Machine Learning System Design -The Model Serving Triangle, With One Forward Pass Flowing Through Every Trade-off (Part3)

Last Updated on April 29, 2026 by Editorial Team Author(s): Utkarsh Mittal Originally published on Towards AI. The Model Serving Triangle, With One Forward Pass Flowing Through Every Trade-off (Part3) Part 1-p https://pub.towardsai.net/the-ml-system-design-interview-with-numbers-flowing-through-every-stage-part-1-a77888339297?source=friends_link&sk=9064640f37c84a131ef24b1126bc0cf9 Three pieces of memory math that every candidate must have memorizedThis article discusses the complexities and trade-offs of machine learning model serving, detailing how decisions revolve around three sources: latency, throughput, and cost. It emphasizes the importance of understanding these factors when deploying models in production and features practical examples and strategies to maintain efficiency, including latency requirements and architectural choices. It provides insights into challenges such as cold starts and the significance of training-serving skew, supporting these topics with numerous examples, analogies, and recommendations for best practices in model deployment and monitoring. Read the full blog for free on Medium. Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor. Published via Towards AI