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YouTube

Bridging the Gap from GPU-as-a-Service to AI Cloud

Tech Field Day via YouTube

Overview

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Learn how to distinguish between true AI cloud services and basic GPU-as-a-Service offerings in this 11-minute conference presentation. Explore the three essential components that define a legitimate cloud provider: self-service consumption, applications or tools, and multi-tenancy. Discover why many current GPU cloud solutions fall short by relying on manual processes like spreadsheets and bare metal servers instead of automated, on-demand services. Examine the technical requirements for proper multi-tenancy, including secure VMs, pre-configured operating system images, public IP addresses, firewall rules, and VPCs that must be automatically provisioned without backend intervention. Understand the scalability challenges of serving diverse customer needs, from single GPU requirements to 64-GPU deployments, and how automation enables true self-service experiences. Gain insights into the industry's evolution beyond GPU-as-a-Service toward model and endpoint consumption, where users focus on applications rather than underlying infrastructure management.

Syllabus

Bridging the gap from GPU-as-a-Service to AI Cloud with Rafay

Taught by

Tech Field Day

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