AZ-400 Implement an instrumentation strategy Practice Test 2 — 15 Questions

Question 1

A company deploys a web application to Azure App Service. They want to monitor application performance and detect anomalies using Application Insights. Which two components should be configured?

Accepted Answer

Configure sampling to reduce data volume. Sampling in Application Insights reduces the volume of telemetry data while preserving statistically correct analysis, which is essential for managing cost and performance in high-traffic applications. Option D is correct because the application-side SDK (e.g., Application Insights SDK for .NET, Java, or Node.js) is required to instrument the code and collect detailed telemetry such as requests, dependencies, and exceptions for performance monitoring and anomaly detection.

Answer

Deploy the Azure Monitor agent on the App Service instance

Answer

Create a Log Analytics workspace and configure data collection rules

Answer

Enable diagnostics settings to stream logs to Event Hubs

Question 2

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?

Accepted Answer

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

Deploy the Application Insights agent as a DaemonSet on each AKS node

Answer

Enable Azure Monitor Container Insights on the AKS cluster

Question 3

A company deploys a .NET Core web application to Azure App Service. The application uses Application Insights for monitoring. The operations team reports that dependency tracking is missing for calls to a third-party REST API made using HttpClient. The application is instrumented with the Application Insights SDK. Which action should be taken to enable dependency tracking for HttpClient calls?

Accepted Answer

Ensure the SDK is configured using services.AddApplicationInsightsTelemetry(); in the Startup.cs file.. `services.AddApplicationInsightsTelemetry()` in `Startup.cs` automatically registers the `DependencyTrackingModule` for .NET Core applications. This module collects dependency telemetry for `HttpClient` calls made via `IHttpClientFactory` or typed `HttpClient` instances, provided the SDK is properly configured. Since the application already uses the Application Insights SDK, this single line enables automatic dependency tracking without additional packages or agents.

Answer

Install the Application Insights Agent on the App Service instance.

Answer

Add a reference to Microsoft.ApplicationInsights.DependencyCollector and call DependencyTrackingModule.Initialize().

Answer

Use the Application Insights Status Monitor to enable dependency tracking.

Question 4

A company uses Azure Monitor and Application Insights to monitor a microservices application deployed on Azure Kubernetes Service (AKS). The development team wants to implement distributed tracing to correlate requests across services. They currently have Application Insights SDKs instrumented in each service. Which TWO configurations are required to enable end-to-end distributed tracing?

Accepted Answer

Ensure all services use the same Application Insights instrumentation key or connection string.. All services must share the same Application Insights instrumentation key or connection string to ensure that telemetry from different microservices is correlated into a single application map and trace. Without a common instrumentation key, the distributed trace data would be siloed across separate Application Insights resources, preventing end-to-end correlation.

Answer

Enable the Live Metrics Stream feature in Application Insights.

Answer

Configure adaptive sampling in the Application Insights SDK.

Answer

Enable Application Map in the Azure portal for each service.

Question 5

Drag and drop the steps to configure Azure DevOps artifact feeds for NuGet packages into the correct order.

Accepted Answer

Step 1: Create a new feed, Step 2: Configure upstream sources, Step 3: Set feed permissions, Step 4: Publish NuGet packages, Step 5: Consume packages from feed. Feed setup starts with creation, upstream sources, permissions, publishing, and consumption.

Answer

Step 1: Create a new feed, Step 2: Set feed permissions, Step 3: Configure upstream sources, Step 4: Publish NuGet packages, Step 5: Consume packages from feed

Answer

Step 1: Create a new feed, Step 2: Publish NuGet packages, Step 3: Configure upstream sources, Step 4: Set feed permissions, Step 5: Consume packages from feed

Answer

Step 1: Create a new feed, Step 2: Configure upstream sources, Step 3: Publish NuGet packages, Step 4: Set feed permissions, Step 5: Consume packages from feed

Question 6

Match each Azure DevOps security concept to its purpose.

Accepted Answer

Azure Active Directory: Used for identity and access management, including authentication to Azure DevOps.. Azure AD manages user identities; PATs authenticate scripts; Service Principals authenticate automated services; Security Groups manage user permissions. Common confusions include mixing the roles of Azure AD and Service Principals, or PATs with Security Groups.

Answer

Azure Active Directory: Used to authenticate automated pipelines to Azure resources.

Answer

Personal Access Token (PAT): Used to manage permissions for groups of users.

Question 7

Your team uses Azure Pipelines to deploy a Node.js application. Recently, deployments have been failing intermittently due to a missing npm package. The pipeline runs successfully on the local agent but fails on the hosted agent. Which instrumentation strategy should you implement to identify the root cause?

