AZ-204 Monitor, troubleshoot, and optimize Azure solutions Practice Test 4 — 15 Questions

Question 1

You are monitoring an Azure web application with Application Insights. You want to create a custom dashboard that shows the number of requests over time and the average server response time. Which Application Insights feature should you use to create this dashboard?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Metrics Explorer. Metrics Explorer in Application Insights is designed for visualizing pre-aggregated metrics like request count and server response time over time. It allows you to create custom charts and pin them to an Azure dashboard, making it the correct choice for this monitoring requirement.

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Log Analytics

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Application Map

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Smart Detection

Question 2

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'.

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appInsights.trackTrace

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appInsights.trackPageView

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appInsights.trackException

Question 3

You manage a web application hosted on Azure App Service. You need to monitor the application's availability from multiple geographic locations. The test should check that the homepage loads successfully and returns HTTP 200 within 5 seconds. You want to receive an alert if the test fails from any location. Which type of Application Insights test should you create?

Accepted Answer

URL ping test. The URL ping test is the correct choice because it is a simple, single-URL availability test that checks whether a specific endpoint (the homepage) returns HTTP 200 within a specified timeout (5 seconds). It can be configured to run from multiple geographic locations and trigger an alert on failure, meeting all requirements without the complexity of multi-step or custom code.

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Multi-step web test

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Custom availability test using TrackAvailability

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Continuous export test

Question 4

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.

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Application Insights Analytics (Log Analytics)

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Metrics Explorer

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Application Insights Profiler

Question 5

You need to analyze all exceptions that occurred in the last 24 hours from an application monitored by Application Insights. You want to group them by exception type, and for each type show the URL where it occurred and the count. Which Log Analytics Kusto query should you use?

Accepted Answer

exceptions | where timestamp > ago(24h) | summarize count() by type, url. The query filters exceptions from the last 24 hours using `timestamp > ago(24h)`, groups them by `type` (exception type) and `url` (the URL where the exception occurred), and then counts occurrences per group with `summarize count()`. This directly matches the requirement to show, for each exception type, the URL and the count.

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exceptions | where timestamp > ago(24h) | summarize count() by type, cloud_RoleInstance

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exceptions | where timestamp > ago(24h) | summarize count() by type, operation_Name

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exceptions | where timestamp > ago(24h) | summarize count() by type

Question 6

You are monitoring an Azure web application with Application Insights. You want to create a custom dashboard that shows the number of requests over time and the average server response time. Which Application Insights feature should you use to create this dashboard?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Use the 'Performance' blade under 'Investigate' in the Application Insights resource.. The 'Performance' blade in Application Insights provides a pre-built, optimized view that automatically aggregates request data by endpoint URL, displaying average response time and request count. It allows you to sort by average duration to quickly identify the top 5 slowest API endpoints over the last 7 days without writing any custom query.

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Use Log Analytics and run a query on the 'requests' table to aggregate by URL and sort by avg(duration).

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Use the 'Application Map' feature to visualize dependencies and endpoints.

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Configure Smart Detection to automatically identify slow API endpoints.

Question 7

You are monitoring a web application with Application Insights. The application occasionally returns HTTP 500 errors. You want to be notified immediately when the error rate exceeds 5% of all requests in a rolling 5-minute window. Which feature of Application Insights should you configure?

Accepted Answer

Create a log alert using a Kusto query that calculates the percentage of failed requests over the last 5 minutes, with an alert condition when the result exceeds 0.05.. A log alert using a Kusto query allows you to calculate the exact percentage of failed requests over a rolling 5-minute window and trigger when that percentage exceeds 0.05 (5%). This is the only option that supports a dynamic, percentage-based threshold on a rolling time window, which is required for the stated condition. Metric alerts on 'Failed requests' measure absolute counts, not percentages, and Smart Detection does not allow custom percentage thresholds.

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Create a Smart Detection rule for anomalous failures.

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Create a metric alert on the 'Failed requests' metric with a threshold of 5%.

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Create an availability test that checks for HTTP 200 responses and alert on failures.

Question 8

You are investigating a slow API call in your Azure web app. Application Insights shows that the request took 10 seconds. You need to view all the dependencies (database calls, external HTTP requests) that contributed to this request. What should you use?

Accepted Answer

Transaction Search. Transaction Search (now part of the 'Search' experience in Application Insights) allows you to query individual requests and drill into their correlated dependency calls, such as SQL queries or external HTTP requests, showing the exact duration and sequence of each dependency. This is the correct tool to identify which specific dependencies contributed to the 10-second request latency.

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Application Map

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Live Metrics

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Usage Analysis

Question 9

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.

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TrackEvent

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TrackMetric

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TrackDependency

Question 10

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.

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Metrics Explorer

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Application Map

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Live Metrics Stream

Question 11

You have a web application monitored by Application Insights. You want to receive an alert when the average server response time exceeds 2 seconds for a rolling 5-minute period. Which alert rule type should you create?

Accepted Answer

Application Insights metric alert on 'Server response time' with condition 'Greater than 2' and evaluation frequency 5 minutes. A metric alert on 'Server response time' is the correct choice because it continuously evaluates the average server response time over a rolling 5-minute window and triggers when the value exceeds 2 seconds. Metric alerts are designed for near-real-time monitoring of performance counters like response time, with a fixed evaluation frequency that matches the aggregation window, making them ideal for this scenario.

Answer

Log alert based on a Kusto query that measures average response time in 5-minute windows

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Smart Detection alert on response time degradation

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Availability test alert for HTTP response time

Question 12

You are monitoring an Azure web app using Application Insights. You need to create a query that returns the average duration of requests for each HTTP method (GET, POST, etc.) over the last hour, sorted by duration. Which Kusto query should you use?

Accepted Answer

requests | where timestamp > ago(1h) | summarize avg(duration) by method | order by avg_duration desc. It first filters requests to only those from the last hour using `where timestamp > ago(1h)`, then calculates the average duration grouped by HTTP method with `summarize avg(duration) by method`, and finally orders the results by the computed average duration in descending order using `order by avg_duration desc`. This matches the requirement exactly: last hour, average duration per method, sorted by duration.

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requests | summarize avg(duration) by method | order by avg_duration desc

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requests | summarize avg(duration) by method | sort by method asc

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requests | where timestamp > ago(1h) | summarize avg(duration) by method | sort by method

Question 13

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.

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Log alert

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Activity log alert

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Smart detection alert

Question 14

An Azure App Service application has slow API requests. The developer needs distributed tracing across requests and dependencies. What should be enabled?

Accepted Answer

Application Insights with dependency tracking. Application Insights with dependency tracking is the correct choice because it provides distributed tracing across requests and dependencies, enabling developers to correlate end-to-end transactions in a microservices or multi-component application. It automatically collects telemetry for HTTP calls, database queries, and other external service calls, which is essential for diagnosing slow API requests in an Azure App Service environment.

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Azure Policy compliance scan

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Storage account static website logs

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Cost Management budgets only

Question 15

Application Insights ingestion cost is rising because a high-traffic app emits large telemetry volume. The team needs statistically useful telemetry while reducing ingestion. What should be configured?

Accepted Answer

Adaptive sampling. Adaptive sampling is the correct solution because it automatically adjusts the volume of telemetry data sent to Application Insights, retaining only a representative subset that preserves statistical accuracy for analysis. This reduces ingestion costs while ensuring the sampled data remains statistically useful for detecting trends and anomalies in high-traffic applications.

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Move the app to a larger App Service plan

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Disable all exception telemetry

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Increase log verbosity to debug