AZ-204 Practice Test 7 — 10 Questions

Question 1

You are debugging a performance issue in a live web application monitored by Application Insights. You need to see real-time metrics such as request rate, response times, and any exceptions as they occur, without waiting for the usual telemetry pipeline. Which Application Insights feature should you use?

Accepted Answer

Live Metrics Stream. Live Metrics Stream (option B) is the correct feature because it provides real-time, low-latency telemetry directly from the Application Insights SDK, bypassing the usual ingestion pipeline. This allows you to monitor request rate, response times, and exceptions as they occur, which is exactly what the scenario requires for debugging a live performance issue without waiting for data to be processed.

Answer

Application Insights Analytics (Log Analytics)

Answer

Metrics Explorer

Answer

Application Insights Profiler

Question 2

A production API needs proactive alerting for unexpected exceptions. Which two elements are required for a useful Azure Monitor alert?

Accepted Answer

A signal or metric/log query that detects the condition. A is correct because an Azure Monitor alert requires a signal (such as a metric, log query, or activity log event) to define the condition that triggers the alert. Without a signal, the alert has no basis for evaluation, making it impossible to detect unexpected exceptions proactively.

Answer

A public IP address on the app

Answer

A manually exported CSV report

Question 3

You are using Application Insights to monitor a web application. You notice that a specific request is slow. You want to see the complete end-to-end transaction details, including all dependency calls and exceptions for that single request. Which feature should you use?

Accepted Answer

Transaction Search (End-to-End Transaction Details). Transaction Search (End-to-End Transaction Details) is the correct feature because it allows you to view the complete trace of a single request, including all dependency calls (e.g., SQL, HTTP, Azure services), exceptions, and logs associated with that specific operation. This is achieved by correlating telemetry using the operation_Id field, which groups all telemetry items from the same request into a single end-to-end view. Other features like Metrics Explorer or Application Map provide aggregated or topological views, not per-request drill-down.

Answer

Metrics Explorer

Answer

Application Map

Answer

Live Metrics Stream

Question 4

You are developing a web API that must authenticate requests using Microsoft Entra ID (Microsoft Entra ID) and OAuth 2.0 bearer tokens. You want to validate the token in your API code. Which library should you use?

Accepted Answer

Microsoft.Identity.Web. Microsoft.Identity.Web is the recommended library for integrating ASP.NET Core web APIs with Microsoft Entra ID. It provides built-in token validation, policy enforcement, and handles the OAuth 2.0 bearer token flow, including JWT validation, issuer signing keys, and audience checks, without requiring manual configuration of middleware.

Answer

Microsoft Authentication Library (MSAL)

Answer

ADAL.NET

Answer

Azure.Identity

Question 5

You are using Application Insights to monitor a web application. The business team wants to track how many users click a specific button on the page. You need to send custom telemetry data from the client-side JavaScript. Which Application Insights JavaScript SDK method should you call?

Accepted Answer

appInsights.trackEvent. The correct method is `trackEvent` because it is specifically designed for capturing user interactions, such as button clicks, as custom events in Application Insights. Unlike other methods, `trackEvent` allows you to attach custom properties and measurements, making it ideal for business metrics like click tracking. This method sends the data as a custom event telemetry item, which can be analyzed in the Azure portal under 'Events'.

Answer

appInsights.trackTrace

Answer

appInsights.trackPageView

Answer

appInsights.trackException

Question 6

You are monitoring an e-commerce application with Application Insights. You need to analyze all exceptions that occurred in the last 24 hours, grouped by the exception type. You also need to include the URL where each exception was triggered and the number of times each type occurred. Which Log Analytics Kusto query should you use?

Accepted Answer

exceptions | where timestamp > ago(24h) | join kind=inner requests on operation_Id | extend exceptionType = tostring(innermostType) | summarize Count=count() by exceptionType, url. Option A is correct because it uses the `exceptions` table to filter exceptions from the last 24 hours, joins with the `requests` table on `operation_Id` to correlate each exception with the request URL, and then summarizes the count by exception type (extracted from `innermostType`) and URL. This meets all requirements: grouping by exception type, including the URL, and counting occurrences.

Answer

exceptions | where timestamp > ago(24h) | extend exceptionType = tostring(customDimensions.['ExceptionType']) | summarize Count=count() by exceptionType, url = tostring(customDimensions.['Url'])

Answer

requests | where timestamp > ago(24h) and success == false | extend exceptionType = tostring(resultCode) | summarize Count=count() by exceptionType, url

Answer

exceptions | where timestamp > ago(24h) | extend exceptionType = tostring(innermostType) | summarize Count=count() by exceptionType

Question 7

You are using Application Insights to monitor a web app. You want to automatically analyze and alert on sudden increases in request failure rates, without manually setting static thresholds. Which Application Insights feature should you use?

Accepted Answer

Smart Detection. Smart Detection in Application Insights automatically analyzes telemetry from your web app to detect anomalies, such as sudden increases in request failure rates, without requiring manual static thresholds. It uses machine learning models to adapt to your app's normal behavior and alert on deviations, making it ideal for dynamic monitoring scenarios.

Answer

Application Insights Profiler

Answer

Live Metrics Stream

Answer

Continuous Export

Question 8

You need to emit a custom metric in Application Insights that tracks the number of page views per browser. You expect high volume (millions of events per day). Which API should you use to ensure efficient pre-aggregation and avoid performance issues?

Accepted Answer

GetMetric. C is correct because the GetMetric API (previously known as Pre-Aggregated Metric API) is designed for high-volume telemetry scenarios. It pre-aggregates metrics on the client side before sending them to Application Insights, significantly reducing network traffic and storage costs while avoiding performance bottlenecks from millions of individual events.

Answer

TrackEvent

Answer

TrackMetric

Answer

TrackDependency

Question 9

You are using Application Insights to monitor an ASP.NET Core web API. Users report that a specific endpoint is slow, but you cannot reproduce the issue in development. You need to identify which line of code is causing the delay in production. Which Application Insights feature should you use?

Accepted Answer

Enable Application Insights Profiler.. Application Insights Profiler is designed specifically to trace code-level performance issues in production without requiring code changes or reproducing the problem. It captures detailed call stacks and timing for each request, allowing you to identify exactly which line of code is causing the delay. This makes it the correct choice for diagnosing a slow endpoint that cannot be reproduced in development.

Answer

Use the Application Insights Map to visualize dependencies.

Answer

Use the Snapshot Debugger to capture debug snapshots on exceptions.

Answer

Create a custom telemetry event in the slow endpoint to log timing data.

Question 10

You have an App Service web app with Application Insights configured. You want to create an alert that fires when the server response time exceeds 2 seconds for a rolling 10-minute window. Which type of alert rule should you create?

Accepted Answer

Metric alert. Metric alerts in Azure Monitor evaluate resource-level performance counters at regular intervals, making them ideal for threshold-based conditions like server response time. Application Insights automatically collects server response time as a pre-aggregated metric, so a metric alert can check whether the average exceeds 2 seconds over a rolling 10-minute window without needing to query raw log data.

Answer

Log alert

Answer

Activity log alert

Answer

Smart detection alert