Systems | Development | Analytics | API | Testing

Operationalizing Code Optimization to Improve Cost, Performance, and Reliability of Your Cloud and AI Workloads While infrastructure optimizations like rightsizing and auto-suspending idle resources are standard practice, they cannot solve the cost and performance issues caused by inefficient code. Unoptimized workloads and AI functions waste compute resources, lead to missed SLAs, and significantly inflate cloud spend.

AI costs are unpredictable and behave nothing like traditional cloud spend. FinOps teams face new challenges: opaque model pricing, and hidden costs in places like prompt design and context length. In this session, our Head of AI, Prajakta, will show you how to bring FinOps discipline to AI costs: how to see them, attribute them, and optimize them. She’ll give you practical levers that can cut AI costs by 20 – 80%.