Azure Batch is a service that enables you to run batch processes on high-performance computing (HPC) clusters composed of Azure virtual machines (VMs). Batch processes are ideal for handling computationally intensive tasks that can run unattended such as photorealistic rendering and computational fluid dynamics. Azure Batch uses VM scale sets to scale up and down and to prevent you from paying for VMs that aren't being used. It also supports autoscaling, which, if enabled, allows Batch to scale up as needed to handle massively complex workloads.
Azure Batch involves three important concepts: storage, pools, and jobs. Storage is implemented through Azure Storage, and is where data input and output are stored. Pools are composed of compute nodes. Each pool has one or more VMs, and each VM has one or more CPUs. Jobs contain the scripts that process the information in storage and write the results back out to storage. Jobs themselves are composed of one or more tasks. Tasks can be run one at a time or in parallel.
Batch Shipyard is an open-source toolkit that allows Dockerized workloads to be deployed to Azure Batch compute pools. Dockerized workloads use Docker containers rather than VMs. (Containers are hosted in VMs but typically require fewer VMs because one VM can host multiple container instances.) Containers start faster and use fewer resources than VMs and are generally more cost-efficient. For more information, see https://docs.microsoft.com/en-us/azure/virtual-machines/windows/containers.
The workflow for using Batch Shipyard with Azure Batch is pictured below. After creating a Batch account and configuring Batch Shipyard to use it, you upload input files to storage and use Batch Shipyard to create Batch pools. Then you use Batch Shipyard to create and run jobs against those pools. The jobs themselves use tasks to read data from storage, process it, and write the results back to storage.
Azure Batch Shipyard workflow
In this lab, you will use Azure Batch and Batch Shipyard to process a set of text files containing chapters from a famous novel and generate .ogg sound files from the text files.
Note: This lab requires an Internet connection with a minimum upload speed of approximately 1 MB/sec or higher. If you don't have that, or if the lab fails in Exercise 6, try creating a Windows VM in Azure and working the lab in the VM. You will find instructions for creating a Windows VM in Azure at https://docs.microsoft.com/en-us/azure/virtual-machines/windows/quick-create-portal.
In this hands-on lab, you will learn how to:
Click here to download a zip file containing the resources used in this lab. Copy the contents of the zip file into a folder on your hard disk.
This hands-on lab includes the following exercises:
Estimated time to complete this lab: 60 minutes.