AZ-204 Develop Azure compute solutions Practice Test 10 — 15 Questions

Question 1

Your Azure Function app uses an event-driven architecture with Azure Event Hubs. You need to ensure that if the function fails to process an event, the event is retried up to three times and then sent to a dead-letter queue. What should you configure?

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

Accepted Answer

Configure the retry policy in the function's host.json file.. Azure Functions for Event Hubs supports a built-in retry policy configured in the host.json file. This policy allows you to specify the maximum number of retries (e.g., 3) and, after exhausting those retries, the event is automatically sent to a dead-letter queue (DLQ) configured on the Event Hub. This approach is declarative and requires no custom code for retry or dead-lettering logic.

Answer

Use Durable Functions to orchestrate retries and dead-lettering.

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Implement a try-catch block in the function code and manually re-queue the event.

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Set the 'enableRetry' property on the Event Hub namespace.

Question 2

You deploy the above ARM template resource. After deployment, the web app cannot connect to Application Insights. The Application Insights resource exists in the same region. What is the most likely cause?

Accepted Answer

The app setting 'APPINSIGHTS_INSTRUMENTATIONKEY' is deprecated; you should use 'APPLICATIONINSIGHTS_CONNECTION_STRING' instead.. The ARM template likely sets the 'APPINSIGHTS_INSTRUMENTATIONKEY' app setting, which is deprecated. Application Insights now requires the 'APPLICATIONINSIGHTS_CONNECTION_STRING' app setting for authentication and telemetry ingestion, as the instrumentation key alone is no longer sufficient for newer SDK versions and regional endpoints.

Answer

The dependsOn is incorrect; it should reference the Application Insights resource ID.

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The web app needs a user-assigned managed identity to access Application Insights.

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The instrumentation key must be set under a different name, like 'APPINSIGHTS_KEY'.

Question 3

You are designing a solution that uses Azure Container Instances (ACI) to run a batch processing job. The job is expected to run for up to 2 hours. You need to minimize costs. Which ACI configuration should you use?

Accepted Answer

Use a container group with a restart policy of 'OnFailure' or 'Never'.. Setting the restart policy to 'OnFailure' or 'Never' ensures that the container does not restart after the batch job completes, avoiding unnecessary compute charges. ACI bills per second of container runtime, so any idle or restarted container time directly increases cost. For a finite batch job, a restart policy that prevents automatic restarts is the most cost-effective choice.

Answer

Use GPU-enabled containers for faster processing.

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Deploy the container group in a virtual network.

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Use a container group with a restart policy of 'Always'.

Question 4

Your company has an Azure App Service web app that runs on a Standard App Service plan. You need to scale out the app to handle increased traffic during business hours and scale in during off-hours. What should you configure?

Accepted Answer

Configure autoscale rules on the App Service plan to scale out and in based on CPU usage.. Azure App Service autoscale rules allow you to automatically scale out (increase instance count) and scale in (decrease instance count) based on metrics like CPU usage. This meets the requirement to handle increased traffic during business hours and reduce costs during off-hours without manual intervention. Autoscale is configured at the App Service plan level, not the web app itself, and works with the Standard tier and above.

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Manually increase the instance count during business hours.

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Scale up the App Service plan to a Premium plan.

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Use Azure Traffic Manager to distribute load.

Question 5

You deploy the above ARM template resource for a web app. The web app reads the connection string from the 'DefaultConnection' name. However, the web app fails to connect to the database with an error 'Login failed for user 'myuser'. What is the most likely cause?

Accepted Answer

The SQL server is configured to use Microsoft Entra authentication only, not SQL authentication.. The login failure indicates that the SQL server does not accept SQL authentication. If the server is configured for Microsoft Entra authentication only, then SQL login credentials (username/password) will fail. Option A is incorrect because the user ID may exist but authentication method is wrong. Option B is incorrect because 'SQLAzure' is the correct connection string type for Azure SQL Database. Option D is incorrect because 'Trusted_Connection=True' is for Windows authentication, not applicable to Azure SQL.

Answer

The user ID does not have access to the database.

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The connection string type should be 'SQLServer' instead of 'SQLAzure'.

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The connection string is missing 'Trusted_Connection=True;'.

Question 6

You are developing a solution that uses Azure Container Apps. Your application is a microservice that needs to expose a gRPC endpoint. The service must scale to zero when idle. What should you do?

Accepted Answer

Deploy the microservice to Azure Container Apps and configure a scale rule with minReplicas set to 0.. Azure Container Apps natively supports gRPC endpoints and can scale to zero by setting `minReplicas` to 0 in a scale rule. This configuration allows the microservice to run only when there are active requests, reducing costs during idle periods. The combination of gRPC support and dynamic scaling makes Container Apps the correct choice for this scenario.

Answer

Use Azure Functions with a gRPC trigger.

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Deploy the microservice to Azure Kubernetes Service with a virtual node.

Answer

Deploy the microservice to Azure Container Instances with a scale rule.

Question 7

A company deploys a microservices application on Azure Kubernetes Service (AKS). They need to automatically scale individual microservices based on custom metrics (e.g., queue depth). Which feature should they use?

Accepted Answer

Horizontal Pod Autoscaler. The Horizontal Pod Autoscaler (HPA) is the correct choice because it automatically scales the number of pod replicas in a deployment or replica set based on observed metrics, including custom metrics like queue depth. HPA queries the Kubernetes Metrics API, which can be extended with custom metrics adapters (e.g., Prometheus Adapter) to support application-specific metrics, enabling fine-grained scaling for each microservice.

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Virtual Node

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Vertical Pod Autoscaler

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Cluster Autoscaler

Question 8

A team develops an Azure Functions app that processes IoT telemetry. They notice cold start latency is impacting performance. The function uses the Consumption plan. Which action reduces cold starts most effectively?

Accepted Answer

Change to Premium plan with pre-warmed instances. The Consumption plan for Azure Functions can cause cold start latency because the function app is deallocated after a period of inactivity. Changing to the Premium plan with pre-warmed instances keeps a specified number of instances always running and ready to handle requests, eliminating the cold start delay for those instances. This is the most effective action among the options to reduce cold starts.

Answer

Use Durable Functions for long-running workflows

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Increase the function timeout to maximum

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Use a dedicated App Service plan

Question 9

You need to deploy a containerized application to Azure that must be restarted automatically if it crashes. The solution should minimize management overhead. Which compute service should you use?

Accepted Answer

Azure Container Instances. Azure Container Instances (ACI) is the correct choice because it provides a serverless container platform that automatically restarts containers if they crash when configured with a restart policy of 'Always' or 'OnFailure'. This minimizes management overhead by eliminating the need to manage underlying infrastructure, orchestration, or virtual machines, making it ideal for simple, stateless containerized applications that require automatic recovery.

Answer

Azure Functions

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Azure Kubernetes Service (AKS)

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Azure Virtual Machines

Question 10

A company runs a critical web app on Azure App Service that must handle traffic spikes without downtime. They set up autoscaling rules based on CPU percentage. However, during a spike, the app becomes unresponsive before new instances are added. What should they do?

Accepted Answer

Use pre-warming instances with a scheduled scaling rule. Pre-warming instances with a scheduled scaling rule ensures that additional instances are already running and ready to handle traffic before the CPU spike occurs. This avoids the cold-start delay inherent in reactive autoscaling, where new instances take time to provision and initialize, causing unresponsiveness during rapid spikes.

Answer

Switch to memory-based autoscaling

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Decrease the scale-in cooldown period

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Increase the CPU percentage threshold for scale-out

Question 11

You are designing a solution to process thousands of images uploaded to Azure Blob Storage. Each image must be resized and metadata extracted. The processing must be serverless and cost-effective. Which Azure service should you use?

Accepted Answer

Azure Functions with Blob Storage trigger. Azure Functions with a Blob Storage trigger is the correct choice because it provides a serverless, event-driven compute model that automatically scales to process thousands of images as they are uploaded to Blob Storage. The trigger binds directly to a blob container, invoking a function for each new blob, which allows you to resize images and extract metadata without managing infrastructure, making it both cost-effective and efficient for high-throughput workloads.

Answer

Azure Container Instances with Blob Storage SDK

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Azure Logic Apps with Blob Storage connector

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Azure Event Grid with Webhook to a custom service

Question 12

A company has an Azure App Service web app that occasionally returns 500 errors. You need to diagnose the root cause without impacting production traffic. Which feature should you use?

Accepted Answer

Application Insights. Application Insights is a powerful diagnostic tool that provides detailed telemetry and performance monitoring for your web app. It can automatically detect and analyze 500 errors, showing stack traces, request details, and dependencies. This allows you to identify the root cause without impacting production traffic, as it works passively by collecting data.

Answer

Kudu console

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Deployment slots

Answer

Autoscaling rules

Question 13

You are migrating an on-premises .NET Framework app to Azure. The app uses Windows authentication and requires persistent storage. You want to minimize rework. Which Azure compute service should you choose?

Accepted Answer

Azure App Service on Windows. Azure App Service on Windows (D) supports Windows authentication natively via its built-in integration with Azure Active Directory and on-premises Active Directory through Azure AD Domain Services or hybrid identity setups. It also provides persistent storage options like Azure Files or blob storage attached to the web app, minimizing rework by allowing the existing .NET Framework app to run with minimal code changes in a Platform-as-a-Service (PaaS) environment.

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Azure Spring Apps

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Azure Functions

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Azure Container Instances

Question 14

A company uses Azure Functions to process messages from Azure Service Bus. The function currently uses the Consumption plan. They notice that during high load, messages are processed slowly due to scaling latency. Which change would improve throughput most?

Accepted Answer

Switch to the Premium plan. The Premium plan for Azure Functions provides pre-warmed instances and faster scaling, eliminating the cold start and scaling latency inherent in the Consumption plan. This directly addresses the bottleneck during high load by ensuring that new instances are allocated instantly, thereby improving message processing throughput from Service Bus.

Answer

Set the maximum instance count to 20

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Increase the function's batch size to 100

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Enable Service Bus sessions

Question 15

You need to deploy a microservice that runs a long-running background job (up to 30 minutes). The job should not be affected by App Service recycling. Which Azure technology should you use?

Accepted Answer

Azure WebJobs with Always On enabled. Azure WebJobs with Always On enabled ensures the WebJob runs continuously on a dedicated App Service instance, preventing it from being unloaded during idle periods or App Service recycling. This allows the long-running background job (up to 30 minutes) to complete without interruption, as the WebJob runs in the same process as the web app and is not subject to the 5-minute timeout of the Consumption plan.

Answer

Azure Automation Runbook

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Azure Functions (Consumption plan)

Answer

Azure Kubernetes Service (AKS)