Azure Batch

Official Documentation

Service Description

The automated execution of large computational processes (e.g., for mathematical calculations, video rendering, data analyses) normally poses several challenges: the temporary provision of sufficient compute capacity and distribution of the computation logic and associated data are difficult or impossible to implement in conventional IT. Azure Batch can handle these tasks, making the capabilities of batch processing available to every Azure user. The service provides the cluster environments required, distributes the calculation logic provided by EXE file or script, manages the execution, and releases the computational resources following completion so that only the required resources are billed.

Getting Started

  1. 9/27/2016, Webpage
    Azure Batch helps you run large-scale parallel and HPC applications efficiently in the cloud. It's a platform service that provides job scheduling and autoscaling of a managed...
  2. 12/12/2014, Video, 0:11:46
    Mark tells Scott all about how to run compute intensive jobs at scale in the cloud.Areas covered in this video: Azure batch example scenarios View Azure batch service in the...
  3. 3/30/2016, Video, 0:42:26
    Azure Batch enables large-scale parallel and compute-intensive workloads to be easily and efficiently run in the Azure; execute your new or existing applications on tens to...
  4. 2/10/2017, Video, 1:12:08
    High Performance Computing (HPC) applications are some of the most challenging to run in the cloud due to requirements that include fast processors, low-latency networking,...
  5. 11/6/2017, Video, 0:14:10
    Dave Fellows joins Donovan Brown to chat about a new service called Azure Batch Rendering, which is built on the Azure Batch service to provide capabilities for rendering 3D...
  6. 9/30/2016, Video, 0:58:50
    High performance computing (HPC) applications are some of the most challenging to run in the cloud due to requirements that can include fast processors, low-latency...



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Web Content

Azure Documentation

1. Batch Documentation
2. Overview
     2.1. What is Azure Batch?
3. Quickstarts
     3.1. Run a Batch job - CLI
     3.2. Run a Batch job - Portal
     3.3. Run a Batch job - .NET
     3.4. Run a Batch job - Python
4. Tutorials
     4.1. Parallel file processing - .NET
     4.2. Parallel file processing - Python
     4.3. Scene rendering with Arnold
     4.4. Parallel R simulation
5. Samples
     5.1. Code samples
          5.1.1. Azure code samples
          5.1.2. Batch samples repo
     5.2. Azure CLI
6. Concepts
     6.1. Developer features
     6.2. APIs and tools
     6.3. Quotas and limits
     6.4. Supported VM sizes
7. How-to guides
     7.1. Manage Batch accounts
          7.1.1. Manage Batch accounts with the portal
          7.1.2. Manage Batch accounts with Batch Management .NET
     7.2. Authenticate with Azure AD
          7.2.1. Azure AD with Batch service
          7.2.2. Azure AD with Batch Management
     7.3. Create application packages
     7.4. Create and manage pools
          7.4.1. Autoscale compute nodes
          7.4.2. Choose a VM size for compute nodes
          7.4.3. Configure access to compute nodes
          7.4.4. Create a pool with a custom image
          7.4.5. Create a pool in a virtual network
          7.4.6. Use compute-intensive VMs
          7.4.7. Use Linux compute nodes
          7.4.8. Use low-priority VMs
     7.5. Manage jobs and tasks
          7.5.1. Job preparation and completion tasks
          7.5.2. Concurrent node tasks
          7.5.3. Count tasks by state
          7.5.4. Task dependencies
          7.5.5. User accounts for running tasks
          7.5.6. Run Batch jobs without code
     7.6. Persist job and task output
          7.6.1. Persist output with Batch API
          7.6.2. Persist output with File Conventions library
     7.7. Run workloads
          7.7.1. MPI jobs
          7.7.2. Container workloads
          7.7.3. Rendering
          7.7.4. Data processing with Batch and Data Factory
     7.8. Monitor Batch solutions
          7.8.1. Use metrics and diagnostic logs
          7.8.2. Monitor with Application Insights
          7.8.3. Efficient list queries
     7.9. Use developer tools
          7.9.1. Use Batch .NET
          7.9.2. Use Batch Python
          7.9.3. Use Batch Node.js
          7.9.4. Use PowerShell cmdlets
          7.9.5. Use Azure CLI
8. Reference
     8.1. Azure CLI
     8.2. Azure PowerShell
     8.3. .NET
     8.4. Java
     8.5. Node.js
     8.6. Python
     8.7. REST
          8.7.1. Batch Service
          8.7.2. Batch Management
     8.8. Batch Analytics
          8.8.1. Pool create event
          8.8.2. Pool delete start event
          8.8.3. Pool delete complete event
          8.8.4. Pool resize start event
          8.8.5. Pool resize complete event
          8.8.6. Task start event
          8.8.7. Task complete event
          8.8.8. Task fail event
     8.9. Batch compute node environment variables
9. Resources
     9.1. Azure Roadmap
     9.2. Batch forum
     9.3. Batch Shipyard
     9.4. Blog
     9.5. HPC solutions in Azure
     9.6. Pricing
     9.7. Pricing calculator
     9.8. Resource Manager template
     9.9. Service updates
     9.10. Stack Overflow
     9.11. Videos

Online Training Content

Date Title

Tools

Tool Description
Azure Batch Explorer The Azure Batch Explorer is a Windows Presentation Foundation (WPF) application used for viewing, managing, monitoring, and debugging entities within an Azure Batch account. While this application is not officially supported, it is updated periodically, and is an invaluable tool not only for those new to Batch, but anyone developing or managing Batch applications.

Videos

Date Title Length
5/9/2018
Getting Started with Visual Studio Tools for AI
0:20:55
5/9/2018
Developing large-scale parallel compute and HPC solutions with Azure Batch
0:20:55
11/6/2017
Azure Friday: Azure Batch Rendering Service
0:14:11
11/6/2017
Azure Batch Rendering Service
0:14:10
10/16/2017
Cloud Tech 10 - 16th October 2017 - Batch AI, Durable Functions, File Share Snapshots and more!
0:05:59
10/11/2017
Past, present, and future: GPU and AI infrastructure on Microsoft Azure
1:11:01
10/11/2017
Building a Hollywood blockbuster using Microsoft Azure Batch rendering
1:01:43
10/11/2017
Design big data applications using Azure Storage
1:00:53
9/29/2017
Meet the most demanding HPC customer needs on Azure with Cycle Computing and Batch
1:25:27
9/28/2017
Design big data applications using Azure Storage
1:04:28

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