How J.J. Keller leveraged Split’s integration with Microsoft’s Azure DevOps services to bring robust feature flagging, experimentation and targeting to its CI/CD process
Split DemoDecember 7, 2022
On Demand Webinars
Testing in staging alone doesn’t give teams the confidence they need to move fast and reduce cycle times. Testing directly in production gives teams a clear understanding of how a change behaves. Pairing this with the ability to limit who sees a change in production means a superior developer experience and a better user experience.
Dave and Julian explore and share how Healthfirst migrated users to a new user experience in a safe and rapid way using Split
Progressive delivery experts from SmartBear and Split.io talk about how users can leverage the integration
Miro’s journey from the initial roll-out of Split to the key use cases at the center of a mature culture of experimentation
Doing away with exhausting release nights and support ticket spikes, they’ve turned IT back into a “day job” and they’ve gotten their evenings and weekends back. Once you learn the progressive delivery model, the rest of the steps are intuitive and simple to execute. Come learn how!
Join us as we break down Continuous Delivery with Split’s Delivery Evangelist Dave Karow and Pete Hodgson.
Progressive Delivery is the practice of decoupling deploy from release, refresh on the basics
En esta sesión de 45 minutos, el CTO de Split, Pato Echagüe, tendrá una plática con Federico Díaz, gerente de informática, y Juan Pablo Juárez, líder de Martech, en Naranja
Learn how to make better product decisions in the face of uncertainty & how to approach experiments in a methodical, open-minded way
Join a pedantic data scientist, Lizzie, as she discusses and explains experimentation from all angles
With new and innovative experimentation solutions, you can continuously perform A/B testing to base your next decision on hard data and metrics instead of gutfeel and opinions. The end result is that everyone in the business can agree upon credible, data-driven results, based on solid data experimentation.