AZ-400 Question 300
Single answerYour DevOps team manages a microservices-based application running on Azure Kubernetes Service (AKS). You have enabled Azure Application Insights for each microservice to collect telemetry data, including usage and performance metrics such as request rate, response time, and failure rate. The product owner now wants to quickly pinpoint performance bottlenecks across these microservices and detect anomalies that affect critical services. Which Azure Monitor feature should you use to query and analyze telemetry from all microservices in near real time from a single location?
- A
A. Use Azure Monitor Metrics Explorer to view metrics from each microservice individually and aggregate the data.
- B
B. Use Azure Monitor Logs (Log Analytics) with Kusto Query Language (KQL) to query and correlate the telemetry across all microservices.
- C
C. Use the Application Insights Profiler to capture and analyze performance traces in real time for each microservice.
- D
D. Use Azure Monitor for Containers to analyze container resource usage and generate service-level performance dashboards.
Show answer and explanation
Correct answer: B
Explanation
Azure Monitor Logs (Log Analytics) is the recommended approach when you need to correlate, filter, and analyze large volumes of telemetry from multiple distributed services. By using Kusto Query Language (KQL), you can find patterns, identify anomalies, and troubleshoot performance issues or error spikes in near real time. Refer to the Microsoft documentation on Azure Monitor Logs (https://docs.microsoft.com/azure/azure-monitor/logs/) for best practices on creating and running KQL queries across Application Insights data.
- A. Incorrect.
A. This option partially addresses metrics visualization but is limited to pre-aggregated metrics and does not provide the ad-hoc query and cross-service correlation power of Log Analytics.
- B. Correct.
B. Correct. Azure Monitor Logs (formerly known as Log Analytics) allows you to run KQL queries that correlate telemetry (requests, dependencies, failures, etc.) across multiple services. This provides near real-time, interactive analysis and investigation of performance anomalies.
- C. Incorrect.
C. While Profiler helps identify code-level performance issues, it is not suitable for simultaneously querying and aggregating across multiple microservices' telemetry data in broad investigations.
- D. Incorrect.
D. Azure Monitor for Containers focuses on container resource metrics (CPU, memory, etc.) rather than providing detailed, cross-service telemetry correlation and usage metrics analysis.