Citation:

Gunjan Chaudhari , 2021. "Performance Testing Strategy for Cloud Migration on AWS", ESP Journal of Engineering & Technology Advancements 1(1): 298-301.

Abstract:

As enterprises transition legacy workloads to Amazon Web Services (AWS), the shift from static on premises infrastructure to dynamic, software-defined environments introduces unique performance risks. This paper outlines a comprehensive performance testing strategy designed to mitigate latency, throughput, and scalability bottlenecks during the migration lifecycle. Grounded in foundational cloud-computing scholarship and the AWS Well Architected Framework, the strategy integrates “Shift-Left” testing methodologies with AWS-native observability tooling so that migrated applications meet or exceed their pre-migration baseline performance metrics. We examine the roles of load simulation, resource right-sizing, and post-cutover optimization in sustaining operational excellence, and we present a three-phase testing lifecycle — Pre-Migration Baselining, During-Migration Validation, and Post Migration Optimization — together with a set of measurable key performance indicators (KPIs) that organizations can use to validate migration success.

References:

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Keywords:

Auto Scaling, AWS Cloud Migration, AWS CloudWatch, AWS Well-Architected Framework, AWS X-Ray, Capacity Planning, Cloud Migration Validation, Cloud Performance Optimization, Cloud-Native Applications, Continuous Performance Testing, Elastic Scalability, Infrastructure as Code (IaC), Latency Optimization, Load Testing, Observability, Performance Benchmarking, Performance Testing, Resource Right-Sizing, Scalability Testing, Shift-Left Testing, Throughput Analysis.