- Add jupyter_launcher.sh script to start Jupyter with ML tools
- Create cli_integration.py helper for CLI operations
- Add sample notebook structure for experiments
- Create workflow documentation for seamless data science integration
- Add Prometheus, Grafana, and Loki monitoring stack
- Include pre-configured dashboards for ML metrics and logs
- Add Podman container support with security policies
- Implement ML runtime environments for multiple frameworks
- Add containerized ML project templates (PyTorch, TensorFlow, etc.)
- Include secure runner with isolation and resource limits
- Add comprehensive log aggregation and alerting
