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208 published articles
Use keyword retrieval when the query's terms carry essential evidence, vector retrieval when meaning is expressed differently from the stored wording, and hybrid retrieval when both signals matter.
Locate the failing stage by starting with the actual request and its permitted trace, confirming which application version and operations it represents, and following the recorded execution through retrieval, model calls, tools, and…
Organize production monitoring around three connected views: sampled quality and safety evidence, operational performance, and cost drivers.
Choose quality, safety, and custom evaluation gates by naming the failures a release must detect.
Prepare evaluation records by first deciding whether Microsoft Foundry will score stored responses or invoke a model or agent target to generate new responses.
Versioning prompts and comparing variants with Git works best when the team versions a complete application change: prompt text, its configuration, the evaluation inputs, and the evidence used to approve it.
Choose provisioned throughput in Microsoft Foundry when measured, reasonably predictable demand and response-time requirements justify dedicated model-processing capacity.
Change a production base model through a controlled sequence: discover the need and deadline, assess an available replacement, adapt the application, validate against fixed evidence, roll out in stages and retire the source deliberately.
When choosing Foundry model deployment options, start with a model that meets the application's quality and capability requirements, then reject deployment paths that violate production constraints.
Securing Foundry identities and private connectivity requires two cooperating controls: Microsoft Entra ID and role-based access control (RBAC) authorize an operation, while network configuration provides an allowed path to its…
Provisioning Foundry resources and projects establishes an application environment: a Foundry resource supplies the administrative boundary, a child project organizes development, and separately configured model deployments supply…
Investigate when production data quality, input or prediction distributions, or measured model performance depart from an agreed expectation.
