AI agents are moving from prototypes into production, and platform teams are increasingly asked to provide a “paved road” for deploying them safely. But agentic workloads don’t fit neatly into traditional stateless service templates: they pull in embeddings and retrieval context, call tools, stream responses, and require repeatable execution across environments—often leading to one-off deployments and operational inconsistency.

This talk presents a platform engineering "path” for agentic workloads using a pattern we call self-contained data agents: a standardized, containerized unit that packages the agent runtime, tool contracts, and data-adjacent execution model behind a clear service boundary. We’ll show how Knative enables a consistent developer experience—request-driven deployment, scale-to-zero, revision-based rollouts, and session management—while keeping the platform portable and Kubernetes-native.

KubeCon + CloudNativeCon India 2026, Mumbai