AZ-204 Develop Azure compute solutions Practice Test 2 — 15 Questions

Question 1

You are deploying a Docker container to Azure Container Instances (ACI). The container must use GPU resources for machine learning inference. You need to select the appropriate option to provision GPU-enabled containers. What should you do?

Accepted Answer

Deploy the container to a container group with a GPU-enabled SKU (e.g., NV series).. Azure Container Instances supports GPU resources only when you deploy a container group using a GPU-optimized SKU, such as the NV-series (e.g., Standard_NC6s_v3). These SKUs provide NVIDIA Tesla GPUs (e.g., K80, P100, V100) that are directly exposed to the container, enabling hardware-accelerated machine learning inference. You must specify the GPU SKU in the container group's resource requests during deployment, and the container image must include the appropriate NVIDIA CUDA drivers or runtime.

Answer

Mount a GPU volume from the host.

Answer

Use Azure Batch with GPU-enabled pools.

Answer

Enable container GPU support in the Dockerfile.

Question 2

You are deploying a containerized application to Azure Container Instances. The application requires a custom domain name and SSL/TLS termination. You need to configure these features. Which resource should you create alongside the container group?

Accepted Answer

Azure Application Gateway. Azure Application Gateway provides Layer 7 load balancing with SSL/TLS termination and custom domain support. By associating a custom domain with the Application Gateway's frontend IP and uploading an SSL certificate, you can terminate HTTPS connections at the gateway and forward traffic to the container group over HTTP. This meets the requirement without exposing the container group directly.

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Azure Front Door

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Azure Container Registry

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Azure DNS zone

Question 3

You develop an Azure Function app that processes orders. The function must write order status updates to a database. You need to ensure that if the function fails after writing to the database, the order is not lost and can be retried. Which pattern should you implement?

Accepted Answer

Use a Durable Functions orchestration. Option A is correct because Durable Functions orchestrations provide built-in support for reliable execution and automatic retry on failure. By using an orchestration, you can write the order status to the database as an activity function, and if the function fails after the write, the orchestration can replay from the last checkpoint, ensuring the order is not lost and can be retried without duplicating the write.

Answer

Use a retry policy in the function code

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Enable function-level exception handling

Answer

Use an Azure Storage Queue for the function input

Question 4

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.

Answer

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 5

You deploy a container to Azure Container Instances (ACI). The container runs a background job that should automatically restart only if it exits with a non-zero exit code (i.e., crashes). You want to minimize costs. Which restart policy should you configure?

Accepted Answer

Set restart policy to OnFailure and use a single container group. The OnFailure restart policy restarts the container only when it exits with a non-zero exit code, which matches the requirement to restart only on crashes. This policy minimizes costs because the container does not run continuously when it exits successfully, unlike the Always policy. Using a single container group is the simplest and most cost-effective deployment for a single background job.

Answer

Set restart policy to Always and use a private container registry

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Set restart policy to Never and use a public container registry

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Set restart policy to OnFailure and deploy in a virtual network

Question 6

You are deploying a containerized application to Azure Container Instances (ACI). The application writes temporary data to a local disk that must persist across container restarts (e.g., after a crash). Which configuration should you use?

Accepted Answer

Mount an Azure Files share as a volume in the container group.. Option A is correct because Azure Container Instances (ACI) supports mounting an Azure Files share as a persistent volume. When a container restarts (e.g., after a crash), the temporary disk is wiped, but data written to an Azure Files share persists independently of the container's lifecycle. This meets the requirement for data to survive container restarts.

Answer

Use the temporary disk automatically allocated by ACI.

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Store data in an Azure Cosmos DB database.

Answer

Use an emptyDir volume as available in Kubernetes.

Question 7

You are developing an Azure Function that runs on a Consumption Plan. The function calls an external API that enforces a rate limit of 10 requests per second. When the function scales out to multiple instances, you must ensure the rate limit is not exceeded. Which pattern should you implement?

Accepted Answer

Use a queue-based load leveling pattern with an Azure Storage Queue.. Option D is correct because a queue-based load leveling pattern uses an Azure Storage Queue to buffer incoming requests, allowing the function to process them at a controlled rate. This decouples the function's scaling from the external API's rate limit, ensuring that even with multiple function instances, the total request rate does not exceed 10 requests per second. The queue acts as a buffer, and the function can be configured to dequeue and process messages at a fixed rate, effectively smoothing out spikes in demand.

Answer

Use a singleton attribute on the function to ensure only one instance runs.

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Use a static SemaphoreSlim in the function code to limit concurrent calls.

Answer

Configure the function's host.json to limit concurrency to 1.

Question 8

You deploy a containerized background job to Azure Container Instances (ACI). The job should automatically restart only if it exits with a non-zero exit code (i.e., crashes). You want to minimize costs. Which restart policy should you configure?

Accepted Answer

OnFailure. The OnFailure restart policy is correct because it restarts the container only when it exits with a non-zero exit code, indicating a crash or error. This matches the requirement to automatically restart only on failure while minimizing costs, as it avoids unnecessary restarts on successful completions.

Answer

Always

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Never

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Retry

Question 9

You are developing an Azure Function that processes messages from an Azure Service Bus queue. The function uses a Service Bus queue trigger and runs on a Consumption Plan. The queue receives a high volume of messages in bursts. You need to ensure that the function scales out to handle the load but does not exceed 10 concurrent instances. Which configuration should you apply?

