As AI and data-intensive workloads expand, cloud efficiency and engineering teams see storage costs grow exponentially while struggling to pinpoint where waste and unexpected growth are hiding. At scale, the problem compounds: billions of objects, thousands of buckets, and limited visibility into which workloads and teams are driving spend.

This session takes the guesswork out of optimizing cloud object storage costs at scale.

In this session, the FanDuel team shares lessons from using Datadog Storage Management to optimize cloud object storage costs: identifying unused data in large buckets, transitioning cold data to lower-cost storage tiers, and detecting abnormal storage growth before it affects margins.

If you need to scale AI and data platforms while keeping storage costs disciplined and aligned to product outcomes, you won’t want to miss this. You’ll leave with a practical framework for shifting from reactive cost cleanup to proactive, continuous storage optimization.