Azure Batch development

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Manage your workloads, not the infrastructure. This session covers how to use Azure Batch to build cloud-native Big Compute and HPC solutions. Batch provides APIs for creating and managing pools of resources and running jobs on them. It handles VM provisioning, management, and job scheduling under the hood, so your developers don’t have to.

Rendering
Media transcoding & processing
Test execution
Monte Carlo simulations
Genomics
Motorsports simulations
Deep Learning
OCR
Data ingestion, processing, ETL
R at scale
Compiled MATLAB
Engineering simulations
Image analysis & processing

UberCloud helps you run your
engineering simulations on
powerful cloud resources.

Cloud Services, VMs,
& VMSS
Azure Batch
VM Management & Job Scheduling
SaaS / Client
SolutionVFX Plug-Ins
Parallel R
APIs, CLIs, UIs
Developers
App Users
Azure
Batch AI
Render Managers

Queue
Pay-per-minute
licensing
Upload assets
Submit job
Return outputs
Client Plug-in’s
Batch Labs x-plat
client templates
Azure CLI /
PowerShell
Batch APIs
Monitor job
Windows & Linux
VM Images

Azure Batch Service allows running large-scale parallel and high-performance computing jobs efficiently in Azure. It creates and manages a pool of virtual machines, installs required applications, and schedules jobs to run on the nodes. Key features include auto-scaling pools, running jobs across multiple nodes, and monitoring resources and processes. The document provides an overview of Azure Batch and examples of how it can be used for applications like simulations in industries like automotive, computing, and more.

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