Elsevier builds healthcare education and clinical solutions-based products, our products are used daily by medical students, nurses, clinicians, practitioners, and healthcare professionals who rely on latest, up-to-the-moment information. To deliver new features and contents faster to our customers we wanted to steer away from doing traditional monthly releases to be able to release on demand . The bottleneck was running more than 3000 automated regression scripts in a short time. We worked on condensing 5-hour regression run into 30 mins by breaking the big Release on Demand challenge into smaller problems and addressed each one of them separately, Moving to current best DevOps practices like moving automation infrastructure to Docker, Kubernetes, infrastructure and configuration as code, managing environments, so that we can scale our tests and get fast feedback to developers to produce fixes faster. Faster fixes means quicker delivery of value to customers. Automation test results integration in JIRA using (ZAPI APIs), Improving pass percentage to avoid tedious manual verification for script failures, Implementing risk based separate UI and API test coverage for releases by categorizing and prioritizing tests

April 24 @ 09:55
09:55 — 10:35 (40′)

Lagan Khare