AWS Batch Service
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An AWS Batch Service is a online batch data processing service that is an AWS data processing service.
- …
- Counter-Example(s):
- AWS Glue, AWS EMR, or AWS Lambda.
- See: Data Streaming Platform.
References
2019
- https://aws.amazon.com/batch/
- QUOTE: AWS Batch enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. AWS Batch dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted. With AWS Batch, there is no need to install and manage batch computing software or server clusters that you use to run your jobs, allowing you to focus on analyzing results and solving problems. AWS Batch plans, schedules, and executes your batch computing workloads across the full range of AWS compute services and features, such as Amazon EC2 and Spot Instances.
There is no additional charge for AWS Batch. You only pay for the AWS resources (e.g. EC2 instances) you create to store and run your batch jobs.
- Benefits:
- Fully managed: AWS Batch eliminates the need to operate third-party commercial or open source batch processing solutions. There is no batch software or servers to install or manage. AWS Batch manages all the infrastructure for you, avoiding the complexities of provisioning, managing, monitoring, and scaling your batch computing jobs.
- Integrated with AWS: AWS Batch is natively integrated with the AWS platform, allowing you to leverage the scaling, networking, and access management capabilities of AWS. This makes it easy to run jobs that safely and securely retrieve and write data to and from AWS data stores such as Amazon S3 or Amazon DynamoDB.
- Cost optimized resource provisioning: AWS Batch provisions compute resources and optimizes the job distribution based on the volume and resource requirements of the submitted batch jobs. AWS Batch dynamically scales compute resources to any quantity required to run your batch jobs, freeing you from the constraints of fixed-capacity clusters. AWS Batch also dynamically bids for Spot Instances on your behalf, reducing the cost of running your batch jobs further.
- QUOTE: AWS Batch enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. AWS Batch dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted. With AWS Batch, there is no need to install and manage batch computing software or server clusters that you use to run your jobs, allowing you to focus on analyzing results and solving problems. AWS Batch plans, schedules, and executes your batch computing workloads across the full range of AWS compute services and features, such as Amazon EC2 and Spot Instances.
2018
- https://medium.com/@joshua.a.kahn/understanding-aws-batch-a-brief-introduction-and-sample-project-5a3885dda0ce
- QUOTE: AWS Batch organizes its work into four components:
- Jobs — the unit of work submitted to AWS Batch, whether it be implemented as a shell script, executable, or Docker container image.
- Job Definition — describes how your work is be executed, including the CPU and memory requirements and IAM role that provides access to other AWS services.
- Job Queues — listing of work to be completed by your Jobs. You can leverage multiple queues with different priority levels.
- Compute Environment — the compute resources that run your Jobs. Environments can be configured to be managed by AWS or on your own as well as the number of and type(s) of instances on which Jobs will run. You can also allow AWS to select the right instance type.
- QUOTE: AWS Batch organizes its work into four components: