What is a serving graph architecture in large-scale classification systems?

A serving graph architecture represents the classification system as a dependency graph of services, features, and models executed per request.

In large-scale classification systems, inference is rarely a single model call. Instead, it becomes a directed acyclic graph (DAG) where nodes represent feature retrieval, transformations, embeddings, models, and post-processing steps. A serving graph engine orchestrates execution, resolves dependencies, and parallelizes independent nodes. This design improves modularity and reuse but introduces challenges like graph scheduling, dependency resolution, and debugging distributed inference paths.