Official Technical Resources: Microsoft (page 11)
Official Technical Resources · Microsoft: 312 entries in total; this page lists entries 151–165.
Monitoring evaluation metrics descriptions and use cases
Understand the metrics used when monitoring the performance of generative AI models deployed to production on Azure Machine Learning.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Model Evaluation and Benchmarks · Large Language Model (LLM)
Link last checked: 2026-09-24
Hyperparameters for computer vision tasks in automated machine learning
Learn which hyperparameters are available for computer vision tasks with automated ML.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Supervised Learning · Regularization
Link last checked: 2026-09-24
Durable state store for Microsoft Foundry hosted agents (preview)
Learn how the Microsoft Foundry durable state store preserves hosted agent data with user isolation, tags, expiration, and service limits.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Agent Memory · AI Agent
Link last checked: 2026-09-24
Resilience for long-running Microsoft Foundry hosted agents (preview)
Understand how Microsoft Foundry hosted agents preserve long-running work, recover after process interruptions, and replay streamed results.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Agent · Agent Frameworks
Link last checked: 2026-09-24
Routines in Foundry Agent Service
Learn how routines in Foundry Agent Service invoke agents from timers, schedules, GitHub issues, and Microsoft Teams messages.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Agent · Agent Frameworks
Link last checked: 2026-09-24
Build with agents, conversations, and responses
Learn how agents, conversations, and responses work together in Foundry Agent Service, and choose the runtime components your application needs.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Agent · Agent Frameworks
Link last checked: 2026-09-24
Tool best practices for Microsoft Foundry Agent Service
Learn tool best practices for Foundry Agent Service: configure tool_choice, secure tool usage, and troubleshoot tool-calling issues.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Tool Calling · AI Agent
Link last checked: 2026-09-24
What is Toolbox in Foundry?
Learn how a toolbox packages agent tools behind a single managed MCP endpoint in Microsoft Foundry, with centralized authentication, tool search, and skills.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Tool Calling · AI Agent
Link last checked: 2026-09-24
Vector stores for file search
Learn how vector stores enable file search for agents, including ingestion (chunking and embeddings), readiness, limits, and expiration policies.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Agent · Agent Frameworks
Link last checked: 2026-09-24
Voice agent tracing, monitoring, and evaluation
Learn what is different when you trace, monitor, and evaluate voice-based agents in Microsoft Foundry.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Model Evaluation and Benchmarks · Large Language Model (LLM)
Link last checked: 2026-09-24
Memory in Microsoft Foundry Agent Service (preview)
Learn about memory in Foundry Agent Service, including how it works, long-term memory types, retention and item-level controls, and security considerations.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Agent Memory · AI Agent
Link last checked: 2026-09-24
AI Red Teaming Agent
This article provides conceptual overview of the AI Red Teaming Agent.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Red Teaming · AI Guardrails · AI Governance and Regulation
Link last checked: 2026-09-24
Agent evaluators
Learn how to evaluate Azure AI agents using intent resolution, tool call accuracy, and task adherence evaluators.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Model Evaluation and Benchmarks · Large Language Model (LLM)
Link last checked: 2026-09-24
Azure OpenAI graders
Learn about Azure OpenAI Graders for evaluating AI model outputs, including label grading, string checking, text similarity, and custom grading.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Model Evaluation and Benchmarks · Large Language Model (LLM)
Link last checked: 2026-09-24
Custom evaluators (preview)
Learn how to create custom evaluators for your AI applications using code-based, prompt-based, or endpoint-based approaches.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Model Evaluation and Benchmarks · Large Language Model (LLM)
Link last checked: 2026-09-24