Accepted Answer

Enable verbose logging for the npm install task and compare the output between pipeline runs.. Enabling verbose logging for the npm install task allows you to see detailed output of package resolution and installation steps. By comparing the logs between the local agent (success) and hosted agent (failure), you can identify differences in npm registry availability, package versions, or authentication issues that cause the intermittent missing package. Option A is wrong because self-hosted agents might not match the hosted environment's configuration, and the goal is to diagnose the problem on hosted agents. Option B is wrong because Application Insights monitors application runtime behavior, not build-time dependency installation. Option D is wrong because pipeline caching would reuse previously installed packages, which could mask the problem by not performing a fresh install, and does not help identify why the package is missing on hosted agents.

Answer

Replace the hosted agent with a self-hosted agent.

Answer

Configure Application Insights for the Node.js app to monitor runtime errors.

Answer

Add a pipeline cache task for npm packages to ensure consistent restore.

Question 8

You are designing an instrumentation strategy for a microservices application deployed to Azure Kubernetes Service (AKS) using Azure Pipelines. The application emits custom metrics using OpenTelemetry. You need to ensure that all pipeline-related events (build, release, and test results) are correlated with application telemetry to enable end-to-end traceability. What should you do?

Accepted Answer

Set a unique Correlation ID in the pipeline variables and pass it to the application's OpenTelemetry instrumentation as a span attribute.. Setting a unique Correlation ID in pipeline variables and passing it as a span attribute to OpenTelemetry allows end-to-end traceability by linking pipeline events with application telemetry. Option A is incorrect because Application Insights can ingest pipeline telemetry, but that alone does not correlate with application telemetry; you need a shared correlation ID. Option B is wrong because storing pipeline logs in Log Analytics and querying with metrics does not provide real-time correlation at the span level. Option C is incorrect because deployment gates based on application metrics do not create correlation; they only block deployments based on conditions.

Answer

Configure Application Insights to ingest pipeline telemetry via a custom exporter.

Answer

Store pipeline logs in an Azure Log Analytics workspace and query them together with application metrics.

Answer

Use Azure Pipelines' Checks feature to enforce deployment gates based on application metrics.

Question 9

Your team uses GitHub Actions for CI/CD. You need to collect and analyze build and deployment logs centrally to identify recurring failures. Which service should you use to ingest and query these logs?

Accepted Answer

Azure Log Analytics. Azure Log Analytics is the correct service for centralizing and querying logs from GitHub Actions. It can ingest logs via connectors or API, enabling analysis of build and deployment logs to identify recurring failures. Azure Monitor Alerts (A) is for setting up alerts, not for storing or querying logs. GitHub Insights (C) provides reporting and analytics for GitHub repositories but is not designed for custom log querying from CI/CD pipelines. Application Insights (D) focuses on application performance monitoring and telemetry, not CI/CD pipeline logs.

Answer

Azure Monitor Alerts

Answer

GitHub Insights

Answer

Application Insights

Question 10

Your organization uses Azure Pipelines with multiple release stages. You need to instrument the pipeline to capture the duration of each stage and the number of failed tasks. Which TWO approaches should you use?

Accepted Answer

Use the Azure DevOps REST API to retrieve pipeline run statistics after each run.. Options D and E are correct. The goal is to capture stage duration and failed task counts. Option D uses the Azure DevOps REST API to programmatically retrieve pipeline run statistics, which includes stage-level durations and failure information. Option E adds a script task at the end of each stage that logs the stage's duration and task results to a custom log file, providing direct instrumentation. Option A is incorrect because pipeline notifications only alert on failures, they don't capture or log durations. Option B is incorrect because 'runOnce' is a deployment strategy that ensures sequential stages, not an instrumentation method. Option C is incorrect because the 'Summary' tab in the pipeline run provides a high-level overview, not detailed per-stage duration data that can be programmatically captured.

Answer

Configure pipeline notifications for failed tasks.

Answer

Implement a 'runOnce' deployment strategy to ensure sequential stages.

Answer

Enable the 'Summary' tab in the pipeline run to view stage durations.

Question 11

You are building a comprehensive instrumentation strategy for a large-scale Azure DevOps environment. You need to ensure that all pipeline events (build, release, test) are automatically tracked and correlated with application performance data. Which THREE components should you include?

