datagen24/dshield-coordination-engine

AI Summary: Implement comprehensive monitoring and observability for the DShield Coordination Engine, including Prometheus metrics, health checks, integration with an observability stack (like ELK/Grafana), alerting, and distributed tracing. This addresses a missing production readiness requirement.

AI Summary: Implement a CI/CD pipeline for the DShield Coordination Engine project, including automated testing, security scanning, deployment, code quality checks, dependency updates, and documentation generation using GitHub Actions and tools like Snyk, ruff, and mypy.

AI Summary: Implement robust security features in the DShield Coordination Engine, including a SecurityMonitor for anomaly detection, comprehensive audit logging, rate limiting, a security testing framework, security metrics and alerting, and improved error handling to prevent information leakage. This addresses critical security vulnerabilities identified in the project.

AI Summary: Implement missing core services (LLM integration, worker processes, workflow orchestration, and coordination analysis algorithms) for an AI-powered attack coordination detection service. This includes adding error handling, logging, and configuration management. The project uses FastAPI, LangGraph, Ollama, PostgreSQL, Redis, and Docker.