As SRE teams grow, incident response often slows under the weight of alert noise, weak signals, and manual triage. This talk explores a pragmatic approach to improving incident detection, triage, and root cause analysis by combining strong SRE fundamentals with targeted AI assistance. Drawing from real production workflows, the session covers how better signal design and contextual enrichment can reduce alert fatigue, how AI and LLMs can accelerate triage, log analysis, and hypothesis generation, and where automation should stop to preserve operational trust. Attendees will hear concrete lessons learned from real incidents and platform-scale reliability challenges, with a focus on improving MTTR without over-engineering. This talk is aimed at practicing SREs and platform engineers looking for practical, trustworthy ways to augment their existing reliability workflows.
Charit Upadhyay is a Senior Site Reliability Engineer at Adobe, working on platform reliability for large-scale compute and query services. He previously worked as an SRE at Oracle, focusing on Kubernetes, Terraform, CI CD pipelines, and large distributed infrastructure. Charit is an IEEE Senior Member, a frequent conference speaker, and a regular reviewer of research papers in the reliability and systems space.
