We had an amazing time at this year’s AWS re:Invent in Vegas. We were able to chat with more than 2,000 developers, operators, and cloud architects that stopped by. A few observations: Feature flags were a hot topic. We chatted with quite a few organizations that are already getting value…
Great teams don’t run experiments to prove they are right; they run them to answer questions. Guard against wishful thinking and hidden biases with this shortlist of core principles for productive online controlled experiments. (Video, transcript and screenshots from talk given at Pinterest HQ on September 13, 2019)
Here’s the video of my talk, “Experimentation for Speed, Safety & Learning in CD” delivered at QCon New York 2019. I’ve edited it down to 39 minutes, so you can easily fit this into a lunch hour or possibly a commute. Text and screenshots follow the video below. Transcript and…
Feature launches in leading engineering teams increasingly look like a ramp rather than a one time switch, going through dogfooding, debugging, max power ramp, scalability and learning phases.
Here are 12 ways a robust feature flag solution can bring benefits to your organization.
Here are 15 ways feature flags can make software rollouts run smoother than ever. Safe testing in production, stress-free migrations and much more.
Product teams that don’t take into account a user communication and user feedback collection strategy as part of their experiments risk not getting enough data to evaluate results. This article walks through a couple key communication steps that products should follow to ensure effective and timely product experiments.
We are thrilled to announce that Twilio has chosen Split as a key component of their experimentation capability to drive faster product decisions.
We demoed our new feature experimentation platform at the event, and the response was overwhelming. Engineering leaders saw the value of controlling the blast radius of a new feature, by only exposing it to beta customers or even doing a percentage-based roll-out to users that match specific attributes.
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