– Case Study –
The Challenge
Founded in 2000, Fandango is one of America’s largest ticketing companies that sells movie tickets via their website as well as through their mobile app. As the go-to destination for just about 36 million moviegoers each month, Fandango’s web and mobile applications experience significant traffic during major movie releases. For multiple years, during peak sales periods, Fandango’s site has experienced significant performance issues due to the high level of online traffic. In anticipation of Star Wars: The Last Jedi, Fandango needed to be able to scale their platform to manage a potential calculated load of approximately 85,168 concurrent users on mobile and desktop applications. Our team was required to create a full performance test suite to run against all their environments in order to monitor site performance under heavy load and to identify bottlenecks.
Through collaboration with the Fandango team, we were able to assess peak traffic on the production environment and calculate a load of 85,168 concurrent users and an average of 2 Million page views per hour. Using this data, our team was able to:
- Replicate that same load at a reduced cost based on strategic load tests
- Prepare proof of concept performance scripts
- Understand how the system would perform and react under different kinds of pressure
- Identify six major performance bottlenecks affecting critical applications and database servers.
Our team also created an internal performance test environment using Jenkins, AWS & Ansible that significantly reduced the dependency on the more expensive tool, Blazemeter. This solution was not only effective but sustainable as it became a part of their continuous performance testing pipeline, allowing them to easily test the performance of their system before future new movie releases.
Our performance testing solutions enabled Fandango to optimize their system by a factor of 7x on the basis of performance and scalability. ‘Star Wars: The Last Jedi’ became Fandango’s top advance ticket seller for 2017.
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