AZ-204 Develop Azure compute solutions Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✗

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

  Why it's wrong here

  Azure Container Apps introduces an orchestrator and scaling controller that, while capable of queue-length-based scaling, adds management overhead and cost from the underlying Kubernetes-style infrastructure, which contradicts the requirement to minimise both. It is tempting because its built-in scale rule on queue length directly addresses the need to process messages as they arrive, making it the correct choice when the application requires automatic scaling to zero and fine-grained per-replica scaling, rather than the always-on, single-instance worker that ACI provides.

• ✗

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

  Why it's wrong here

  Running a containerized worker inside an Azure Virtual Machine (VM) with a container runtime introduces significant management overhead. This approach requires the user to provision, patch, and secure the underlying operating system, as well as install and maintain the container runtime environment (e.g., Docker). For a single container, this infrastructure management and the associated compute/storage costs are disproportionately high compared to serverless container options, making it an inefficient choice.

• ✗

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

  Why it's wrong here

  The `OnFailure` restart policy in Azure Container Instances (ACI) is designed for tasks that should only be retried if they terminate with a non-zero exit code, indicating an error. If the worker process successfully completes its current task and exits with a zero exit code, ACI will consider the container's job finished and will not restart it. This behavior is unsuitable for a continuously running worker that needs to remain active indefinitely to process new messages as they arrive.

• ✓

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

  Why this is correct

  Deploying the worker as a container group in Azure Container Instances (ACI) with the restart policy set to `Always` is the most appropriate solution. ACI offers a serverless platform, eliminating the need to manage underlying virtual machines or orchestration infrastructure. The `Always` restart policy ensures that the container is automatically restarted by ACI if it stops for any reason, guaranteeing continuous availability for the worker process to handle incoming messages efficiently and cost-effectively.