Introduction
Modern AI infrastructure has become increasingly complex. AI workloads often span Kubernetes clusters, GPU Server infrastructure, enterprise storage, networking, and observability platforms. When performance issues arise, platform teams frequently spend valuable time gathering operational data from multiple systems before they can begin troubleshooting.
This complexity is driving the rise of Agentic AI — AI systems that can reason, invoke tools, and interact with enterprise environments to accomplish multi-step tasks. Unlike traditional chatbots that simply respond to prompts, Agentic AI can gather evidence, analyze infrastructure ...