AZ-204 Develop Azure compute solutions Practice Test 13 — 15 Questions

Question 1

Your company runs a batch processing job on Azure Batch. The job processes large datasets and requires access to Azure Storage. You need to ensure that the compute nodes can securely access the storage account without exposing credentials. What should you configure?

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

Accepted Answer

Managed identity for the Batch pool. Managed identities for Azure resources allow compute nodes to authenticate to Azure Storage without storing credentials. Option A is wrong because Azure AD service principals require managing credentials and are not the simplest approach for Batch compute nodes to access storage. Option B is wrong because storage account access keys are shared secrets that should not be exposed. Option D is wrong because shared access signatures (SAS) tokens can be exposed and need to be managed.

Answer

Azure AD service principal

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Storage account access keys

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Shared access signatures (SAS)

Question 2

You are developing an Azure Functions app that processes large files from Azure Blob Storage. When a file is uploaded, the function triggers and reads the entire file into memory, causing high memory usage. You need to optimize the function to handle large files efficiently. Which approach should you recommend?

Accepted Answer

Stream the blob content directly to the processing logic. Streaming the blob content directly to the processing logic avoids loading the entire file into memory at once. The Azure Blob Storage SDK supports reading blob content as a stream (e.g., using `BlobClient.OpenReadAsync()`), which allows the function to process data in chunks, significantly reducing memory pressure for large files.

Answer

Use a byte array to read the blob in chunks

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Read the blob content into a temporary file on disk

Answer

Increase the memory allocation of the function app

Question 3

You deploy a containerized application to Azure Container Instances (ACI). The application needs to store configuration settings that might change at runtime. You need to update the configuration without redeploying the container. What should you do?

Accepted Answer

Mount an Azure Files share and update the configuration file. To update configuration settings at runtime without redeploying the container in Azure Container Instances (ACI), you should mount an Azure Files share. The application can read its configuration from a file stored on this share. When configuration changes are needed, you can update the file directly on the Azure Files share. The container itself does not need to be redeployed or restarted, provided the application is designed to periodically re-read the configuration file or react to file changes. This approach allows for dynamic configuration updates independent of the container lifecycle.

Answer

Use environment variables in the container group

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Use Application Settings in the container

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Modify the container image to include new configuration

Question 4

Your company has a multi-tier application running on Azure Virtual Machines. The application experiences high CPU usage during peak hours. You need to implement autoscaling for the virtual machine scale set based on CPU usage. The scaling should be aggressive when CPU exceeds 80% and conservative when CPU drops below 30%. Which scaling rule configuration should you use?

Accepted Answer

Scale out when CPU > 80%, scale in when CPU < 30%. The question explicitly requires aggressive scaling when CPU exceeds 80% and conservative scaling when CPU drops below 30%. The scale-out threshold of 80% triggers rapid addition of instances to handle high load, while the scale-in threshold of 30% ensures instances are removed only when utilization is consistently low, preventing premature scale-in and thrashing. This matches the exact thresholds specified in the requirement.

Answer

Scale out when CPU > 50%, scale in when CPU < 20%

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Scale out when CPU > 90%, scale in when CPU < 10%

Answer

Scale out when CPU > 70%, scale in when CPU < 70%

Question 5

You develop an Azure Durable Functions application that orchestrates a series of activities. The orchestrator function calls activity functions that perform long-running tasks. You need to ensure that the orchestrator function can handle transient errors and retry failed activity functions. Which feature should you use?

Accepted Answer

Built-in retry policies in Durable Functions. Durable Functions provides built-in retry policies that can be configured directly on activity function calls within orchestrator functions. This allows you to specify parameters such as max retry count, backoff interval, and retry timeout, enabling the orchestrator to automatically retry failed activities without custom code or external dependencies.

Answer

Polly library for retry logic

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Application Insights alerts

Answer

Azure Storage queue message retries

Question 6

You are deploying an application to Azure App Service that requires a custom startup script to initialize the environment. Where should you place the startup script in the application code?

Accepted Answer

As a startup command in the App Service configuration. Azure App Service allows you to specify a custom startup command or script in the App Service configuration (under 'General settings' or via the Azure CLI with `--startup-file`). This startup command runs before the application starts, enabling you to initialize the environment, run pre-deployment tasks, or set up dependencies. Placing the startup script in the configuration ensures it is executed by the App Service platform, which handles the runtime environment (Windows or Linux) and integrates with the application lifecycle.

Answer

In the 'web.config' file

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In a 'docker-compose.yml' file

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In the root of the application code as 'startup.sh'

Question 7

Which THREE factors should you consider when choosing between Azure Container Instances (ACI) and Azure Kubernetes Service (AKS) for a containerized workload? (Choose three.)

Accepted Answer

The need for orchestration of multiple containers. AKS provides full orchestration capabilities for managing multiple containers across a cluster, including service discovery, load balancing, and scaling. ACI is designed for single-container or simple multi-container groups without native orchestration, making AKS the appropriate choice when complex orchestration is required (A).
Azure Container Instances (ACI) has specific maximum resource limits for a single container group (e.g., 16 vCPU, 112 GiB memory), making it suitable for smaller, burstable workloads. Azure Kubernetes Service (AKS) allows for much larger, distributed applications by scaling out across multiple nodes and pods, making the overall resource capacity a key differentiator (E).
The Azure Application Gateway Ingress Controller (AGIC) is an AKS-specific feature that allows Application Gateway to act as an Ingress controller for an AKS cluster. If a workload requires this specific ingress solution, AKS is the appropriate choice, whereas ACI does not offer this native integration (D).

