INTURN - QA AUTOMATION (NOW VUE.AI)

DEVELOPING A PERFORMANCE TESTING LAB FOR MICROSERVICES ARCHITECTURE

Client

Inturn holds a unique position in the global market as the only enterprise software solution providing a system of record to manage slow-moving or excess inventory across various industries. In the face of global market uncertainties, Inturn equips brands for success by digitally optimizing their excess inventory.

Challenge

Inturn provides a comprehensive platform that supports businesses in inventory management, offer creation, and bidding on their own inventory - including items ranging from clothing and household chemicals to food and other goods. Their software is known for its high-performance capabilities, effectively reducing data processing time even with extensive item volumes.

However, one significant challenge that Inturn faced in software testing was the generation and management of vast volumes of test data for automated testing. This test data needed to be diverse, realistic, and span multiple scenarios, requiring scalable and repeatable mechanisms for generation and maintenance.

Furthermore, orchestrating the execution of tests across multiple microservices and coordinating their interactions proved to be a more complex task. Ensuring proper sequencing, synchronization, and data flow between services was a tough challenge, especially when working with asynchronous and event-driven architectures.

Consequently, Inturn was looking for a software development company to implement automated tests capable of handling large data processing in asynchronous mode and developing a performance testing lab for microservices architecture. They approached Spiral Scout's team for answers and a plan moving forward.

Strategy

To address these challenges, Spiral Scout established a 5-member dedicated Automation QA team, including AQA engineers, a QA architect, and senior software developers in test. Our initial step was to craft a tool that would allow us to generate and validate vast amounts of data that would be utilized for acceptance, integration, and performance testing.

Simultaneously, we aimed to create a robust architecture capable of seamlessly supporting the asynchronous processing of massive data volumes and integrating with microservices architecture. Once this approach was confirmed and approved by Inturn, we began work on the software solution.

integrating with microservices architecture

/ Inturn - QA automation (now Vue.ai)

Solutions

Technologies

CodeceptJS
Browserstack
Jest
Axios
BambooCI
Golang
jMeter

Our approach to developing a robust architecture capable of supporting asynchronous processing of large data volumes and integrating with microservices architecture involved transposing the primary approaches for microservices architecture implementation to an automated testing environment.

We developed a set of tools enabling us to construct the necessary infrastructure for automated testing. The microservices architecture for testing could be effortlessly integrated into any type of test, including front-end, back-end, and performance tests. The tests we created facilitated work at all testing levels, from end-to-end testing to isolated testing of individual microservices within the application itself.

A key focus was placed on the system for monitoring and testing the current state of system performance. The release enabled us to swiftly check the performance state, identify degradations, and simplify the location of specific performance leaks.

In addition, in our technical solution set, alongside Golang’s concurrency model and performance, we implemented Temporal as the backbone for workflow automation and tested that implementation. This powerful combination meant that each service was fully tested with automation and could operate independently, yet be part of a cohesive, orchestrated system."

Results

Our framework is capable of covering various scenarios, from data ingestion and processing to storage and retrieval, ensuring that the system performs as expected under varying conditions. Moreover, it enables scalability QA software testing, ensuring that the system can handle increasing data volumes without performance degradation or failure. This solution empowers Inturn to serve its clients with confidence and efficiency.