AI in DevOps is often reduced to chatbots and code completion tools. But large language models can be used far beyond simple assistance—they can actively reduce operational risk and improve system resilience.

This session explores real-world applications of LLMs within DevOps and SRE workflows, including:

AI-assisted incident summarization and RCA drafting

Automated log analysis using embeddings

Infrastructure-as-Code generation and validation

Risk detection in CI/CD pipelines before production rollout

Intelligent runbook generation and policy enforcement

Rather than theoretical possibilities, this talk focuses on practical implementations and lessons learned when integrating AI into production reliability engineering.

Attendees will gain a framework for responsibly deploying LLM-powered automation inside their DevOps ecosystems—without introducing new operational or security risks.