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

Question 1

A web app experiences intermittent high latency. You discover that the Azure SQL database is experiencing a high number of connection timeouts. The application uses Entity Framework Core with the default connection pooling settings. You need to improve database connection reliability without changing the application code. What should you do?

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

Accepted Answer

Set the Minimum Pool Size to 10 in the connection string.. Setting the Minimum Pool Size to 10 pre-creates a baseline of open connections in the pool, reducing the frequency of new connection creations during traffic spikes. This mitigates intermittent connection timeouts caused by the default pool starting empty and struggling to keep up with demand under high latency. Since the application uses Entity Framework Core with default pooling, this change is applied via the connection string without modifying code.

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Increase the maximum pool size in the connection string.

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Set the Connection Lifetime to 300 seconds.

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Enable Multipool in the connection string.

Question 2

You deploy an Azure Function app that uses the Premium plan. The function processes messages from an Azure Service Bus queue. Under heavy load, some messages are processed multiple times. You need to ensure exactly-once processing without losing messages. What should you do?

Accepted Answer

Enable duplicate detection on the Service Bus queue.. Enabling duplicate detection on the Service Bus queue ensures that the Service Bus broker itself discards duplicate messages based on a user-defined time window. This prevents the function from processing the same message multiple times, even if the function host restarts or the message is re-delivered due to transient failures. Duplicate detection works by tracking the MessageId of each message and ignoring any subsequent message with the same MessageId within the detection window.

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Use Peek-Lock mode instead of Receive and Delete.

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Set the maxDeliveryCount to 1 on the queue.

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Reduce the batch size in the function host.json.

Question 3

You are building a serverless API using Azure Functions. The API must authenticate requests using Microsoft Entra ID. You need to restrict access to users from a specific Microsoft Entra tenant only. What should you configure in the function app?

Accepted Answer

Set the 'Issuer URL' to the specific tenant's endpoint.. Setting the 'Issuer URL' to the specific tenant's endpoint (e.g., https://login.microsoftonline.com/{tenant-id}/v2.0) tells Azure Functions to validate that the token was issued by that exact tenant. This restricts access to users from that tenant only, as tokens from other tenants will fail issuer validation.

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Set the 'Allowed Token Audiences' to the application ID.

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Enable 'Require Authentication' and set the action to 'Login with Microsoft Entra ID'.

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Set the 'Client ID' to the application ID.

Question 4

You develop a containerized application that runs on Azure Container Instances (ACI). The application needs to securely access Azure SQL Database using a connection string. You want to minimize administrative effort and avoid storing secrets in the container image. What should you do?

Accepted Answer

Enable managed identity for the container group and use Microsoft Entra authentication to Azure SQL.. Enabling a managed identity for the container group allows the application to authenticate to Azure SQL Database using Microsoft Entra ID (formerly Azure Active Directory) without storing any secrets. The application requests an access token from the Azure Instance Metadata Service (IMDS) endpoint at 169.254.169.254, then uses that token to connect to Azure SQL. This eliminates the need to manage connection strings or secrets, minimizing administrative effort and keeping secrets out of the container image.

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Embed the connection string in the container image as a configuration file.

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Store the connection string in an environment variable in the container group.

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Mount a volume from Azure Key Vault using a secret volume.

Question 5

You host a web application on Azure App Service using multiple deployment slots (production and staging). After swapping staging into production, users report errors. You need to ensure that the staging slot is warmed up before swapping and that any errors during swap cause an automatic rollback. What should you configure?

Accepted Answer

Enable auto swap and configure a custom warm-up path.. Enabling auto swap with a custom warm-up path ensures the staging slot is fully warmed up before the swap occurs, and if the warm-up fails or the application returns errors during the swap, Azure App Service automatically rolls back to the previous slot. This directly addresses the requirement for both pre-swap warm-up and automatic rollback on errors.

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Configure deployment slot settings to be sticky.

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Use swap with preview and complete the swap after verification.

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Configure manual swap and run a warm-up script before swapping.

Question 6

You are building a solution that processes real-time telemetry from IoT devices. The telemetry data must be ingested, processed with minimal latency, and stored in Azure Blob Storage for long-term analytics. You need to choose the serverless compute service that is best suited for this scenario. What should you use?

