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

Question 1

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

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

Accepted Answer

Standard test. A Standard test (also known as a URL ping test) is the correct choice because it is the simplest availability test in Application Insights, designed to check that a single URL returns an HTTP 200 response within a specified timeout (here, 5 seconds). It can be configured to run from multiple geographic locations, and you can set an alert to fire if any location reports a failure, meeting the requirement exactly. In the Azure portal, this test type is explicitly named 'Standard test'.

Answer

Availability test (URL ping test)

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Multi-step web test

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Custom metric test

Question 2

You are monitoring an Azure web application with Application Insights. You need to identify the top 5 slowest API endpoints over the last 7 days. The results should show the endpoint URL, average response time, and request count. Which feature or query should you use?

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 3

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%.

Answer

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

Question 4

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 5

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

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TrackMetric

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TrackDependency

Question 6

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

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Application Map

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Live Metrics Stream

Question 7

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 8

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 9

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 10

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 11

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.

Answer

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

Question 12

A developer needs to run a Kusto query against application request data to identify 95th percentile latency by operation. Where should the query be run?

Accepted Answer

Logs in Application Insights or the associated Log Analytics workspace. Application Insights stores application request data, including latency metrics, and supports Kusto queries via its Logs blade. The associated Log Analytics workspace also provides the same query capabilities, making it the correct location to run a Kusto query for 95th percentile latency by operation.

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Microsoft Entra audit logs

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Azure Key Vault diagnostic settings

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Azure Resource Graph only

Question 13

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.

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A public IP address on the app

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A manually exported CSV report

Question 14

An Azure App Service application has availability failures. 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 in an Azure App Service application. It automatically collects telemetry data, including end-to-end transaction details, and maps dependencies like SQL databases, HTTP calls, and Azure services, enabling developers to diagnose availability failures by correlating traces across components.

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Storage account static website logs

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Azure Policy compliance scan

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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? The design must avoid adding custom operational scripts.

Accepted Answer

Adaptive sampling. Adaptive sampling is the correct solution because it automatically adjusts the volume of telemetry data collected from your application, ensuring that only a representative fraction of events is sent to Application Insights while preserving statistical accuracy for analysis. This reduces ingestion costs without requiring custom scripts or manual intervention, as it is a built-in feature of the Application Insights SDK that dynamically adapts based on traffic patterns.

Answer

Move the app to a larger App Service plan

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Disable all exception telemetry

Answer

Increase log verbosity to debug