AI-200 Security And Observability Practice Question
You are using Application Insights to monitor a Retrieval-Augmented Generation (RAG) application. You need to log custom dimensions such as prompt token counts and user IDs alongside standard telemetry. Which class should you use in your C# application?
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
✓
Use the TelemetryClient class and its TrackEvent method with a dictionary of custom dimensions.
The TelemetryClient class allows developers to track custom events, metrics, and traces with custom properties (dimensions).
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Configure the AzureMonitorLogExporter in the standard logging pipeline.
Why it's wrong here
While log exporters forward logs, TelemetryClient is specifically designed for structured custom event telemetry with dimensions.
- ✓
Use the TelemetryClient class and its TrackEvent method with a dictionary of custom dimensions.
Why this is correct
TelemetryClient.TrackEvent allows passing custom key-value pairs for rich analysis in Kusto queries.
- ✗
Use the DiagnosticSource class to emit unstructured string logs to Console.
Why it's wrong here
DiagnosticSource is low-level and does not automatically format custom dimensions for Application Insights analytics.
- ✗
Use the AzureKeyVaultClient to store transient custom properties.
Why it's wrong here
Azure Key Vault is for secrets management, not telemetry.
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-200 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-200 exam.