Model Serving · Software component

Serving Configuration Optimizer

Software componentModel ServingModelsarc:ServingConfigurationOptimizer

An automated search component that sweeps inference-server settings (instance count, dynamic-batching size and timeout, concurrency, cache sizing), measures each, and reports the latency-throughput Pareto frontier.

Responsibility. Selects serving configurations on the latency-throughput Pareto frontier.

Also known as: Configuration search, Model analyzer

Direct neighbourhood (hover for relationship types)

Relationships

invokes dependency

Inference Performance Analyzer Ch4.4

produces lifecycle

Inference Serving Configuration abstract Ch4.4

Design guidance

SHOULD choose small batches with multiple instances for latency-sensitive services and large batches with fewer instances for throughput-focused batch processing.

Classification

Patterns: Pareto-frontier configuration selectionAutomated configuration sweep
Technologies: NVIDIA Triton Model Analyzer
Quality attributes: Performance efficiency (ISO/IEC 25010)Cost efficiency
Risks mitigated: Manual tuning guesswork

Sources

Ch4.4: T. Nguyen, "Performance Profiling and Optimization," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 4.4. ISBN: 9798244538229.