After optimizing models for inference and establishing scalable infrastructure, the focus shifts to exposing the model's capabilities through a well-defined interface. This chapter addresses the construction of Application Programming Interfaces (APIs) tailored for serving diffusion model inference requests effectively at scale.

You will examine patterns for API design suitable for generative tasks, including strategies for managing long-running image generation processes through asynchronous operations and message queues. Techniques such as request batching for maximizing GPU throughput, implementing rate limiting for service protection, handling authentication, and managing API versions will be covered. The goal is to equip you with the knowledge to build reliable and efficient access points for your deployed diffusion models.