AZ-400 Implement an instrumentation strategy Practice Question
A company runs a critical microservices application on Azure Kubernetes Service (AKS). They need to implement distributed tracing across services using Application Insights. Which three actions should be performed?
⚠ Common exam trap
Candidates often confuse infrastructure monitoring (Container Insights) with application-level distributed tracing, leading candidates to select options that collect metrics but fail to provide the cross-service correlation needed for distributed tracing.
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 OpenTelemetry SDK with Application Insights exporter
Distributed tracing requires every microservice to emit trace data. This can be achieved by instrumenting each service with the Application Insights SDK (option C) or using OpenTelemetry SDK with the Application Insights exporter (option B). To ensure all spans from different services are correlated into a single distributed trace, all services must use the same instrumentation key so telemetry lands in the same Application Insights resource (option D). Option A is incorrect because the Application Insights agent is not deployed as a DaemonSet for this purpose, and option E is incorrect because Container Insights is for infrastructure monitoring, not application-level distributed tracing.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Deploy the Application Insights agent as a DaemonSet on each AKS node
Why it's wrong here
The Application Insights agent deployed as a DaemonSet collects node-level performance metrics and host counters, but it does not perform distributed tracing because it cannot propagate context or track dependencies across microservice calls.
- ✓
Use OpenTelemetry SDK with Application Insights exporter
Why this is correct
OpenTelemetry SDKs instrument application code to generate standardized distributed traces with context propagation, and the Application Insights exporter sends that telemetry to Azure Monitor, allowing end-to-end correlation and analysis across microservices.
- ✓
Instrument each microservice with the Application Insights SDK
Why this is correct
Instrumenting each microservice with the Application Insights SDK automatically captures incoming and outgoing HTTP calls, dependencies, and custom metrics, correlating them via operation IDs to build a distributed trace that spans all services.
- ✓
Set the same instrumentation key for all microservices
Why this is correct
Setting the same instrumentation key for all microservices directs all telemetry into a single Application Insights resource, enabling traces to be correlated across services through the shared operation ID and providing a unified end-to-end view.
- ✗
Enable Azure Monitor Container Insights on the AKS cluster
Why it's wrong here
Azure Monitor Container Insights collects performance metrics, container inventory, and logs from AKS into a Log Analytics workspace, but it does not support distributed tracing or correlate individual requests across microservices, so it cannot meet the tracing requirement.
Go deeper
Related to this question
Learn chapter
Introduction to DevOps and Azure DevOps
Key term
Telemetry
Telemetry is the automatic collection, transmission, and measurement of data from remote sources to a central system for analysis and monitoring.
Key term
Distributed tracing
Distributed tracing is a method used to track and observe requests as they flow through multiple services in a distributed system, helping identify performance bottlenecks and failures.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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