Cloud-native application development in AWS often requires complex, layered architecture with synchronous and asynchronous interactions between multiple components, e.g., API Gateway, Microservices, Serverless Functions, and system of record integration. Performance engineering requires analysis of the performance and resiliency of each component level and the interactions between these. While there is guidance available at the technical implementation of components, e.g., for AWS API Gateway, Lambda functions, etc., it still mandates understanding and applying end-to-end best practices for achieving the required performance requirements at the overall component architecture level. This article attempts to provide some fine-grained mechanisms to improve the performance of a complex cloud-native architecture flow curated from the on-ground experience and lessons learned from real projects deployed on production.

Problem Statement

The mission-critical applications often have stringent nonfunctional requirements for concurrency in the form of transactions per second (henceforth called “tps”). A proven mechanism to validate the concurrency requirement is to conduct performance testing.

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