40%
Reduction in response times
Improved performance during peak usage periods, enhancing overall system performance.
50%
Increase in transaction throughput
Increased throughput allowed the system to process more transactions concurrently, improving operational efficiency.
30%
Drop in CPU usage
Improved resource efficiency and system stability.
The leading financial software provider encountered scalability challenges as its user base expanded rapidly. This growth led to performance degradation during peak usage periods, impacting the real-time processing of financial transactions.
The client is a $20 billion IT giant with operations across the world providing mission-critical IT services. With operations in 70 countries globally, the client drives innovation in the IT world. The client has over 130,000 employees across the world and is a Fortune 500 global IT services leader.
PROJECT SUMMARY
A leading financial software provider faced scalability challenges as its user base rapidly expanded, leading to performance degradation during peak periods and affecting real-time financial transactions. To address these issues, the team implemented shift-left performance testing using Apache JMeter and Gatling, conducted in-depth architectural analysis, and optimized key system components. CI/CD integration with Jenkins and GitLab CI enabled continuous scalability monitoring. The solution resulted in a 40% reduction in response times during peak usage, a 50% increase in transaction throughput, and a 30% drop in CPU usage, significantly enhancing system performance and stability.
CHALLENGES
The software grappled with the consequences of rapid user base expansion, which increased transaction volumes and strained the existing infrastructure. During peak periods, the system experienced performance issues due to the higher transaction load, affecting system stability. The critical challenges included ensuring seamless real-time financial transaction processing and addressing scalability limitations. It was imperative to identify and mitigate specific scalability bottlenecks within the system architecture to implement effective solutions.
SOLUTION
To tackle these challenges, several strategic solutions were implemented:
Shift-Left Performance Testing: This involved integrating performance testing early in the development lifecycle to identify scalability bottlenecks proactively.
In-Depth Analysis: To gain insights into scalability challenges, a comprehensive analysis of the software's architecture and transaction flow was conducted.
Scalability Testing: Tools like Apache JMeter and Gatling were utilized to simulate varying user activity levels and peak loads, aiding in scalability testing.
Optimization Recommendations: The engineering team was advised to optimize database queries, introduce caching mechanisms, and implement horizontal scaling for critical components.
Collaboration and Implementation: Close collaboration between development and operations teams ensured seamless implementation and validation of scalability improvements.
CI/CD Integration: One-click performance testing was integrated into the CI/CD pipeline using tools like Jenkins and GitLab CI to monitor scalability with each software release continuously.

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