## Basics of Batch Computing

**Batch computing** involves running a series of jobs that can operate independently or in parallel. **AWS Batch** streamlines this by dynamically scaling EC2 instances or using AWS Fargate to match the workload demand, making it suitable for large-scale tasks like **data processing** or **media rendering**.

## Job Definitions

**Job definitions** in AWS Batch detail how individual jobs should run, specifying resource needs like **CPU** and **memory**, environment variables, and the execution command or script. These definitions allow for the customization of job execution, whether for simple single-node tasks or complex multi-node computations, ensuring each job has the resources it needs to run efficiently.

## Job Queues

**Job queues** in AWS Batch manage when and how jobs are run by holding them until resources are available. Queues can be prioritized, allowing you to dictate which jobs run first based on urgency or business needs. This system provides control over job execution order and resource allocation, ensuring optimal use of compute environments.

## Key Takeaways

AWS Batch automates the **scaling** and **management** of resources for batch computing, with job definitions providing customized execution settings and job queues ensuring efficient job processing based on priority and available resources.

What does a job definition in AWS Batch specify?

How does AWS Batch manage the order in which jobs are executed?

What is the main benefit of AWS Batch automatically provisioning compute resources?

AWS Solutions Architect Associate

AWS Batch

Basics of Batch Computing

Job Definitions

Job Queues

Key Takeaways