Cloud Computing platforms, such as Microsoft Azure, bring the availability of massive compute resources on a consumption billing model. The Azure Batch service simplifies the task of running distributed parallel compute jobs in the cloud.
This course will focus on the use of the Azure Batch service for job processing, using the rendering of a 3D ray-traced animation as an example.
The demos and real-world scenarios covered in this course will provide you with the knowledge and skills to utilize the power and flexibility of the Azure Batch service in distributed processing scenarios.
Alan Smith is a Windows Azure developer, trainer, mentor and evangelist at Active Solution in Stockholm. He has a strong hands-on philosophy and focusses on embracing the power and flexibility of cloud computing to deliver engaging and exciting demos.
Course Overview Hello, and welcome to my Pluralsight course, Microsoft Azure Batch: Getting Started. My name's Alan Smith, and I work as a consultant for Active Solution based in Stockholm. In this course, we'll be gaining an understanding of using Azure Batch to manage distributed processing workloads in Azure. Microsoft Azure Batch provides the functionality for managing pools of processing resources, scheduling and managing jobs, and visualizing the execution and completion status of jobs. Batch processing involves the use of dynamically scalable compute resources to perform the parallel processing of tasks in a job in order to complete the job processing in a time and cost efficient manner. We'll start the course by looking at cloud computing in Microsoft Azure and how cloud‑based environments can be optimal for parallel job processing. We'll then take a look at parallel job processing scenarios and the kinds of jobs that are suitable for running in Azure Batch. We'll then introduce the core Azure Batch functionality and introduce a sample scenario which we'll use throughout the course, rendering a 3D animation. In following modules, we'll take a more in‑depth look at the Azure Batch features and architecture. We'll look at the ways that we can create workloads in Azure Batch programmatically. We'll also focus on the management and optimization of jobs in Azure Batch and how we can handle and fix errors during job processing. We'll round off the course by looking how we can provision Batch services and automatically run Batch workloads using PowerShell and the Azure CLI. The requirements for this course are that you have some knowledge of C# programming. And to use Azure Batch, you'll need a Microsoft Azure subscription and Visual Studio, either 2015 2017 or any future versions.