AZ-204 Develop Azure compute solutions Practice Test 18 — 15 Questions

Question 1

You are developing a solution that processes messages from an Azure Storage Queue. Each message triggers a long-running operation that may take up to 30 minutes. You need to ensure that if the processing fails, the message is not lost and can be retried later. The current implementation uses a console application that polls the queue and deletes messages after processing. What should you change?

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

Accepted Answer

After processing fails, update the message's visibility timeout to a later time so it becomes visible again for retry.. The correct approach is to update the message's visibility timeout to a later time when processing fails. This makes the message reappear in the queue after the specified timeout, allowing another consumer to retry processing. Azure Storage Queue messages have a default visibility timeout of 30 seconds, but you can extend it to up to 7 days. This ensures the message is not lost and can be retried without being deleted or moved prematurely.

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Move the message to a poison queue after the first failure.

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Increase the polling interval to reduce the chance of missing messages.

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Delete the message only if processing succeeds; otherwise, leave it in the queue.

Question 2

Your company is migrating a legacy on-premises .NET Framework 4.7.2 web application to Azure. The application uses session state stored in-memory and reads/writes to a local SQL Server database. The migration must minimize code changes, support auto-scaling, and handle session state across multiple instances. You plan to use Azure App Service with Windows OS. You need to recommend a solution for session state storage and database connectivity. Which option should you choose?

Accepted Answer

Use Azure Cache for Redis as the session state provider via the RedisSessionStateProvider NuGet package, and configure the database connection string in Azure App Service App Settings.. Azure Cache for Redis provides a distributed, in-memory session state provider that supports session state sharing across multiple App Service instances without requiring code changes to the application logic. The RedisSessionStateProvider NuGet package is a drop-in replacement for the default in-memory provider, and configuring the database connection string in App Settings allows you to change the target without modifying web.config, minimizing migration effort.

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Store session state in Azure Table Storage using a custom session state provider, and use a connection string for Azure SQL Database.

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Configure session state using Azure SQL Database with a session state database, and update the connection string in web.config.

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Use App Service's built-in session state with ARR affinity and connect to Azure SQL Database using Managed Identity.

Question 3

You are developing a containerized application that will be deployed to Azure Container Instances (ACI). The application consists of a web front-end and a background worker that processes messages from an Azure Storage Queue. You need to ensure that the worker container runs continuously and processes messages as they arrive. The solution must minimize cost and management overhead. What should you do?

Accepted Answer

Deploy the worker as a container group in ACI with the restart policy set to Always.. ACI with a restart policy of Always ensures the worker container restarts immediately after it finishes processing a message, allowing it to continuously poll the Azure Storage Queue for new messages. This minimizes cost by using a serverless container model without provisioning VMs or managing orchestration, and it reduces management overhead compared to alternatives like Azure virtual machines.

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Use Azure Container Apps with a scale rule that triggers on queue length.

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Run the worker inside an Azure virtual machine with a container runtime.

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Deploy the worker as a container in ACI with the restart policy set to OnFailure.

Question 4

Your company is developing a real-time dashboard that displays live metrics from IoT devices. The backend processes device data using Azure Functions with an Event Hubs trigger. The processed data is stored in Azure Cosmos DB. You need to ensure that the system can handle a sudden increase in device data without losing messages or overloading Cosmos DB. The solution must minimize latency and cost. What should you do?

Accepted Answer

Implement a buffer using Azure Blob storage: the Event Hubs triggered function writes raw data to blobs, and a separate timer-triggered function batches and writes to Cosmos DB at a controlled rate.. It decouples the ingestion rate from the write rate to Cosmos DB. By buffering raw data in Azure Blob storage and using a timer-triggered function to batch-write at a controlled rate, the system can absorb sudden spikes in device data without overwhelming Cosmos DB or losing messages. This approach minimizes latency by keeping the Event Hubs trigger processing fast (writing to blob) and reduces cost by avoiding the need to over-provision RU/s on Cosmos DB.

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Configure the Event Hubs trigger to use a checkpointing strategy with a larger batch size to reduce the number of function invocations.

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Use Azure Stream Analytics to process the Event Hubs data and write directly to Cosmos DB.

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Increase the provisioned throughput (RU/s) on the Cosmos DB container to handle peak loads.

Question 5

You are developing a web app that processes images uploaded by users. The processing can take up to 30 seconds per image. You need to ensure that the web app remains responsive and can handle spikes in traffic. Which Azure service should you use to offload the image processing?

