Monitoring

By pushing feature flagging metadata into New Relic, you can understand the impact of a feature change across any metric you care about, in real time.

We’ll take a quick look at using New Relic to sleuth through a production incident, and then walk through setting it up for a Spring Boot web service.

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.

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…

Split manages more than 50 billion feature flags changes around the world every day. A recent study shows that about 5 to 6% of feature flags are rolled-back (or killed, using Split terminology in reference to a kill switch) within 30 days of being created. This speaks to the importance…

At Split we believe in the power of metrics, and are always striving to improve the ways we help our users make more data-driven product decisions. In this previous post we talked about the importance of understanding the impact of a new feature release via key and guardrail metrics. With…

Find faulty features before your customers do. One of the most common reasons that our customers move  towards feature flags is risk mitigation: the need to make sure releases don’t cause errors for users. Given how frequently organizations are now deploying features, the ability to limit the blast radius of…

Anomaly detection in application monitoring systems (APM) is the gold standard. The idea is that if your APM can tell you when something is wrong, you can multiply the effectiveness of your site reliability team. Unnecessary alerts are never thrown and humans are not stuck watching dashboards.