Accepted Answer

Azure Functions with Event Hubs trigger. Azure Functions with an Event Hubs trigger is the best choice because it provides a serverless, event-driven compute model that can process high-throughput telemetry data with minimal latency. The Event Hubs trigger scales automatically based on the number of partitions and events, ensuring real-time processing, and the output can directly write to Azure Blob Storage for long-term analytics.

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Azure Batch with Event Hubs input

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Azure Logic Apps with Event Hubs connector

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Azure WebJobs with Event Hubs SDK

Question 7

You deploy an Azure Function app that runs on the Consumption plan. The function writes logs to Application Insights. You notice that some log entries are missing during periods of high load. You need to ensure that all logs are captured without significantly increasing cost. What should you do?

Accepted Answer

Adjust the sampling rate in the Application Insights configuration to 100%.. Under high load, Application Insights uses adaptive sampling by default to reduce data volume, which can cause log entries to be dropped. Adjusting the sampling rate to 100% in the Application Insights configuration ensures all telemetry data is captured, while still running on the Consumption plan, which does not significantly increase cost because the function app itself scales and you only pay for execution time and resources used.

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Change the function app to the Premium plan to get more CPU and memory.

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Create a separate Application Insights resource for the function app.

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Disable sampling in the function's host.json.

Question 8

You are designing a microservices solution using Azure Container Apps. One service must be exposed externally via HTTPS, while others should only be accessible within the environment. You need to configure networking for this scenario. What should you do?

Accepted Answer

Configure each container app's ingress: set the external service to 'External' and the internal services to 'Internal'.. Azure Container Apps allows you to control ingress at the individual container app level. Setting the external service's ingress to 'External' makes it reachable from the internet via HTTPS, while setting internal services to 'Internal' restricts access to only within the Container Apps environment, using the internal FQDN. This provides the required isolation without needing separate environments or complex network policies.

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Enable external ingress at the environment level and use network policies to restrict access.

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Deploy the external service in a different environment and use an internal load balancer.

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Use a Dapr sidecar to route requests between services.

Question 9

You are deploying a critical application on Azure App Service. The application must be highly available across two Azure regions. You need to implement a disaster recovery strategy that meets the following requirements: automatic failover with minimal data loss, and the ability to test failover without affecting production. Which THREE actions should you perform?

Accepted Answer

Use deployment slots to test failover before making it active.. Deployment slots in Azure App Service allow you to create separate environments (e.g., staging) that can be swapped to production. This enables testing failover scenarios (like pointing Traffic Manager to the staging slot) without affecting the live production traffic, meeting the requirement for non-disruptive failover testing.

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Configure the app to use active-passive database replication.

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Deploy both instances in the same App Service Plan.

Question 10

Your company has an Azure Kubernetes Service (AKS) cluster that hosts multiple microservices. You are tasked with deploying a new microservice that processes incoming HTTP requests and publishes messages to an Azure Service Bus topic. The microservice must scale based on the number of messages in the topic, and it must support graceful shutdown to complete in-flight requests. You need to choose the appropriate compute platform. The microservice is stateless and can be containerized. You want to minimize operational overhead and cost. The solution must automatically scale to zero when there are no messages. Which option should you choose?

Option A: Deploy the microservice as an Azure Function with a Service Bus trigger on the Consumption plan.
Option B: Deploy the microservice as a container in AKS with a Horizontal Pod Autoscaler based on Service Bus queue length.
Option C: Deploy the microservice as an Azure Container App with a Service Bus scale rule.
Option D: Deploy the microservice as an Azure App Service WebJob with continuous mode.

Accepted Answer

Deploy the microservice as an Azure Container App with a Service Bus scale rule.. Azure Container Apps (ACA) with a Service Bus scale rule is the correct choice because it provides event-driven scaling based on the number of messages in a Service Bus topic, can scale to zero when there are no messages, supports graceful shutdown via terminationGracePeriodSeconds, and minimizes operational overhead compared to AKS. ACA is a serverless container platform that abstracts Kubernetes complexity while still allowing containerized workloads, making it ideal for stateless microservices that need to scale on demand. Azure Functions with a Service Bus trigger also scales based on messages and can scale to zero, but it does not natively support containerization (unless using custom containers which adds complexity) and has less control over graceful shutdown. AKS requires managing a cluster and does not scale to zero. App Service WebJobs are not containerized and do not scale based on Service Bus metrics.

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Deploy the microservice as an Azure Function with a Service Bus trigger on the Consumption plan.

