Microsoft Azure Solutions Architect Expert AZ-305 Practice Question
Your company renders high-resolution video frames using a proprietary command-line application that must run on Windows Server with GPU acceleration. Each night about 20,000 independent rendering jobs are submitted, and the output is written to Azure Blob Storage. You need a fully managed, cost-efficient compute platform that can automatically provision and deallocate hundreds of GPU-enabled virtual machines, handle job queuing and scheduling, and require minimal custom orchestration code. Which Azure service should you recommend?
Azure Container Instances (ACI) with Event Grid-based job orchestration
Azure Functions running on a Premium plan with event triggers
Azure Batch with GPU-enabled pools and automatic pool scaling
Azure Kubernetes Service (AKS) with the Kubernetes Event-Driven Autoscaler (KEDA)
Azure Batch is purpose-built for large-scale, parallel, or high-performance batch workloads. It automatically creates and manages pools of virtual machines (including GPU SKUs), queues and schedules jobs, distributes tasks, collects results, and scales the pool up or down so you pay only for the compute consumed. Azure Kubernetes Service, Azure Functions, and Azure Container Instances can run containerized workloads, but they require you to build and operate custom job schedulers or are constrained by execution limits and lack integrated VM-level autoscaling across thousands of tasks. Therefore, Azure Batch best meets the requirements for a managed, scalable batch rendering solution.
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Microsoft Azure Solutions Architect Expert AZ-305
Design infrastructure solutions
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