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New Relic and Split enable customers to make data-driven decisions using feature flags, with a shared belief that you can’t improve what you can’t measure.

When versioning your API, consider the tradeoffs between distinct microservices and feature flags.

It’s easy to think of the user interface as the primary target for new functionality, with product teams eagerly watching important business metrics such as conversion rates and user engagement for improvements after each release. But behind the scenes, engineers are continually working on server-side innovations such as changes in…

Canary releases (also “canary deployments”) and feature flag rollouts are two common feature release strategies for testing in the production environment, increasing the safety of continuous delivery, deploying faster and more often. Both aim to reduce the “blast radius” of unforeseen problems and build confidence in a new release. Both…

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.

As our software development processes have evolved we’ve mostly said goodbye to the idea of defined product versions. Many modern product delivery teams are taking this a step further – even the concept of a “product release” is starting to fade. Instead our products are becoming a fluid, rapidly evolving set of features, assembled uniquely for any given user.

Following up from the excellent post by Pete Hodgson on Retiring Your Flags, and his presentation at the Meetup we recently sponsored, I wanted to dive into how Split plays a role in managing your flag debt. Feature flags (aka toggles, flips, gates, or switches) are a software delivery concept…

Teams working with feature flags usually come to the conclusion that a large number of active flags isn’t necessarily a good thing. While each active feature flag in your system delivers some benefit, each flag also comes with a cost. I’m going to explain those costs, such as cognitive load and technical debt, and explain how to avoid them.

Feature flagging systems can sometimes become victims of their own success. The benefits of feature flagging along with the broad applicability of the technique can lead to rapid adoption within an organization, and pretty soon the number of active flags can start to feel overwhelming. One way to keep your feature flags manageable is to introduce a categorization system.