Answer

The restart policy for containers

Answer

The need for GPU-accelerated compute

Question 8

You are developing a web application that processes images uploaded by users. The images must be resized and analyzed for offensive content before being stored. You need to implement the solution with minimal latency and cost. What should you do?

Accepted Answer

Use an Azure Function triggered by Blob Storage, with Consumption plan.. Using an Azure Function triggered by Blob Storage on a Consumption plan provides a serverless, event-driven architecture that automatically scales to process each image upload with minimal latency and cost. The Consumption plan charges only for execution time and resources used, making it cost-effective for sporadic workloads, while the Blob Storage trigger ensures immediate processing upon upload without polling or additional infrastructure.

Answer

Use Azure Batch to process images in parallel.

Answer

Use Durable Functions to orchestrate the resizing and analysis.

Answer

Use Azure Logic Apps with a trigger for each upload.

Question 9

You are deploying a containerized application to Azure Container Instances. The application requires a custom domain name and SSL/TLS certificate. What should you do?

Accepted Answer

Place an Azure Application Gateway in front of the container group.. Azure Container Instances (ACI) does not natively support custom domain names or SSL/TLS termination. By placing an Azure Application Gateway in front of the container group, you can offload SSL/TLS termination at the gateway layer, map a custom domain via the gateway's frontend IP, and route traffic to the container group's private IP. This is the recommended pattern for adding HTTPS and custom domains to ACI workloads.

Answer

Configure the container to listen on port 443 and map a custom domain.

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Upload the certificate to the container and configure the web server.

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Use a private endpoint with a custom domain.

Question 10

You are developing a microservices application deployed on Azure Kubernetes Service (AKS). You need to ensure that service-to-service communication is encrypted using mutual TLS (mTLS) without modifying application code. What should you do?

Accepted Answer

Deploy Azure Service Mesh and enable mTLS.. Azure Service Mesh (e.g., Open Service Mesh or Istio-based) provides a transparent infrastructure layer that can automatically inject sidecar proxies into pods and enforce mTLS for all service-to-service communication without requiring any changes to application code. This meets the requirement of encrypting traffic with mutual TLS while keeping the application code untouched.

Answer

Use Azure Application Gateway Ingress Controller with mTLS.

Answer

Enable Azure Kubernetes Service (AKS) pod-to-pod encryption.

Answer

Configure Azure Network Security Groups to enforce encryption.

Question 11

You have an Azure App Service web app that experiences high CPU usage during peak hours. You need to scale out automatically based on CPU load. What should you configure?

Accepted Answer

Configure an autoscale rule to scale out based on CPU percentage.. Azure App Service autoscale rules allow you to scale out (increase instance count) based on a metric like CPU percentage. This automatically adds more instances when CPU exceeds a threshold, distributing the load and reducing CPU usage per instance during peak hours.

Answer

Manually increase the instance count during peak hours.

Answer

Configure an autoscale rule to scale up the App Service plan.

Answer

Use Azure Front Door to distribute load across multiple instances.

Question 12

Which TWO actions should you take to ensure high availability for a stateful ASP.NET application deployed on Azure App Service?

Accepted Answer

Enable ARR Affinity (client affinity) to maintain session state.. Enabling ARR Affinity (client affinity) ensures that all requests from a given client session are routed to the same instance, preserving in-memory session state. Without this, a stateful ASP.NET application would lose session data if subsequent requests are load-balanced to different instances, causing session state errors.

Answer

Scale up the App Service plan to a higher tier.

Answer

Store session state in Azure Files share.

Answer

Disable session state to allow any instance to handle requests.

Question 13

Refer to the exhibit. You run the Azure CLI command shown for an Azure Function app. What is the effect of this setting?

Accepted Answer

The function app runs from a deployment package in Azure Storage.. The `--run-from-package` flag in the Azure CLI command `az functionapp config appsettings set` sets the `WEBSITE_RUN_FROM_PACKAGE` app setting to `1`. This configures the function app to run from a deployment package (a .zip file) stored in Azure Blob Storage, which improves cold-start performance and ensures all files are consistent across instances. Option D correctly identifies this behavior.

Answer

The function app uses the latest runtime version.

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Remote debugging is enabled for the function app.

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The function app scales out to multiple instances.

Question 14

Refer to the exhibit. You deploy this ARM template to a resource group. The template fails with a 'ResourceNotFound' error. What is the most likely cause?

Accepted Answer

The App Service plan 'myplan' does not exist in the resource group.. The ARM template references an App Service plan named 'myplan' in the 'serverFarmId' property of the Microsoft.Web/sites resource. If 'myplan' does not exist in the same resource group, the deployment fails with a 'ResourceNotFound' error because Azure Resource Manager cannot resolve the dependency on a non-existent resource. The template does not include a definition for the App Service plan, so it must already exist in the resource group.

Answer

The 'apiVersion' is incorrect.

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The template is missing the 'dependsOn' property.

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The 'type' property is incorrect for a web app.

Question 15

Refer to the exhibit. You run this KQL query in Azure Resource Graph Explorer. The query returns no results. What is the most likely reason?

Accepted Answer

The resource type is incorrect; it should be 'microsoft.insights/components' in lowercase.. The KQL query uses the resource type 'Microsoft.Insights/Components' with mixed case, but Azure Resource Graph Explorer requires resource types to be specified in all lowercase. The correct type is 'microsoft.insights/components'. When the case does not match, the query returns no results because Azure Resource Graph performs a case-sensitive match on the 'type' property.

Answer

The 'contains' operator is case-sensitive.

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The query must specify a subscription filter.

Answer

The 'where' clause must use '== ' instead of '=='.