‹ All AI-103 questions

AI-103 Practice Question 62: Diagnostic Logging Log Analytics

Microsoft Azure AI Apps and Agents Developer Associate (AI-103) · Test 7 · question 2 of 10

Plan and manage an Azure AI solutionmedium

A platform team runs a shared Foundry resource that several application teams call. After an incident where nobody could say which application caused a spike in 429 errors, the platform team is asked to make every request and error auditable and to be able to write alert queries over the history, not just look at live counters.

What should they configure on the Foundry resource?

Select one answer
Show answer and explanation

Answer:

  • A. A diagnostic setting under Monitoring that sends the Audit and RequestResponse log categories, plus AllMetrics, to a Log Analytics workspace

Diagnostic logs are generated automatically but are not retained or queryable until a diagnostic setting routes them somewhere. Microsoft's how-to has the team add a diagnostic setting on the Foundry resource, select the Audit, RequestResponse, and AllMetrics categories, and send them to a Log Analytics workspace, after which the data can be queried with Kusto (for example, grouping by Resource or OperationName) and used as the source for alert rules. That is exactly the audit-and-alert requirement here.

- B is wrong because quotas and rate limits change how much traffic is *allowed*, not whether the resulting requests and errors are recorded anywhere queryable. It doesn't produce an audit trail. - C is wrong because the Metrics blade shows near-real-time aggregated charts. It isn't a durable log store, doesn't retain per-request detail, and can't back a Kusto alert query the way a Log Analytics workspace can. - D is wrong because Entra sign-in logs record authentication events for identities, not the resource's own API request/response traffic and errors; it doesn't tell the team which application generated a given 429.

Reference: Enable diagnostic logging

Practice Test 7 ›

Study guides for AI-103

AI engineer roadmap 2026: skills, certs and the orderAI engineer roadmap for 2026: skills to learn in order, AI engineer vs ML engineer, which certifications fit each stage, and what to skip.
AI-200 exam guide: Azure AI Cloud Developer AssociateAI-200 replaced AZ-204: what the Azure AI Cloud Developer exam tests, how it differs from AI-103, price in USD and INR, format and how to prepare.
How AI Is Changing Software Jobs: Where to PrepareHow AI is changing software jobs: what history shows, the evidence on junior developers, what Klarna learned, new AI roles and five domains to prepare for.
AI-901 exam guide: Azure AI Fundamentals after AI-900AI-901 replaced AI-900: learn what changed, how much Python and Microsoft Foundry you need, exam costs in India, and how to prepare.
Best AI certifications 2026: AWS, Google, Microsoft, ClaudeThe best AI certifications in 2026 from AWS, Google, Microsoft, Claude and Databricks, by level, with price, status and which one to take first.
Microsoft AI certification path 2026: which exam firstMicrosoft AI certification path for 2026 - AI-901, AB-730, AI-103, AI-200, AI-300, AB-100, AI-500 and GH-300 by role, and which exam to take first.
AI-103 Certification Guide: What Changed From AI-102The AI-103 certification replaced AI-102 in 2026. Exam format, cost, the five skill domains, what changed and how to prepare, with free practice questions.
What Is RAG? How Retrieval-Augmented Generation WorksWhat RAG is and how it works: chunking, embeddings, vector search, hybrid search, reranking, GraphRAG and agentic RAG on AWS, Google and Azure.
Prompt engineering vs RAG vs fine-tuningWhen to use prompt engineering, retrieval-augmented generation, fine-tuning or continued pre-training, compared on cost, freshness, hallucination and privacy.