Accepted Answer

Set the 'WEBSITE_MAX_INSTANCES' application setting to 10 in the function app.. Option B is correct because the 'WEBSITE_MAX_INSTANCES' application setting is the proper way to limit the number of concurrent instances (scale-out) for a function app running on a Consumption Plan. This setting caps the maximum number of instances the platform can allocate, ensuring that even under high burst loads, the function does not exceed 10 concurrent instances. The Service Bus trigger's 'maxConcurrentCalls' controls per-instance concurrency, not instance count, and 'maxMessageBatchSize' controls batch size, not scaling.

Answer

Set the 'maxConcurrentCalls' property to 10 in the host.json file.

Answer

Set the 'maxMessageBatchSize' property to 10 in the host.json file.

Answer

Restrict the Service Bus queue to have a maximum concurrency of 10 at the namespace level.

Question 10

You deploy a containerized web application to Azure Container Instances (ACI). The application writes session data to a local directory. You need the data to persist across container restarts (e.g., after a crash or redeployment). Which storage configuration should you use?

Accepted Answer

Mount an Azure Files share as a volume in the container group.. Option B is correct because Azure Files provides a fully managed SMB file share in the cloud that can be mounted as a volume in an Azure Container Instance. This allows session data written to the local directory to persist across container restarts, crashes, or redeployments, as the data lives on the share rather than in the ephemeral container filesystem.

Answer

Use an emptyDir volume within the container group.

Answer

Use the container's own filesystem and copy data to a blob storage on shutdown.

Answer

Enable Azure Disk Encryption on the container group.

Question 11

You are developing an Azure Function that uses a Service Bus queue trigger. You need to ensure that the function processes messages one at a time to guarantee order. Which configuration should you use?

Accepted Answer

Set the batchSize to 1 in host.json. Option A is correct because setting `batchSize` to 1 in `host.json` forces the Service Bus trigger to process only one message at a time from the queue. This ensures strict message ordering, as the function will not fetch or process the next message until the current one is completed (either successfully or moved to the dead-letter queue). The Service Bus trigger uses a message pump that respects the `batchSize` setting to control concurrency.

Answer

Set the maxMessages to 1 in the ServiceBusTrigger attribute

Answer

Set the function to run on a Premium Plan

Answer

Set the maxDequeueCount to 1 in host.json

Question 12

You have an Azure Function with a Service Bus queue trigger. The function processes messages that must be handled in order within each partition of the queue. You need to ensure that the function does not process multiple messages from the same partition concurrently, while still allowing parallel processing across different partitions. Which setting should you configure?

Accepted Answer

Set the maxConcurrentCallsPerSession to 1, or use a session-enabled queue and set maxConcurrentSessions to 1 if using sessionId.. Option B is correct because Service Bus sessions provide exactly-once-in-order message processing within a partition (session). Setting `maxConcurrentCallsPerSession` to 1 ensures that only one message from a given session is processed at a time, while `maxConcurrentSessions` controls how many different sessions can be processed in parallel. This allows concurrent processing across partitions but serializes processing within each partition.

Answer

Set the batch size to 1 in the function configuration.

Answer

Use a consumption plan, which automatically limits concurrency.

Answer

Use a queue trigger instead of a Service Bus trigger.

Question 13

You are developing a solution that needs to run a background task every 10 minutes to clean up temporary files in Azure Blob Storage. You want to use Azure Functions with the Consumption Plan to minimize cost. Which trigger type should you use?

Accepted Answer

TimerTrigger. B is correct because TimerTrigger is designed for scheduled execution of background tasks at fixed intervals, such as every 10 minutes. It uses a cron expression to define the schedule and runs on the Consumption Plan, which scales to zero when idle, minimizing cost. This makes it the ideal choice for periodic cleanup of temporary files in Azure Blob Storage.

Answer

HTTPTrigger

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BlobTrigger

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ServiceBusTrigger

Question 14

You are deploying a batch processing application to Azure Container Instances (ACI). The application processes multiple files from an Azure Blob Storage container and writes results to another container. Each container instance processes a single file and then exits. The processing logic is written in a Docker image that reads input and output connection strings from environment variables. You need to configure the container group so that it writes the results to the output container durably and efficiently. The environment variables must be provided at runtime but must not be exposed in the ACI configuration. Which approach should you use?

Accepted Answer

Use a managed identity for the container group, grant the identity access to an Azure Key Vault secret that contains the storage account connection string. The application retrieves the secret at startup using the managed identity and then writes directly to Azure Blob Storage.. Option B is correct because it uses a managed identity to securely retrieve the storage account connection string from Azure Key Vault at runtime, ensuring the secret is never exposed in the ACI configuration. The application writes directly to Azure Blob Storage, which is durable and efficient for blob output. This approach aligns with the requirement to avoid exposing environment variables in the ACI configuration while providing them at runtime.

Answer

Mount an Azure File Share volume for the output container and configure the application to write output files to a directory on that share. Store the connection string for the file share in a secure fashion using Key Vault and pass it as an environment variable.

Answer

Embed the storage account connection string directly into the Docker image during build time and rely on the container's environment to provide the output blob container name.

Answer

Set the storage account connection string as an environment variable in the ACI container group definition (YAML or ARM template) and have the application use it at runtime.

Question 15

You are developing a solution that needs to perform a multi-step workflow. The workflow involves calling several third-party APIs, and some steps may require waiting for a human approval via email. The workflow may run for hours. You want to use Azure Functions to implement this orchestration. Which Azure Functions feature should you use?

Accepted Answer

Durable Functions. Durable Functions is the correct choice because it is an extension of Azure Functions that enables stateful, long-running orchestration workflows. It supports waiting for external events (like human approval via email), managing multi-step API calls, and handling execution that may run for hours, all while preserving state through checkpoints and replay.

Answer

Timer trigger functions

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Service Bus queue trigger functions

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Blob storage trigger functions