AZ-305 Question 165
Single answerA manufacturing company needs to perform large-scale 3D model processing and analysis every night with minimal operational overhead. These compute-intensive jobs involve converting raw CAD files into optimized geometries. The company wants an Azure-native service that can automatically manage job scheduling, scale compute nodes based on workload, and minimize idle infrastructure costs. Which Azure service should they use for this batch processing requirement?
- A
Azure Batch
- B
Azure Virtual Machines with manual scaling
- C
Azure Container Instances
- D
Azure Synapse Analytics with serverless SQL pools
Show answer and explanation
Correct answer: A
Explanation
Azure Batch enables high-scale batch and HPC processing by automatically scheduling jobs and managing compute resources, allowing organizations to efficiently run parallel tasks without manual orchestration. It integrates well with Azure Storage and provides straightforward scaling options. For more details, see: https://docs.microsoft.com/azure/batch/
- A. Correct.
Correct. Azure Batch is specifically designed for large-scale parallel and HPC workloads, automating job scheduling and resource scaling. It integrates with Azure Storage and allows you to pay only for the compute resources used, making it an ideal solution for scheduled batch jobs.
- B. Incorrect.
Incorrect. While you could run background jobs on Azure Virtual Machines, you would be responsible for manually orchestrating both scaling and job scheduling, leading to higher operational overhead. This setup is less efficient for large nightly batch runs compared to Azure Batch.
- C. Incorrect.
Incorrect. Azure Container Instances (ACI) is a good option for quickly running containerized tasks, but it does not provide the built-in job scheduling, autoscaling, or orchestration features needed for large-scale batch processing over many nodes. You would need additional services to manage these tasks at scale.
- D. Incorrect.
Incorrect. Azure Synapse Analytics with serverless SQL pools is primarily used for on-demand querying and data processing within a data warehouse or data lake context. It does not natively cater to automating non-SQL tasks like 3D model conversions or HPC scenarios as effectively as Azure Batch.