Accepted Answer

Azure Queue Storage. Azure Queue Storage is correct because it provides a durable, asynchronous message queue that can decouple the web app's frontend from the long-running image processing task. By placing a message for each image onto a queue, the web app can immediately return a response to the user, while a background worker (e.g., an Azure Function or WebJob) polls the queue and processes images as capacity allows. This pattern ensures the web app remains responsive under traffic spikes, as the queue acts as a buffer that scales independently.

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Azure Cosmos DB

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Azure Event Grid

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Azure SignalR Service

Question 6

You are deploying a containerized application to Azure Container Instances. The application must restart automatically if it crashes. You set the restart policy to 'Always'. However, the container keeps restarting continuously even when there is no crash. What is the most likely cause?

Accepted Answer

The application inside the container exits with a non-zero exit code on startup.. The 'Always' restart policy in Azure Container Instances restarts the container whenever it stops, regardless of the exit code. If the application exits with a non-zero exit code on startup (e.g., due to a configuration error or missing dependency), the container will stop immediately, triggering an infinite restart loop. This is the most likely cause because the container is not crashing due to external factors but rather failing during its initialization phase.

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The container is configured with an Azure Files volume that is not accessible.

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The container is trying to bind to a port that is already in use on the host.

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The container is exceeding the allocated CPU or memory limits.

Question 7

Your company is migrating a monolithic application to Azure. The application consists of several components that need to be deployed and scaled independently. You need to design a container orchestration solution. Which TWO services should you consider?

Accepted Answer

Azure Container Apps. Azure Container Apps (B) is correct because it provides a serverless container orchestration platform that allows you to deploy and scale microservices independently without managing the underlying Kubernetes infrastructure. It supports event-driven scaling, revision management, and split traffic routing, making it ideal for migrating monolithic applications to a microservices architecture with minimal operational overhead.

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Azure Container Instances

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Azure Batch

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Azure Service Fabric

Question 8

Refer to the exhibit. You deploy this ARM template to create an Azure App Service. After deployment, the application stops responding after a few minutes. The application is a .NET 6 web API that runs in a Linux container. What is the most likely cause?

Accepted Answer

The 'alwaysOn' setting is enabled but the App Service plan is on a tier that does not support Always On.. The 'alwaysOn' setting keeps the app loaded even after periods of inactivity, but it is only supported on Basic, Standard, Premium, and Isolated tiers. If the App Service plan is on a Free or Shared tier, enabling 'alwaysOn' causes the app to stop responding after a few minutes because the platform forcibly unloads idle apps, leading to timeouts or crashes.

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The ARM template is missing the 'dependsOn' element.

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The 'linuxFxVersion' is set incorrectly for .NET 6.

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The 'WEBSITE_RUN_FROM_PACKAGE' app setting is incorrectly set to '1'.

Question 9

You are a developer at a financial services company. You need to design a solution for processing real-time stock trade data. The system receives thousands of trades per second from an on-premises system. Each trade must be validated, enriched with reference data, and then stored in a data lake for analytics. You have the following requirements:
- The processing must be serverless and scale automatically with high throughput.
- The enrichment step requires calling an external REST API that can handle up to 100 requests per second. If the API is overwhelmed, trades must be retried with exponential backoff.
- The solution must minimize cost and operational overhead.
- Trades must be processed in order per stock symbol.
You provision an Azure Event Hubs namespace with a single event hub. Trades are sent to the event hub with the stock symbol as the partition key. You configure an Azure Functions app with an Event Hubs trigger to process events. The function validates, enriches by calling the external API, and writes the enriched trade to Azure Data Lake Storage. During testing, you notice that some trades are processed out of order for the same stock symbol when the external API throttles requests. What should you do to ensure ordering per stock symbol?

Accepted Answer

Set the 'maxEventBatchSize' to 1 in the host.json file to process one event at a time per instance.. Setting 'maxEventBatchSize' to 1 ensures that each function instance processes only one event at a time. When the external API throttles and triggers retries with exponential backoff, processing of subsequent events for the same partition (stock symbol) is blocked until the current event completes. This preserves the per-partition ordering guarantee that Event Hubs provides, as events within a partition are processed sequentially by a single consumer.

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Use Durable Functions to orchestrate the processing and enforce ordering.

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Increase the 'maxEventBatchSize' setting to 100 in the host.json file to improve throughput.

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Use a different partition key such as a unique trade ID to distribute load evenly.

Question 10

You are developing an Azure Function that processes messages from an Azure Storage queue. The function must handle transient failures when writing to a downstream database. You need to implement a retry policy. What is the recommended approach?

Accepted Answer

Configure the retry policy in the function's host.json file.. Azure Functions provides a built-in retry policy that can be configured declaratively in the host.json file, specifically using the 'retry' section for fixed-delay or exponential-backoff strategies. This is the recommended approach for handling transient failures in a clean, configurable manner without custom code, and it applies to all function executions in the function app.

