AI-Powered DevOps Platform

Description

An intelligent DevOps platform that leverages machine learning to optimize cloud deployments, automate incident response, and provide actionable performance insights.

Features

• Predictive Scaling: ML-driven resource forecasting and auto-scaling.
• Anomaly Detection: Real-time detection of performance and security anomalies.
• Automated Incident Response: Scripted responses to incidents and outages.
• Performance Optimization Recommendations: Data-driven tuning suggestions.

Tech Stack

• Python (FastAPI)
• TensorFlow/PyTorch
• Prometheus
• Grafana
• Jenkins

Setup

1. Install Python dependencies:

   pip install -r requirements.txt

2. Start the backend API:

   uvicorn main:app --reload

3. Run Prometheus with prometheus.yml config.
4. Connect Grafana to Prometheus for dashboards.
5. Use Jenkins for CI/CD (see Jenkinsfile).

Directory Structure

main.py
ml/
  predictive_scaling.py
  anomaly_detection.py
monitoring/
  prometheus_metrics.py
incident/
  auto_response.py
prometheus.yml
Jenkinsfile
requirements.txt
README.md

License

MIT

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Topics

• devops
• machine-learning
• cloud
• automation
• prometheus
• grafana
• jenkins
• fastapi
• anomaly-detection
• predictive-scaling

Next Steps

• Implement real ML models in ml/
• Expand incident automation in incident/
• Add more metrics in monitoring/