How JioStar tackled rapid traffic surges and optimized performance testing with Gatling Enterprise

JioStar required a robust load testing solution to ensure maximum utilization of their infrastructure while avoiding unnecessary costs. The goal was to benchmark and optimize their system’s performance under varying loads, ensuring smooth operation during high-profile events like IPL, which sees more than 30 million concurrent users. This conscious strategy was driven by the need to avoid over-scaling infrastructure and instead focus on extracting the maximum value from their existing resources without compromising customer experience.

• Rapid traffic spikes: During key moments in live events, such as a cricket wicket or a legendary batsman entering the game, concurrent users can spike by 7-8 million within just 90 seconds, creating significant strain on infrastructure.
  
  
• Limited scalability windows: With minimal time to scale infrastructure during sudden traffic surges, maintaining consistent performance was a challenge.
  
  
• Complex user workflows: Real-time interactions, OTP-based logins, dynamic scorecard updates, and simultaneous user engagements on multiple app segments required seamless synchronization across services.

• Third-Party bottlenecks: Services like SMS OTP delivery often became overwhelmed during peak loads, delaying essential user actions and impacting overall experience.

• Simulate High-traffic scenarios: Emulated real-world user behaviors during peak moments, such as cricket match milestones, to replicate rapid spikes and test system resilience.
  
  
• Rapid spike management: Successfully managed user concurrency spikes of 7–8 million within just 90 seconds during key moments.
  
  
• Optimize resource allocation: Benchmarked infrastructure performance to maximize efficiency and avoid unnecessary over-scaling.

• Cost optimization: Streamlined resource allocation to avoid over-scaling, ensuring efficient utilization during high-demand periods.
  
  
• Real-Time monitoring: Gatling Enterprise’s real-time tracing identified and addressed bottlenecks effectively, reducing downtime risks.
  
  
• Faster error resolution: Enabled immediate detection of 5xx errors during load tests, allowing teams to stop tests early and address issues promptly.

• Enhanced service continuity: Ensured consistent performance across third-party services during peak loads, including OTP delivery systems, minimizing user disruptions.

• From JMeter to Gatling Enterprise: Transitioned from JMeter-based tools to Gatling Enterprise, which provided superior scalability and seamlessly integrated with the team’s API automation workflows built on Scala.
  
  
• Enhanced collaboration & monitoring features: Overcame limitations in Gatling Open-Source by adopting Enterprise’s advanced features, including real-time monitoring and enhanced orchestration, streamlining operations by eliminating manual load generator setups and boosting efficiency.