Microsoft Foundry でモデル・コスト・品質を管理する開発者向けガイドA Developer’s Guide to Managing Models, Cost and Quality in Microsoft Foundry

Full Model Lifecycle

Building AI systems is no longer mainly about gaining access to a capable model. The more difficult task is choosing, validating, optimizing, and operating the right model throughout the lifecycle of a real application, which makes model management in Microsoft Foundry a production concern rather than a one-time decision.

The guide focuses on a practical lifecycle that connects model selection with quality evaluation, cost optimization, safe operation, and continued improvement. These activities need to remain aligned as the application and its production requirements develop.

Prototype to Production

A retrieval-augmented generation-based customer support copilot illustrates the difference between an early prototype and a production system. The same distinction applies to a tool-calling agent that helps employees complete business workflows.

For a prototype, selecting a strong model, connecting a few data sources, and producing a useful response may be sufficient. Production introduces additional requirements. The system must retrieve the right context, call the right tools, satisfy quality and safety thresholds, remain within latency targets, and operate at a cost the business can sustain.

Quality and Cost

Model choice therefore cannot be separated from validation and optimization. Quality evaluation determines whether the system meets the required thresholds, while cost optimization addresses whether it can continue operating at a sustainable expense.

Latency is another production constraint. A model and application configuration must not only return useful results but also stay within the required response targets. Safe operation is similarly part of the lifecycle, rather than an issue handled only after deployment.

Iterative Improvement in Production

Production model management is continuous because the surrounding conditions do not remain fixed. Models evolve, costs shift, and production requirements often emerge after the first working version has already been created.

The Microsoft Foundry lifecycle described in the guide responds to that reality through iterative improvement. Model selection, quality evaluation, cost optimization, safety, and operational requirements are revisited as production needs change, keeping the system aligned with the application’s current demands.