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A media company is migrating its video transcoding workflow to Azure. The workflow involves processing large video files, which can take several hours per file, and requires dynamic scaling of compute resources based on incoming job queues. The company needs to minimize operational overhead for managing virtual machines. Which Azure compute solution is best suited for this scenario?
- AAzure Virtual Machines
- BAzure Container Instances
- CAzure App Service
- DAzure Batch
Show answer & explanationAnswer & explanation
Correct answer: D. Azure Batch
Azure Batch is specifically designed for large-scale parallel and high-performance computing (HPC) workloads, such as video transcoding. It automatically provisions and scales pools of virtual machines, schedules compute-intensive tasks, and handles job management, significantly reducing operational overhead.
Why the other options are wrong
- A. Azure Virtual Machines would require manual or custom automation for scaling and job scheduling, increasing operational overhead.
- B. Azure Container Instances are good for single, isolated container tasks, but managing a complex, dynamically scaling workflow for many jobs would be more complex than with Azure Batch.
- C. Azure App Service is for web applications and APIs, not optimized for long-running, compute-intensive batch processing tasks.
Azure Batch
Azure Batch is a managed service for running large-scale parallel and high-performance computing (HPC) applications efficiently in Azure. It automatically provisions and manages compute resources, schedules jobs, and monitors progress.
- Managed service for HPC workloads
- Automatic scaling of compute resources
- Job scheduling and task management
Memory trick: Azure Batch is like a movie director for your big compute jobs, making sure every scene (task) runs perfectly.