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AKS with HPA based on Service Bus queue length

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Azure App Service WebJob with continuous mode

Question 11

You are developing a web application that allows users to upload images. The application is deployed on Azure App Service. After upload, the images must be processed to generate thumbnails and to extract metadata. The processing should happen asynchronously and must be resilient to failures. You need to design the solution using serverless components. The solution must minimize latency for the user during upload, and the processing must be retried automatically if it fails. You also need to ensure that the processing is idempotent, so that duplicate messages do not cause duplicate thumbnails. Which approach should you use?

Option A: Use Azure Functions with a Blob Storage trigger to process each image as it is uploaded. The function generates thumbnails and stores metadata in Cosmos DB. Use the `leaseBlob` property to prevent duplicate processing.
Option B: Use Azure Functions with an Event Grid trigger to process images. The function generates thumbnails and stores metadata in Cosmos DB. Use Event Grid's built-in retry policy and idempotent logic in the function.
Option C: Use Azure Logic Apps with a Blob Storage connector to process images. The logic app generates thumbnails and stores metadata in Cosmos DB. Configure retry policy on the connector.
Option D: Use Azure Functions with a Service Bus queue trigger. The web app sends a message to the queue after upload. The function processes the message, generates thumbnails, and stores metadata. Use message deduplication to ensure idempotency.

Accepted Answer

Azure Functions with Service Bus queue trigger and duplicate detection. It uses a Service Bus queue with duplicate detection, which ensures idempotent processing by automatically discarding duplicate messages within a defined time window. The web app uploads the image and immediately sends a message to the queue, minimizing user latency. The Azure Function triggered by the queue processes the image asynchronously, and Service Bus's built-in retry policy (via dead-lettering and max delivery count) provides resilience against failures.

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Azure Functions with Blob Storage trigger, using leaseBlob

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Azure Logic Apps with Blob Storage connector

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Azure Functions with Event Grid trigger

Question 12

Your team develops a containerized web app using Azure Kubernetes Service (AKS). You need to ensure that the application can automatically scale based on HTTP request load. Which Kubernetes resource should you configure?

Accepted Answer

HorizontalPodAutoscaler. The HorizontalPodAutoscaler (HPA) is the correct Kubernetes resource for automatically scaling the number of pod replicas based on observed CPU, memory, or custom metrics like HTTP request rate. In an AKS cluster, HPA adjusts the replica count of a Deployment or ReplicaSet to match the target metric, enabling the application to handle varying HTTP load without manual intervention.

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VerticalPodAutoscaler

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PodDisruptionBudget

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NetworkPolicy

Question 13

You are designing a serverless application using Azure Functions. The solution must process messages from an Azure Service Bus queue and update a Cosmos DB database. Which binding configuration should you use on the function?

Accepted Answer

Service Bus trigger with Cosmos DB output binding. The requirement specifies processing messages from an Azure Service Bus queue and updating a Cosmos DB database. A Service Bus trigger binds the function to the queue, and a Cosmos DB output binding writes the processed data directly to Cosmos DB, enabling a seamless serverless workflow without additional code for database operations.

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Service Bus trigger with Table storage output binding

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Blob trigger with Cosmos DB output binding

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HTTP trigger with Cosmos DB input binding

Question 14

Your Azure App Service web app experiences slow response times during peak hours. You suspect the App Service plan is under-provisioned. You need to scale out the app automatically based on CPU usage. What should you configure?

Accepted Answer

Configure autoscale rules in the App Service plan. Autoscale rules in the App Service plan allow you to automatically scale out (increase instance count) based on metrics like CPU usage. This is the correct solution because it dynamically adjusts capacity in response to demand during peak hours without manual intervention.

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Configure scheduled scaling in the app

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Manually increase instance count

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Configure scale up in the App Service plan

Question 15

You are developing a solution that processes large files uploaded to Azure Blob Storage. Each file must be processed by a long-running operation that may take up to 30 minutes. You need to use Azure Functions with a consumption plan. How should you handle the processing?

Accepted Answer

Use Durable Functions with a blob-triggered client function. D is correct because Azure Functions on a Consumption Plan have a default timeout of 5 minutes and a maximum of 10 minutes. A blob-triggered client function can start a Durable Functions orchestration, which can run for up to 30 minutes (or longer) by using the orchestration's timeout and retry capabilities, avoiding the Consumption Plan's timeout limit.

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Use a Blob trigger function with a retry policy

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Increase the function timeout to 30 minutes

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Use an Event Grid trigger function to process the blob