Microsoft Azure Solutions Architect Expert AZ-305 Practice Question
Your company must run a CPU-intensive Monte Carlo simulation every night. The workload can be split into thousands of parallel tasks and typically runs for 6-8 hours. You want a fully managed Azure service that can:
Automatically provision and deallocate hundreds of compute nodes at runtime.
Let you choose low-cost Spot Virtual Machines to reduce execution cost.
Provide built-in job and task scheduling with retry policies, without requiring you to maintain any virtual machines yourself. Which Azure service should you recommend to run the simulations?
Azure Batch with a pool that uses Spot Virtual Machines
Azure Kubernetes Service (AKS) running a nightly CronJob
Azure Data Factory mapping data flow executed on an Azure Integration Runtime
Azure Functions on a Consumption plan orchestrated with Durable Functions
Azure Batch is designed for large-scale parallel and high-performance computing workloads. You define a pool of compute nodes, specify jobs and tasks, and Batch automatically handles queueing, scheduling, scaling, failure retries, and node health monitoring. Batch pools can be composed of Spot (formerly low-priority) virtual machines, lowering cost while accepting that nodes may be pre-empted; Batch transparently reschedules interrupted tasks. Azure Functions and AKS CronJobs can run scheduled code but require more orchestration to distribute thousands of parallel tasks and to deal with pre-emptible nodes. Azure Data Factory mapping data flows target data transformations, not general HPC simulations. Therefore, Azure Batch with Spot VM pools best meets the requirements.
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What are Spot Virtual Machines, and why are they used in Azure Batch pools?
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How does Azure Batch handle task scheduling and failure retries?
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Microsoft Azure Solutions Architect Expert AZ-305
Design infrastructure solutions
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