained in this repository, runs standalone within Kubernetes clusters without requiring a control plane, making it suitable for single-cluster setups and self-managed environments. Installation is available through Helm or CLI. A commercial control plane option connects multiple Testkube agents across clusters, teams, and environments into a unified dashboard, offering features like multi-cluster orchestration, Testkube AI capabilities, and enterprise-grade security including SSO, SCIM, RBAC, and audit logging.

The codebase is supported by comprehensive documentation at docs.testkube.io and includes contribution guidelines, development setup instructions using Tilt, and architecture documentation. The project maintains connections with related Kubeshop projects including Monokle, Kusk Gateway, and shares contributors with Argo CD. A marketplace provides ready-to-use workflow templates for infrastructure testing, extending the platform's capabilities through community contributions.