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Agent team for DevOps that solves Kubernetes, Docker, Terraform, and monitoring challenges through intelligent automation.

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DevOps Agent

An AI-powered CLI tool to assist with DevOps troubleshooting, Applications with Kubernetes architecture, log analysis, and infrastructure code generation.

Features

  • 📊 Log Analysis: Analyze log files and get actionable insights
  • 💬 Query Interface: Ask questions about DevOps best practices, Terraform, Kubernetes, etc.
  • 🛠️ Template Generation: Generate infrastructure code templates
  • 🤖 AI-Powered: Leverages Claude AI for intelligent responses

Installation

# Clone the repository
git clone https://github.com/yourusername/devops-agent.git
cd devops-agent

# Install in development mode
pip install -e .

# Or install from PyPI (when published)
pip install devops-agent

Configuration

LLM API KEYS

 export GEMINI_API_KEY=YOUR API KEY
 or 
 export ANTHROPIC_API_KEY=YOUR API KEY
 or
 export OPENAI_API_KEY=YOUR API KEY

Qdrant Config for Agent Memory

export QDRANT_URL=YOUR QDRANT URL
export QDRANT_API_KEY=YOUR QDRANT API KEY

Usage

Analyze Log Files

devops-agent run --log-file /path/to/app.log

Ask Questions

devops-agent run --query "I need terraform script to spin up Azure blob storage"
devops-agent run --query "How to increase my pod memory and CPU in k8s"

Generate Templates

devops-agent template terraform
devops-agent template kubernetes
devops-agent template docker

Configuration

devops-agent config

Examples

# Analyze application logs
devops-agent run --log-file ./logs/app.log --format json

# Get Terraform help
devops-agent run --query "terraform script for AWS S3 bucket with versioning"

# Kubernetes troubleshooting
devops-agent run --query "pod is in CrashLoopBackOff status, how to debug?"

# Save output to file
devops-agent run --query "docker-compose for nginx and postgres" --output docker-compose.yml

Development

# Install development dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Format code
black devops_agent/
isort devops_agent/

# Lint
flake8 devops_agent/

Project Structure

devops-agent/
├── devops_agent/          # Main package
│   ├── cli.py            # CLI interface
│   ├── core/             # Core functionality
│   ├── templates/        # Template generators
│   ├── utils/            # Utilities
│   └── prompts/          # LLM prompts
└── docs/                 # Documentation

Common issues and fixes

  • if you see any error like INFO Error checking if content_hash ed7002b439e9ac845f22357d822bac1444730fbdb6016d3ec9432297b9ec9f73 exists: Unexpected Response: 400 (Bad Request) Raw response content: b'{"status":{"error":"Bad request: Index required but not found for \\"content_hash\\" of one of the following types: [keyword]. Help: Create an index for this key or use a different filter."},"time":2 ...'
curl --request PUT \
  --url https://9df18135-290c-45b3-8158-f73b103dc352.eu-west-2-0.aws.cloud.qdrant.io:6333/collections/devops-memory/index \
  --header 'Authorization: Bearer YOUR_API_KEY' \
  --header 'Content-Type: application/json' \
  --data '{
  "field_name": "content_hash",
  "field_schema": {
    "type": "keyword",
    "on_disk": true
  }
}'

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

Apache2.0 License - see LICENSE file for details

RoadMap

  • Implement log analysis with pattern detection
  • Add support for multiple LLM providers with model params --model gpt-5-mini
  • Add Support for self-hosted models Ollama & vLLM
  • Add Support for Reasoning controls
  • Add Support for MCP to use local file system for quick access
  • Add support for Human-in-the-Loop for more focused and collaborated work
  • Create direct pip package for easy install of the agent.

Support

For issues and questions, please open an issue on GitHub.

Special Credits

  • Built with Agno2.0 framework for multi-agent orchestration
  • Uses POML for structured prompt engineering
  • powered by Claude (Anthropic), GPT (OpenAI) and Gemini (Google)

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Agent team for DevOps that solves Kubernetes, Docker, Terraform, and monitoring challenges through intelligent automation.

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