About This Architecture

Multi-cloud SaaS observability platform built on AWS EKS integrates monitoring agents from AWS, Azure, and GCP environments into a unified control plane. Metrics flow through API Gateway to specialized microservices—Metrics Ingestion writes to Timestream, Topology Discovery maps infrastructure relationships in Neptune graph database, and Incident Detection triggers EventBridge workflows. An Agentic AI Orchestrator leverages LLM endpoints, vector knowledge stores, and Lambda-based tool executors to automate root cause analysis and remediation across customer Kubernetes clusters, CI/CD pipelines (GitHub Actions, ArgoCD, Jenkins), and Git repositories. Platform engineers can fork this architecture on Diagrams.so to customize the AI orchestration layer, swap Neptune for alternative graph databases, or add provider-specific monitoring agents. This design demonstrates best practices for building intelligent, multi-tenant observability platforms that unify metrics, topology, and incident management with generative AI capabilities.

People also ask

How do I architect a multi-cloud SaaS observability platform on AWS with AI-driven incident response?

Deploy an EKS cluster hosting microservices for metrics ingestion (Timestream), topology discovery (Neptune graph), and incident detection (EventBridge). Integrate monitoring agents from AWS, Azure, and GCP via API Gateway. Add an Agentic AI Orchestrator using LLM endpoints, vector knowledge stores, and Lambda tool executors to automate root cause analysis and remediation across customer environme