Accepted Answer

A shared Correlation ID that flows from pipeline to application.. Options A, C, and E are correct. A shared Correlation ID (A) flows from pipeline to application, enabling end-to-end trace correlation. Custom pipeline tasks (C) send telemetry (e.g., build/release events) to Application Insights. The OpenTelemetry SDK (E) emits trace context from the application, which can include the correlation ID. Option B is wrong because Azure Monitor Workbooks are visualization tools, not data collection components. Option D is wrong because Azure Boards is for work item tracking, not pipeline event capture.

Answer

Azure Monitor Workbooks to visualize pipeline data.

Answer

Azure Boards to track pipeline run metadata.

Question 12

Refer to the exhibit. You deploy this ARM template to create a Log Analytics workspace and a saved search. After deployment, you notice that the saved search returns no results even though there are failed pipeline runs. What is the most likely reason?

Accepted Answer

The custom table 'AzureDevOpsPipelineEvents_CL' does not exist in the workspace.. The query uses a custom log table 'AzureDevOpsPipelineEvents_CL' which requires a custom table or data connector to be created first. Option A is wrong because the savedSearch API version is valid. Option B is wrong because the workspace API version is valid. Option D is wrong because the category is just a label.

Answer

The savedSearch API version is not supported.

Answer

The Log Analytics workspace API version is incorrect.

Answer

The category 'Azure Pipelines' is misspelled.

Question 13

You need to monitor the health of your Azure Pipeline agents. Which Azure DevOps Analytics view should you use to identify agents that have not reported in the last hour?

Accepted Answer

Agent Health dashboard. The Agent Health dashboard in Azure DevOps provides real-time status of pipeline agents, including their last communication timestamp. By filtering for agents that have not reported in the last hour, you can identify unhealthy or disconnected agents. This dashboard directly surfaces agent connectivity and health metrics. Note that this is a dashboard, not an Analytics view like Release Analytics, Test Analytics, or Pipeline Run Analytics.

Answer

Release Analytics

Answer

Test Analytics

Answer

Pipeline Run Analytics

Question 14

You are deploying a Java application to Azure App Service using Azure Pipelines. You want to automatically capture JVM metrics (heap usage, garbage collection) and correlate them with deployment events. What should you do?

Accepted Answer

Enable Application Insights Java agent in the App Service.. The Application Insights Java agent automatically captures JVM metrics such as heap usage and garbage collection, and it integrates with Azure Pipelines to correlate deployment events with these metrics. Option A is incorrect because Azure Monitor diagnostic settings capture Azure platform logs, not application-level JVM metrics. Option C is incorrect because the Visual Studio profiler is designed for local or development debugging, not for automatic production monitoring. Option D is incorrect because diagnostic logs for stdout/stderr capture application output, not JVM internals.

Answer

Use Azure Monitor diagnostic settings for the App Service.

Answer

Attach a profiler from Visual Studio to the App Service process.

Answer

Configure App Service diagnostic logs to capture stdout/stderr.

Question 15

You are the DevOps lead for a fintech company. The organization uses a multi-tenant Azure DevOps environment with hundreds of pipelines. The compliance team requires that every pipeline run must be auditable with the following attributes captured: who triggered the run, what code changes were included, which artifacts were produced, and whether any secrets (e.g., Azure Key Vault references) were accessed during the run. Additionally, all audit data must be retained for 7 years and be queryable within 5 minutes of a pipeline completion. Current state: pipelines use Azure Key Vault for secrets, and YAML pipelines are defined with variables referencing Key Vault. You need to design an instrumentation strategy to meet these requirements. What should you do?

Accepted Answer

Enable Azure DevOps Audit Streams to send audit events to a Log Analytics workspace. Configure a Log Analytics workspace with 7-year retention. Create a dashboard and alert rules for compliance.. Using Azure DevOps Audit Streams to send events to a Log Analytics workspace provides long-term retention and near real-time querying. Azure DevOps Audit logs capture all required attributes including pipeline runs, secret access, and user identity. Option B is incorrect because Azure Event Grid subscription to pipeline run events does not provide long-term retention and querying capabilities; it is event-driven delivery. Option C is incorrect because adding a step to upload pipeline logs as artifacts does not capture the audit trail of who triggered the run or whether secrets were accessed. Option D is incorrect because instrumenting pipelines with custom tasks sending telemetry to Application Insights is for application telemetry, not pipeline audit, and does not capture all required attributes.

Answer

Use Azure Event Grid to subscribe to pipeline run events and store them in Azure Cosmos DB with TTL for 7 years.

Answer

Add a step at the end of each pipeline to upload pipeline logs as pipeline artifacts with a retention policy of 7 years.

Answer

Instrument each pipeline with custom tasks that send telemetry to Application Insights. Set Application Insights to 7-year retention.