Jason Vallery

Join us for an in-depth exploration of how Azure Blob Storage (Azure's object storage service) has innovated and scaled to meet the demands of supercomputer AI training efforts. Using OpenAI as a case study, we will dive into the internal architecture and new capabilities that enable blob storage to deliver tens of terabits per second (Tbps) of consistent throughput across a multi-exabyte (EiB) scale hierarchical namespace. Attendees will gain insights into workload patterns, best practices, and the implementation strategies that make such high performance possible. We will also cover the API and tooling improvements that allow storage users to tap into this performance seamlessly for AI training and HPC workloads.

This session is presented by the engineers that build blob storage at Microsoft and is a must-attend for developers and architects looking to understand and leverage the latest advancements in object storage technology to support AI and other high-scale workloads.

- Understanding the architecture and improvements enabling Blob Storage's scalability.
- Best practices for managing large-scale AI training workloads.
- Detailed insights into the "scaled accounts" feature and its implementation.

Jason Vallery

Group Product Manager - Azure Blob Storage

Microsoft

Jegan Devaraju

Group Engineering Manager - Azure Blob Storage

Microsoft