SLK leveraged QA Automation to enable the Insurance Carrier to seamlessly lift and shift its legacy stack to a modern MS Azure cloud-based instance. Consequently accelerating go-to-market and improving quality.
An American Insurance Company, Fortune 500 Insurance Carrier & Commercial Auto Insurer in the United States, was looking to modernize its application portfolio hosted on legacy mainframes. The digital transformation exercise involved migrating the applications to MS Azure based instances.
SLK owned and executed the end-to-end QA strategy for the modernization project successfully leveraging its low-code test automation platform to shrink the execution time and accelerate the go-to-market.
The insurance carrier had deployed a test automation strategy that proved inadequate. With a traditional approach to automation, the initiative had succeeded in achieving only 10-15% automation coverage over several years and was limited to web applications & web services, thereby delivering little or no value to the business.
In search of a radically different approach to solving the challenge, the insurance carrier approached SLK with a mandate to automate all their business-critical applications within one year. They looked to implement a robust QA automation strategy that would leverage the right tools to enable them to move to continuous testing and significantly reduce the time spent on regression testing, allowing in-sprint automation and power-on-demand releases.
SLK partnered with an expert team to perform the Lift Shift Migration approach. SLK completely owned the testing engagement for this migration initiative.
SLK’s multi-skilled team of QA experts SLK implemented the QA strategy on an Iterative model across three phases.
Legacy Application analysis and baseline to compare the target state application for Functional, Data migration & Performance testing.
End-to-end test cases automated with a low code platform regression automation suite developed for every iteration execution, reducing the execution time by 50%.
User Feedback and refactoring
execution time reduced by
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