Shopmonkey streamlines and simplifies the operations of auto repair shops, creating a better experience for their customers and giving shop owners more insight into their business. The platform handles the entire repair process from customer service, to parts inventory, to workflow management.
After years of rapid growth, Shopmonkey had outgrown v1 of its application and the architecture decisions the engineering team made during the scrappy start-up days — a problem that should be familiar to many technology leaders.
The decision was made to freeze v1 and begin working on v2, which would give Shopmonkey a new foundation to innovate from. Of course, the end users couldn’t know that anything was different or notice any disruption in their operations when Shopmonkey was ready to migrate from the old system to the new one.
What made Shopmonkey’s platform migration so challenging are the vast number of edge cases created from the different services offered by different shops, integrations with payment processors, inventory management, vehicle diagnostic information, and other data that feed into the system.
In addition, more than 500 regression tests that were built for v1 would need to be rebuilt for v2. These tests, which took more than 90 minutes to complete, would have caused significant delays for the migration project and cost the company tens of thousands of dollars in engineering time.
To prevent disruptions in service, and to give Shopmonkey’s development team a safety net to launch new v2 features quickly, the team wanted to have comprehensive end-to-end regression testing for all the workflows in the application — more than 800 separate test cases.
Managing 800 separate tests — building them, maintaining the infrastructure to run them, and maintaining them as things change — would force Shopmonkey to hire at least six test automation engineers and take several years. The team wanted something faster and a whole lot cheaper.
Offset $600K/year in QA engineering and infrastructure costs
After experimenting with in-house regression testing, Shopmonkey estimated that they would need to hire at least six full-time staff to build and maintain the test coverage they were looking for. With QA Wolf, their QA costs are 20% of what they would otherwise have been.
Helped Shopmonkey bring v2 of their application to market faster
By building a brand new test suite for the v2 application, QA Wolf let Shopmonkey’s engineering team focus on delivering the new platform.
Uncovered performance and load management issues in the application
The QA Wolf infrastructure runs test suites in parallel, with each test running in a separate container. The load from hundreds or thousands of concurrent tests running at the same time simulates what a major spike in real-world traffic would do to an application environment. QA Wolf helped Shopmonkey determine what resources were needed to give their customers the fastest experience.
QA Wolf is a hybrid platform & service that helps software teams ship better software faster by taking QA completely off their plate.
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