Azure Batch makes it easy to run large-scale jobs in parallel. You tell Batch what kind of VM you need, how to configure them, the jobs and tasks to run, and the service takes care of the rest. It’s great for Azure developers who need to scale-out work like engineering simulations, transcoding or financial risk models.
We are excited to announce today a preview of Azure Batch for Linux virtual machines. This brings the power of Batch “scheduling-as-a-service” to customers with Linux applications and workflows across industries and scientific research.
Under the covers, Batch is using Virtual Machine Scale Sets to deploy and manage Linux virtual machines. The Batch agent that manages job and task execution on compute nodes is written in Python for portability. This compliments the support in Batch for Cloud Services. VM Scale Sets will provide us with additional features down the road such as custom VM images.
Batch provides a consistent experience for developers across Linux and Windows virtual machines with the REST API. To better enable Linux users, we’ve published the Batch client in the Azure Python SDK and Azure Node.js SDK. Java support will be available shortly.
Docker is a useful tool for packaging application environments as containers to use with Batch. We have a sample that shows you how to configure Docker in pool setup, load containers with the application, then run a job in the container. We will be working with the community on using containers with Batch and welcome your feedback and suggestions.
For more information about Batch Linux Virtual Machine support, please check out this post.
Let us know what you’re doing with Batch and if you have any questions of suggestions on the Azure Batch forum.