Explore advanced load management techniques for AI models in this 31-minute conference talk from the Linux Foundation. Learn how to effectively manage OpenAI rate limits and implement request prioritization to overcome challenges in AI-driven applications. Discover the limitations of traditional retry and back-off strategies when dealing with fine-grained rate limits imposed by OpenAI. Gain insights into Aperture, an open-source load management platform offering advanced rate-limiting, request prioritization, and quota management capabilities for AI models. Examine a real-world case study from CodeRabbit, showcasing how Aperture facilitated client-side rate limits with business-attribute-based request prioritization to ensure a reliable user experience while scaling their PR review service using OpenAI models.
Overview
Syllabus
Load Management for AI Models - Managing OpenAI Rate Limits with Request Prioritization- Harjot Gill
Taught by
Linux Foundation