Open Source Summit India 2026

Modern Kubernetes platforms generate massive volumes of logs, events, metrics, and reconciliation signals, yet developers still struggle to answer a basic question: why did my deployment fail? At Comcast, operating large-scale internal Kubernetes platforms, failures often span platform abstractions, custom controllers, policies, and cluster runtime behavior—making manual diagnosis slow and unreliable.

This talk explores how AI can act as a diagnostic layer in Kubernetes platforms, focusing on failure explanation rather than detection. It presents architectural patterns for correlating platform intent with Kubernetes signals and translating complex control-plane behavior into clear, human-readable explanations and actionable guidance. Attendees will learn how AI can augment platform engineers, improve developer trust, and significantly reduce time-to-resolution without becoming another opaque system.