how we built a Performance Testing Lab for Microservices Architecture
automated
testing framework
microservice
architecture validation
performance
monitoring & optimization
Services
Industries
Technologies
About the Project
Inturn is an enterprise inventory optimization platform that enables brands to efficiently manage slow-moving or excess stock across various industries. Given the complexity of their data-driven workflows, Inturn needed a comprehensive testing framework to validate microservices interactions, monitor big data processing performance, and ensure scalability without performance degradation.
Spiral Scout partnered with Inturn to develop an advanced automated testing and performance monitoring solution, allowing them to detect issues early, optimize system efficiency, and validate large-scale data transactions in real-time.
Objectives
- Build an automated testing framework to validate the interactions between microservices and big data pipelines.
- Develop a dedicated performance testing lab to monitor scalability, efficiency, and system reliability.
- Ensure seamless integration of test automation within the microservices architecture.
- Create scalable data generation tools to simulate real-world test scenarios with high accuracy.
Challenges
Solutions
Complex Microservices Interactions with Large-Scale Data Processing
Inturn’s platform relies on a highly distributed architecture, where multiple microservices interact asynchronously, processing large volumes of real-time data. Any unoptimized service-to-service interaction could introduce latency, data inconsistency, or failures at scale.
System Performance Monitoring & Optimization
We designed a custom test automation framework that simulates real-world data flows across multiple services, ensuring consistent validation of microservices interactions. Using event-driven testing techniques, we could identify and resolve inefficiencies in system behavior under different conditions.
Need for Scalable and Repeatable Test Data Generation
Testing large-scale data processing pipelines requires massive datasets that reflect real-world usage. Manual data creation was not feasible, and existing tools lacked the flexibility to generate structured test cases.
Data Generation and Validation Tools
Our team built a custom data generation and validation tool that automated the creation of test datasets for acceptance, integration, and performance testing. This allowed Inturn to simulate diverse business scenarios, test high-load conditions, and ensure consistent system behavior.
Performance Monitoring for Microservices Under Load
As the platform scaled, Inturn needed a systematic approach to monitor and optimize performance across services. Traditional monitoring solutions could not provide granular insights into bottlenecks within their microservices architecture.
Robust Architecture for Automated Testing
We established a dedicated performance testing lab that continuously monitored service execution times, database performance, network latency, and processing efficiency. This allowed for proactive identification of slowdowns, rapid debugging, and continuous system optimization.
Need for Automated Testing Solutions
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.
Temporal and Golang Integration
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.
OUR Project strategy
Overview of the critical steps that shaped the project’s success and addressed its key challenges.
Establishing a Dedicated QA & Test Automation Team
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.
Developing a Scalable Testing Framework
We implemented end-to-end test automation for microservices interactions and asynchronous workflows and then built a custom data generation tool to simulate production-scale datasets for accurate testing.
Performance Testing & System Monitoring
Created a performance testing lab to analyze system load, scalability, and real-time performance. 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 developed and deployed a monitoring solutions to track key performance metrics, ensuring system reliability.
Results & Impact
The automated testing framework and performance lab provided Inturn with a highly scalable and repeatable testing solution, ensuring their microservices-based architecture operates smoothly under all conditions.
By implementing end-to-end automation, real-time monitoring, and structured data validation, we enabled Inturn to optimize system efficiency, proactively detect potential issues, and maintain high availability. The performance lab significantly reduced debugging time, allowing Inturn’s engineering team to focus on feature development rather than firefighting system issues.
With QA software testing in place, Inturn now has the ability to confidently scale its platform, ensuring seamless processing of massive data volumes while maintaining system integrity.
Deliverables & Impact
- Automated Testing Framework – Developed a comprehensive microservices test automation solution, reducing manual QA time by 70%.
- Performance Testing Lab – Built a dedicated testing environment, enabling real-time system monitoring and load testing.
- Scalable Data Generation Tools – Created a custom test data generator, ensuring accurate simulation of large-scale processing.
- Microservices Architecture Validation – Provided end-to-end system validation, guaranteeing seamless integration of new services without breaking existing workflows.
The team’s successful work allowed Inturn to thoroughly test each microservice and its interactions within the big data architecture.
Spiral Scout AQA Team
OVERALL SCORE
At Spiral Scout, we believe that when it comes to software development and delivery, it’s time for a change.
5.0
SCHEDULING
On Time / Deadline
5.0
QUALITY
Service & Deliverables
5.0
COST
Value / Within Estimates
5.0
NPS
Willing to Refer
