AZ-204 Practice Test 2 — 10 Questions

Question 1

You are building a serverless image-processing solution using Azure Functions. The function must automatically run whenever a new image is uploaded to a blob container and must scale out to handle high upload volumes. Which trigger and hosting plan should you use?

Accepted Answer

Blob trigger with Consumption plan. The Blob trigger is designed to automatically execute a function when a blob is created or updated in Azure Blob Storage, making it the correct choice for an image-processing solution that must run on new uploads. The Consumption plan provides automatic scaling to handle high upload volumes by allocating resources on demand, which aligns with the serverless, event-driven requirement.

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Timer trigger with Consumption plan

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HTTP trigger with Premium plan

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Queue trigger with App Service plan

Question 2

You are developing a solution that stores large media files in Azure Blob Storage. Users access these files frequently for the first 30 days, then rarely afterwards. To optimize costs, you need to automatically move blobs to a cooler tier after 30 days of creation. Which Azure feature should you use?

Accepted Answer

Lifecycle management policies. Azure Blob Storage lifecycle management policies allow you to automatically transition blobs to cooler tiers (e.g., from Hot to Cool) based on age or last modification time. By defining a rule that moves blobs to the Cool tier 30 days after creation, you optimize storage costs for frequently accessed files that become rarely used. This feature is purpose-built for automating tier transitions without manual intervention or custom code.

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Blob inventory

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Change feed

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Immutable storage

Question 3

You are monitoring an ASP.NET Core web API with Application Insights. You want to view the SQL queries being executed, including the command text and duration, in the Application Insights portal. Which actions must you take? (Select all that apply.) (Choose 2.)

Accepted Answer

Install the `Microsoft.ApplicationInsights.DependencyCollector` NuGet package.. Option B is correct because the `Microsoft.ApplicationInsights.DependencyCollector` NuGet package is required to automatically collect dependency telemetry, including SQL Server calls. Without this package, Application Insights will not capture SQL dependency data at all. Option C is correct because even with the dependency collector installed, SQL command text is not collected by default for security reasons; you must explicitly set `EnableSqlCommandTextInstrumentation` to `true` in the `DependencyTrackingTelemetryModule` configuration to view the actual SQL queries and their duration in the portal.

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Install the `Microsoft.ApplicationInsights.Profiler.AspNetCore` NuGet package.

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Enable adaptive sampling to ensure all SQL queries are collected.

Question 4

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.

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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 5

An Azure Function processes events from Event Hubs. You need to monitor the number of events that were successfully processed and those that were dropped due to processing errors. Which approach should you use?

Accepted Answer

Custom metrics in Application Insights.. Custom metrics in Application Insights allow you to track business-specific counters like successfully processed events and dropped events directly from your Azure Function code. By using the `TelemetryClient.TrackMetric()` API within the function's event processing logic, you can increment counters for success and failure scenarios, giving you precise, real-time monitoring of processing outcomes. This approach is more granular than built-in metrics because it reflects your application's custom error handling, not just infrastructure-level throughput.

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Event Hubs metrics.

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Stream Analytics job.

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Log Analytics query on function logs.

Question 6

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.. Option C is correct because 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 7

You need to diagnose a slow-performing Azure Function. Application Insights shows that the function's dependency calls to an external API take an unusually long time. Which Application Insights feature should you use to visualize the end-to-end request flow?

Accepted Answer

Application Map. Application Map is the correct feature because it provides a visual representation of the end-to-end request flow across distributed components, including dependency calls to external APIs. It shows the latency and failure rates for each dependency, allowing you to pinpoint where the slowdown occurs in the overall transaction.

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Metrics Explorer

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Live Metrics Stream

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Smart Detection

Question 8

You are implementing an Azure Durable Functions application that processes orders. The function must call three external APIs (payment gateway, inventory system, and shipping calculator) in parallel, then aggregate the results once all three have completed. Which Durable Functions pattern should you use?

Accepted Answer

Fan-out/Fan-in. The Fan-out/Fan-in pattern is designed exactly for this scenario: it triggers multiple function tasks in parallel (fan-out) and then aggregates their results once all complete (fan-in). In Durable Functions, this is implemented using `CallActivityAsync` in a loop with `Task.WhenAll` to wait for all parallel activities to finish, allowing the orchestrator to collect and process the combined results.

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Function chaining

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Monitor

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Human interaction

Question 9

You are monitoring an Azure App Service using Application Insights. You notice that HTTP 500 errors are increasing, but the standard server response time metric remains normal. You suspect that the errors are occurring in an external API call made by the application. How can you identify the dependency that is failing?

Accepted Answer

Configure Application Insights dependency tracking and view the Dependency Metrics blade.. Option C is correct because Application Insights dependency tracking automatically monitors HTTP calls, SQL queries, and other external dependencies made by your application. By viewing the Dependency Metrics blade, you can see failure rates, durations, and dependency names, allowing you to identify which external API call is failing without modifying code.

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Enable snapshot debugging for the application.

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Use Application Insights Profiler to capture code-level traces.

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Set up a custom event telemetry for each external call.

Question 10

You are monitoring an Azure Web App with Application Insights. You notice that certain requests have high server response times. You need to identify which specific database queries are causing the delays. Which Application Insights feature should you use?

Accepted Answer

Application Insights Profiler. Application Insights Profiler is the correct feature because it provides detailed, code-level diagnostics for requests with high server response times, including per-operation breakdowns of database query durations. It captures execution traces that show exactly which SQL queries or external calls are contributing to latency, enabling you to pinpoint the specific database queries causing delays.

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Live Metrics Stream

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Performance blade

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Application Map