mut

Mut

AI Powered Kubernetes operator for anomaly detection and resource optimization.

Mut connects to your Kubernetes cluster, continuously monitors resources, metrics, and events, then feeds that data to an LLM to detect patterns, flag anomalies, and suggest optimizations. It bridges the gap between raw cluster data and intelligent decision-making.

🎯 Features

• 🔭 Real-time Cluster Analysis - Watches pods, nodes, deployments, and events across your cluster
• 🧠 LLM-powered Insights - Uses large language models to reason about cluster health and resource efficiency
• 🚨 Anomaly Detection - Identifies unusual patterns and potential issues before they escalate
• ⚙️ Resource Optimization - Suggests improvements to resource requests, limits, and replica counts
• 🛠️ Actionable Recommendations - Generates human-readable explanations and remediation steps

🧭 Versioning

For transparency into our release cycle and in striving to maintain backward compatibility, Mut is maintained under the Semantic Versioning guidelines and release process is predictable and business-friendly.

See the Releases section of our GitHub project for changelogs for each release version of Mut. It contains summaries of the most noteworthy changes made in each release. Also see the Milestones section for the future roadmap.

🐞 Bug tracker

If you have any suggestions, bug reports, or annoyances please report them to our issue tracker at https://github.com/Clivern/Mut/issues

🔐 Security Issues

If you discover a security vulnerability within Mut, please send an email to hello@clivern.com

🤝 Contributing

We are an open source, community-driven project so please feel free to join us. see the contributing guidelines for more details.

⚖️ License

© 2025, Clivern. Released under MIT License.

Mut is authored and maintained by @Clivern.