AWS Batch

AWS Batch

Introduction

Maintainer: DBA Demo Admins DBA_Demo_Admins@bmc.com

AWS Batch is a fully managed batch computing service that plans, schedules, and runs your containerized batch or ML workloads across the full range of AWS compute offerings, such as Amazon ECS, Amazon EKS, AWS Fargate, and Spot or On-Demand Instances.

• AWS Batch Additional Information

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Use Case Overview

This workflow allows organizations to automate cloud-based data processing jobs alongside on-premise workflows in one unified platform. It enables efficient resource scaling through AWS Batch’s auto-scaling capabilities, while Control-M manages job dependencies and triggers across hybrid environments. Additionally, Control-M provides real-time monitoring, error handling, and auditing for AWS Batch jobs, ensuring smooth operations and compliance.

Use Case Technical Explanation

This workflow will start by orchestrating AWS to create a compute environment first-job-run-environment using EC2 as the provisioning model. A job queue first-run-job-queue is defined. Depending on the run (1 or 2), job definitions for the first-run-batch job will change. On run 1, the first-run-batch job performs an “echo hello world” command, whereas on run 2, the first-run-batch job performs an “echo Howdy, world” command.

For additional information on the Helix Control-M AWS Batch job type, select the following links:

• Control-M Integrations - Control-M for AWS Batch
• Helix Control-M AWS Batch Job Type Detail Information
• Helix Control-M AWS Batch Job Type Documentation

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Demo Environment Information

Environment	Status	Folder
Helix Production	Available	zzz-aws-batch
VSE CTM PROD	Coming soon!
VSE CTM QA	Coming soon!