Azure Batch

Azure Batch Documentation

1. Overview
     1.1. What is Azure Batch?
2. Quickstarts
     2.1. Run a Batch job - CLI
     2.2. Run a Batch job - Portal
     2.3. Run a Batch job - .NET
     2.4. Run a Batch job - Python
3. Tutorials
     3.1. Parallel file processing - .NET
     3.2. Parallel file processing - Python
     3.3. Scene rendering with Arnold
     3.4. Rendering using Batch Explorer
     3.5. Parallel R simulation
4. Samples
     4.1. Code samples
          4.1.1. Azure code samples
          4.1.2. Batch samples repo
     4.2. Azure CLI
5. Concepts
     5.1. Developer features
     5.2. APIs and tools
     5.3. Quotas and limits
     5.4. Supported VM sizes
6. How-to guides
     6.1. Manage Batch accounts
          6.1.1. Manage Batch accounts with the portal
          6.1.2. Manage Batch accounts with Batch Management .NET
     6.2. Authenticate with Azure AD
          6.2.1. Azure AD with Batch service
          6.2.2. Azure AD with Batch Management
     6.3. Create application packages
     6.4. Create and manage pools
          6.4.1. Autoscale compute nodes
          6.4.2. Choose a VM size for compute nodes
          6.4.3. Configure access to compute nodes
          6.4.4. Create a pool with a custom image
          6.4.5. Create a pool in a virtual network
          6.4.6. Mount an Azure file share
          6.4.7. Use RDMA or GPU instances
          6.4.8. Use Linux compute nodes
          6.4.9. Use low-priority VMs
          6.4.10. Checking for pool and node errors
     6.5. Manage jobs and tasks
          6.5.1. Job preparation and completion tasks
          6.5.2. Concurrent node tasks
          6.5.3. Task dependencies
          6.5.4. User accounts for running tasks
          6.5.5. Submit a large number of tasks
     6.6. Persist job and task output
          6.6.1. Persist output with Batch API
          6.6.2. Persist output with File Conventions library
     6.7. Monitor Batch solutions
          6.7.1. Use metrics and diagnostic logs
          6.7.2. Monitor with Application Insights
          6.7.3. Count resources by state
          6.7.4. Query resources efficiently
     6.8. Use scripting tools
          6.8.1. Use Azure PowerShell
          6.8.2. Use Azure CLI
               6.8.2.1. Use Batch CLI templates
     6.9. Use Batch Node.js SDK
7. Run workloads
     7.1. MPI jobs
     7.2. Container workloads
     7.3. Rendering
          7.3.1. Rendering using Azure
          7.3.2. Rendering VM images
          7.3.3. Batch rendering capabilities
          7.3.4. Using Batch rendering
          7.3.5. Using render managers
          7.3.6. Rendering application reference
          7.3.7. Storage and data movement
          7.3.8. Rendering architectures
     7.4. Data processing with Batch and Data Factory
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. Resource Manager template
     8.9. Batch Analytics
          8.9.1. Pool create event
          8.9.2. Pool delete start event
          8.9.3. Pool delete complete event
          8.9.4. Pool resize start event
          8.9.5. Pool resize complete event
          8.9.6. Task start event
          8.9.7. Task complete event
          8.9.8. Task fail event
     8.10. Batch compute node environment variables
9. Resources
     9.1. Azure Roadmap
     9.2. Batch Community
     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