Tired of wrestling with cryptic error messages and complex troubleshooting? awesome-ctl is like having a seasoned expert on call 24/7, using the power of AI to provide clear, actionable diagnoses for your infrastructure and applications.
awesome-ctl is a command-line tool that brings cutting-edge LLM (Large Language Model) technology to the forefront of systems diagnostics. Connect awesome-ctl to your Kubernetes cluster, Docker Swarm, AWS environment, or other supported systems, and let our AI analyze the data to help you find and fix issues faster.
- 🧠 AI-Driven Insights: awesome-ctl leverages the reasoning power of LLMs to analyze complex technical data and provide human-readable diagnoses and recommendations.
- 🔌 Extensible Connector Architecture: Easily connect to a variety of systems and services:
- Kubernetes: Get to the bottom of pod crashes, deployment issues, resource bottlenecks, and more.
- Docker: Diagnose container failures, image build problems, and networking issues.
- AWS (Coming Soon): Analyze CloudWatch logs, EC2 instance health, and other AWS services.
- More to Come: We're constantly adding support for new systems!
- 🔍 Deep System Analysis: awesome-ctl gathers the essential information to provide comprehensive diagnoses:
- Logs and Events: Analyze system and application logs to identify errors, warnings, and patterns.
- Resource Utilization: Understand CPU, memory, network usage, and other metrics to spot bottlenecks.
- Configuration Data: Detect misconfigurations and potential conflicts.
- 🛠 Actionable Recommendations: Don't just identify problems - fix them! awesome-ctl provides clear steps and guidance to help you resolve issues quickly.
- 🤖 Easy-to-Use CLI: A simple and intuitive command-line interface makes diagnostics a breeze.
- Python 3.8+: The language of awesome-ctl.
- Connectors: Install the necessary connector libraries for the systems you want to diagnose (e.g.,
kubernetes,docker).
poetry add awesome-ctl💻 Usage
Basic Diagnostics:
awesome-ctl diagnose <connector> [options]awesome-ctl diagnose kubernetes --namespace my-app # Analyze issues in the "my-app" namespace
awesome-ctl diagnose aws # Analyze issues with AWS resourcesawesome-ctl --help📂 Project Structure
- awesome-ctl/: The core Python package.
- agents/: Contains connector plugins that gather data from different systems.
- llm/: Manages interaction with Large Language Models.
- analysis/: Core logic for analysis, diagnosis, and report generation.
- awesome-ctl_cli/: The command-line interface.
- tests/: Keep things running smoothly with a comprehensive test suite.
🙌 Contributing
- awesome-ctl is a community-driven open-source project! We welcome contributions from developers of all levels. Here's how to get involved:
- Open an issue: Report a bug, request a feature, or share your ideas.
- Submit a pull request: Contribute code, documentation, or anything you think can improve awesome-ctl.
📄 License
This project is licensed under the MIT License. For more details, see the LICENSE file.
Key Changes:
- Scope Emphasis: The README now clearly positions
awesome-ctlas a general-purpose diagnostic tool with LLM-powered analysis at its core. - Connector Focus: Highlights the extensibility of the project through connectors while providing examples.
- Actionable Focus: Emphasizes that
awesome-ctlhelps users not only find but also fix problems.
Please find the LICENSE of Awesome-CloudOps-Automation here
We would like to acknowledge the original Awesome-CloudOps-Automation contributors for their hard work and dedication. Their efforts have laid the foundation for this project, and we are grateful for their contributions.