Lumino
What is Lumino?
Lumino is an AI/ML-powered diagnostic engine designed for Site Reliability Engineers (SREs) to enhance observability on Kubernetes and OpenShift environments. It utilizes the Model Context Protocol (MCP) and integrates over 40 tools to analyze logs, metrics, and traces, facilitating automated root cause analysis (RCA) and predictive analysis.
How to use Lumino?
To use Lumino, you can either provision it through Claude Code CLI by following a simple prompt or manually set it up by cloning the repository and installing dependencies. Once set up, you can interact with Lumino using natural language queries to analyze your Kubernetes clusters.
Key features of Lumino?
- Real-time monitoring of cluster health and resources.
- Automated root cause analysis for failed pipelines.
- Predictive analytics to forecast resource bottlenecks.
- Advanced log analysis with anomaly detection.
- Simulation of configuration changes to assess impact before deployment.
Use cases of Lumino?
- Diagnosing complex failures in CI/CD pipelines.
- Predicting potential resource issues before they impact services.
- Analyzing logs for security compliance and certificate management.
- Monitoring and optimizing Kubernetes and OpenShift operations.
FAQ from Lumino?
-
Can Lumino be used with any Kubernetes cluster?
Yes, Lumino is designed to work with any Kubernetes or OpenShift cluster that has the appropriate access permissions. -
Is Lumino open-source?
Yes, Lumino is open-source and available on GitHub under the Apache License 2.0. -
What are the prerequisites for using Lumino?
You need Python 3.10 or higher and a valid kubeconfig with read permissions for your Kubernetes cluster.
Server Config
{
"mcpServers": {
"lumino": {
"type": "stdio",
"command": "<ABSOLUTE_PATH_TO_LUMINO>/.venv/bin/python",
"args": [
"<ABSOLUTE_PATH_TO_LUMINO>/main.py"
],
"env": {
"PYTHONUNBUFFERED": "1"
}
}
}
}