This article explores the emerging architectural paradigm of the “Autonomous Stack,” where software systems are designed to be self-healing, self-optimizing, and resilient by default. As complexity increases across distributed cloud, edge, and AI-enabled environments, architects are leveraging observability, AI/ML, policy-driven orchestration, and event-driven patterns to enable systems that adapt and recover without manual intervention. The article covers key components such as service mesh, health probes, automated rollback mechanisms, and intelligent scaling. It also examines how predictive analytics, feedback loops, and agent-based automation are transforming runtime behavior into a dynamic, learning ecosystem—pushing software architecture beyond static reliability toward autonomous operational excellence.
Keywords: AI/ML in DevOps, Cloud-Native Architecture, autonomous stack, event-driven architecture, policy-driven orchestration, predictive analytics, resilient software design, self-healing systems, self-optimizing applications
