AI-103 Implement Generative AI And Agentic Solutions Practice Question
You are troubleshooting an Azure OpenAI deployment in Azure AI Foundry where agents are failing to complete tasks due to excessive timeouts. Which THREE diagnostic steps should you take? (Choose three.)
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Check if the tokens-per-minute (TPM) quota is throttling requests, causing queued delays.
Troubleshooting agent timeouts involves examining token limits, network latency, and model complexity.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Check if the tokens-per-minute (TPM) quota is throttling requests, causing queued delays.
Why this is correct
TPM throttling causes requests to queue or time out before processing.
- ✗
Double the model temperature to 2.0 to accelerate reasoning speed.
Why it's wrong here
Temperature does not impact execution speed or timeouts.
- ✗
Delete all vector indices to force local memory processing.
Why it's wrong here
Deleting vector indices breaks RAG functionality entirely.
- ✓
Inspect Application Insights telemetry to analyze execution duration per agent step and tool call latency.
Why this is correct
Application Insights provides granular performance tracing for agent steps and tool calls.
- ✓
Increase the client-side HTTP timeout threshold on the API request client.
Why this is correct
Long-running agentic reasoning loops often require extended client timeout settings.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Microsoft exam blueprint
This AI-103 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-103 exam.