A Cost-Effective and Scalable Processing of Heavy Workload with AWS Batch-Reference-Cited by-同舟云学术

A Cost-Effective and Scalable Processing of Heavy Workload with AWS Batch

Published:2022-06-30 Issue:2 Volume:10 Page:144-149
ISSN:2347-470X
Container-title:International Journal of Electrical and Electronics Research
language:en
Short-container-title:IJEER

Author:

Kumar Nagresh¹,Sharma Sanjay Kumar¹

Affiliation:

1. Department of Computer Science, Banasthali Vidyapith, Rajasthan, India

Abstract

Recent technological advancements in the IT field have pushed many products and technologies into the cloud. In the present scenario, the cloud service providers mainly focus on the delivery of IT services and technologies rather than throughput. In this research paper, we used a scalable cost-effective approach to configure AWS Batch with AWS Fargate and CloudFormation and implemented it in order to handle a heavy workload. The AWS service configuration procedure, GitHub repository, and Docker desktop applications have been clearly described in this work. A cost-effective configuration and architecture of AWS Batch processing are given to provide high throughput. The processing of heavy workload by AWS Batch is represented in terms of execution time and the result shows that the concurrent execution reduces the execution time. To enhance the throughput heavy workload using batch processing an "Amazone FSx for Lustre" can also be used.

Publisher

FOREX Publication

Subject

Electrical and Electronic Engineering,Engineering (miscellaneous)

Reference25 articles.

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