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Do nothing; Azure Functions automatically retries failed executions indefinitely.

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Use a try-catch block in the function code to retry on failure.

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Use Durable Functions with a retry policy.

Question 11

You are building a serverless API using Azure Functions. The API must authenticate callers by validating a JWT access token issued by Microsoft Entra ID before executing any business logic. You want to enforce this validation across all HTTP-triggered functions without duplicating token-parsing code in each function. What should you implement?

Accepted Answer

Configure the function app's authentication settings to use the Microsoft Entra ID provider and require authentication for incoming requests.. App Service Authentication integrates with Microsoft Entra ID to validate JWTs at the platform layer before requests reach function code. It checks signature, issuer, audience, and expiration, and it rejects unauthenticated requests with 401. Because the validation is centralized, no per-function token-parsing code is needed, directly meeting the requirement for consistent authentication across all HTTP-triggered functions.

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Add a function-level API key requirement by setting the authLevel property to 'function' on every HTTP trigger.

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Store the JWT in Azure Key Vault and configure the function app to retrieve it via a managed identity at startup.

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Create a custom middleware binding that decodes the JWT and checks the exp claim before each function execution.

Question 12

You are developing an Azure Functions app that must run a cleanup task every night at 2:00 AM UTC. The function does not need to process any external events and should not be triggered by HTTP requests. Which trigger type should you use for this function?

Accepted Answer

Timer trigger. A timer trigger is purpose-built for scheduled execution using a CRON expression. It runs the function automatically at the specified times without needing an external event or caller. For a cleanup task that must run nightly at 2:00 AM UTC and has no event source, the timer trigger is the appropriate and straightforward binding to use.

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HTTP trigger

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Blob trigger

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Queue trigger

Question 13

You are developing a solution that uses Azure Container Apps to host a microservices application. The application consists of multiple services that need to communicate with each other. You need to configure the services to meet the following requirements: (1) Services must be able to discover each other by name, (2) Communication between services must be secure and encrypted, (3) You want to minimize the need for managing certificates. Which two actions should you perform? (Choose two.)

Accepted Answer

Enable mutual TLS (mTLS) for the Container Apps environment.. To enable secure service-to-service communication with discovery by name and minimal certificate management, you should enable mutual TLS for the Container Apps environment and use the built-in service discovery. mTLS automatically encrypts and authenticates traffic between container apps, and the platform manages certificates. Built-in service discovery allows services to find each other using the app name without additional configuration. Together, these features provide a secure and simplified microservices communication setup.

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Deploy an Azure Application Gateway in front of the Container Apps environment to handle internal traffic.

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Store service endpoints in Azure Key Vault and retrieve them at runtime.

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Configure a custom DNS name for each container app and use it for service discovery.

Question 14

You are developing a containerized web application that will be deployed to Azure App Service. The application must read a connection string from an environment variable at runtime. You want to avoid storing the connection string in the source code or in the App Service application settings in plaintext. What should you do?

Accepted Answer

Store the connection string in Azure Key Vault and reference it from App Service application settings by using a Key Vault reference.. Key Vault references let App Service fetch secrets from Azure Key Vault and surface them as environment variables. The connection string is not stored in application settings or source code, and access to Key Vault can be controlled with managed identities and access policies. This provides secure storage, centralized management, and easy rotation, directly meeting the requirement.

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Configure the connection string in the App Service application settings and enable the 'hidden' setting so it is not displayed in the portal.

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Store the connection string in a configuration file that is baked into the container image and read it from the file at runtime.

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Pass the connection string as a build argument when building the container image and set it as a container environment variable.

Question 15

You are developing an Azure Functions app that processes messages from an Azure Service Bus queue. The function must ensure that if processing fails, the message is retried automatically and, after a maximum number of attempts, moved to a dead-letter queue. You want to minimize custom code. What should you configure?

Accepted Answer

Set the maxDeliveryCount property on the Service Bus queue to the desired number of retries and enable dead-lettering on the queue.. Service Bus queues natively support retry and dead-lettering through the maxDeliveryCount property. When a function fails to process a message and abandons it, the delivery count increases. After the maximum number of deliveries, Service Bus automatically moves the message to the dead-letter queue. This requires no custom code in the function, directly meeting the requirement to minimize custom code.

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Enable the 'auto-dead-letter' setting on the function trigger binding and set the retry count in the function's application settings.

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Configure the function's host.json to set maxRetries to the desired number and enable dead-lettering in the function code.

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Use a Durable Functions orchestrator to call the processing activity and implement a retry policy with a maximum attempt count.