Comprehensive API Testing Ecosystem
Maintaining API test cases across multiple environments, for different load levels, and types of tests (eg. smoke, functional, regression) traditionally required separate tests be written and maintained. Test maintenance is expensive. If you have three lower environments that tests are run for, then you usually have at least three different tests you are trying to keep in sync. If you have a new API added for a microservice, then you have to modify and validate across all three tests at a minimum. If you are running different load levels for build tests verses load tests, for example, that could add additional tests that need to be maintained. This session will discuss a method of using one API test and modifying it at run time to support multiple environments, types of tests, and load levels and running as a microservice.
Shailaja Patel is a Principal Automation Engineer with the CIO office of IBM. She comes with a demonstrated history of working in the information technology and services industry. Skilled in Business Automation & Test Automation strategies, Shailaja also provides guidance to teams on various facets of automation. She brings over seven years of experience in information technology, concentrating on automation, DevOps, continuous testing, and performance testing. Prior to joining IBM in 2019, she held test automation roles for multiple clients of Accenture in India.
Lisa Waugh is an exceptional Software Development Engineer in Test and DevOps, passionate about quality and innovation, and currently a Testing Engineer Lead at IBM. She brings over 30 years of experience in information technology, with concentration on DevOps, Continuous Testing, and Performance Testing. She has a diverse background in multi-platform hardware and software technology and extensive technical experience in cloud, workstation, mainframe, and client server environments. Lisa is primarily involved with automating continuous testing pipelines to include performance, load, and system testing, identification of potential performance issues, and performance tuning of cloud microservices.