CLOUDxAI draws 800+ engineers

CLOUDxAI 2026 brought more than 800 engineers and site reliability engineers to Bengaluru on March 14 for a one-day event focused on running cloud systems with more automation and more artificial intelligence. (theprint.in) Organizers said attendees came from more than 500 companies and gathered at NIMHANS Convention Centre in Bengaluru, with Cast AI listed as the conference’s powering partner. (theprint.in, cloudconf.ai) The event site listed sessions from 8:50 a.m. to 6:00 p.m. on March 14 and named speakers including Abhishek Veeramalla, Hitesh Choudhary, Ram Iyengar, Shubham Londhe and Cast AI co-founder Laurent Gil. (cloudconf.ai, cast.ai) To understand the agenda, start with Kubernetes, the open-source software many companies use to deploy, scale and manage containerized applications across clusters of servers. Kubernetes documentation describes it as a system for automating deployment, scaling and management. (kubernetes.io) That matters because cloud teams are trying to move from fixed rules to software that can adjust capacity on its own when traffic rises or falls. Kubernetes already includes automatic scaling tools that can add more application copies, adjust resource requests or provision more machines when workloads change. (kubernetes.io, kubernetes.io, kubernetes.io, kubernetes.io) CLOUDxAI’s published themes pushed that idea further, with tracks on cloud-native artificial intelligence systems, multi-agent orchestration, intelligent automation and production deployments of artificial-intelligence-driven cloud operations. (cloudconf.ai, cast.ai) The cost angle is part of the story too. The FinOps Foundation says workload optimization and waste reduction remained the top priority in its 2025 State of FinOps report, and its framework defines optimization as reducing waste and unnecessary usage over time. (data.finops.org, finops.org) That helps explain why conference materials paired artificial intelligence with infrastructure efficiency and “intelligent scaling,” not just with building new models. The event site also highlighted “LLM optimization,” shorthand for tuning large language model workloads so they use compute more efficiently. (cloudconf.ai) Cast AI’s March 12 press release pitched the conference as a meeting point for cloud-native engineers, DevOps professionals, platform teams and artificial intelligence developers, and said Laurent Gil would speak about “autonomous cloud infrastructure” in the artificial intelligence era. (cast.ai) The conference closed on March 14, but the turnout suggests the infrastructure side of artificial intelligence is becoming its own draw: not just how to build models, but how to keep the servers, clusters and budgets underneath them under control. (theprint.in, finops.org)