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Table of contents
AWS Batch
Components of AWS Batch
Job Definitions
Job Queues
Compute Environment
Frequently Asked Questions 
What is Batch Computing?
What is the reason of using AWS Batch?
AWS Batch is optimised for what use cases?
AWS Batch supports what types of batch jobs?
What are the examples of  "compute resources" ?
What exactly is a compute environment?
Last Updated: Mar 27, 2024

AWS Batch

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Have you ever wondered how you can emphasise on growing the business, reducing human error, boosting speed and accuracy, and automating costs?

growing buisness

Yes, you heard it right, it’s AWS Batch!

A batch job is, in the simplest words, a scheduled computer program that is assigned to execute without additional human input. During the day, batch jobs are frequently queued up and carried out when the computer is idle in the evening or on the weekend.

IT experts can arrange and carry out batch processing activities in the Amazon Web Services public cloud using the AWS Batch service.

In this article, we’ll be studying about AWS Batch and analysing how it is improving the performance of human work. 

AWS Batch

AWS Batch is a bunch of batch management capabilities. Developers, scientists, and engineers may run hundreds of thousands of batch computing jobs on AWS with the help of AWS Batch.

AWS Batch

Whereas AWS Batch Compute Environment is a group of computing resources used to execute jobs. Both managed and unmanaged compute environments, which are managed by customers, are supported by AWS Batch.

Jobs are automatically and asynchronously run across multiple compute instances through batch computing. Running a single job could be trivial, but scaling up multiple jobs, especially ones with many dependencies, might be challenging. When it comes to this, using a fully managed service like AWS Batch has a lot to offer significant benefits.

A series of "jobs'' can be executed on one or more computers with the help of AWS Batch computing. The AWS Batch job control language, command-line arguments, control files, and scripts can all be used to predefined input parameters. Multiple jobs can be scheduled and sequenced easily by making a batch job dependent on the completion of preceding jobs or the availability of specific inputs.

Workflow of AWS

Your batch computing workloads are planned, scheduled, and executed out by AWS Batch using the full range of AWS compute services and features, like AWS Fargate, Amazon EC2, and Spot Instances. AWS Batch doesn't come with any extra charges. Only the AWS resources you create to store and run your batch jobs are payable.

Next, we’ll discuss about the AWS Batch Components: 

Components of AWS Batch

Running batch jobs across several Availability Zones within a Region is simplified by AWS Batch.

A new or existing VPC can be created by AWS Batch compute environments. You can define job definitions that indicate which Docker container images to run for your jobs, once a compute environment is up and associated with a job queue. 

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It is an unit of work that you send to AWS Batch, such as a shell script, Linux executable, or Docker container image. It has a name, uses parameters you specify in a job definition, and runs as a containerized application on AWS Fargate or Amazon EC2 resources in your compute environment. Jobs can depend on the successful completion of other jobs and can refer to other jobs by name or by ID. Jobs that are containerized can make references to commands, parameters, and container images. 

There are several independent, simple jobs that you can submit. You can also go through these topics to understand better about jobs -

Next, we’ll discuss the Job Definitions. 

Job Definitions

How a job is to be run is specified in the job definition. A job definition can be thought of as a blueprint for the resources you will need to do your job. To grant access to various AWS resources, you can supply your job with an IAM role. Additionally, you specify the requirements of CPU and memory. 

job definitions and queue

Additionally, the job definition has control over environment variables, persistent storage mount points, and container properties. When submitting individual Jobs, it is possible to override many of the specifications in a job definition by specifying new values.

Let us now understand about Job Queues.

Job Queues

A job queue is the data structure maintained by the job scheduler software containing jobs to run. An AWS Batch job is submitted to a particular job queue, where it resides until it is scheduled onto a compute environment. A job queue has one or more compute environments associated with it.

job queues

Additionally, you may set priority value for these computing environments and even for individual job queues. You may, for instance, have a high priority queue for time-sensitive jobs that you submit and a low priority queue for jobs that can run anytime compute resources are less cheap.

As it is clearly depicted in the above image that before being scheduled to run in a compute environment, jobs are submitted to a job queue where they wait. AWS accounts are allowed to have several job queues.

Compute Environment

A collection of managed or unmanaged compute resources are used to run jobs together to form a compute environment. You can specify the desired compute type (Fargate or EC2) at various levels of detail when using managed compute environments. You can create computing environments that use a certain EC2 instance model, such as the c5.2xlarge or m5.10xlarge.

compute environment

When needed, AWS Batch efficiently launches, manages, and terminates various compute types.You can also use managed compute environments to meet business requirements. This environment in a AWS Batch helps you to manage the capacity and instance types of the compute resources within the environment. Your own computing environments can also be managed. 

Now, let us discuss some FAQs based on the above discussion.


Frequently Asked Questions 

What is Batch Computing?

Batch computing is the automatic execution of a series of programs (referred to as "jobs") on one or more computers. By using scripts, command-line arguments, control files, or job control language, input parameters can be predefined. The sequencing and scheduling of multiple jobs is crucial since a given batch job could be dependent on the completion of preceding jobs or the availability of specific inputs, making interactive processing impractical.

What is the reason of using AWS Batch?

You can focus on developing applications or analysing results rather than setting up and managing infrastructure since AWS Batch handles job execution and compute resource management. Consider using AWS Batch if you're considering to run or move batch workloads to AWS.

AWS Batch is optimised for what use cases?

AWS Batch is designed for batch computing and applications that scale by executing several jobs at once. Excellent examples of batch computing applications include deep learning, genomics analysis, financial risk models, Monte Carlo simulations, animation rendering, media transcoding, image processing, and engineering simulations.

AWS Batch supports what types of batch jobs?

Any job that can be executed in a Docker container is supported by AWS Batch. Jobs indicate the amount of vCPUs and memory they require. 

What are the examples of  "compute resources" ?

EC2 instances or AWS Fargate compute resources are examples of AWS Batch Compute Resources.

What exactly is a compute environment?

A group of computing resources are referred to as an AWS Batch Compute Environment and are used to execute jobs. Both managed and unmanaged compute environments, which are managed by customers, are supported by AWS Batch. Managed compute environments are those that are provisioned and maintained by AWS.


To conclude the discussion, we’ve extensively looked at the components of AWS Batch, where we’ve looked upon the jobs, job queues concepts, and compute environments. Next you will also get the idea of setting up AWS Batch in your System. Lastly, we’ve also discussed some frequently asked questions.

We hope this article has helped you in understanding the AWS Batch, but the knowledge never stops. Have a look at more related articles:AWS Lambda FoundationsAWS-IAM-RolesAWS Cloud Computing and many more.

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