How Honeycomb Uses Honeycomb, Part 5: Feature Flags

In a detailed exploration of their engineering practices, Honeycomb discusses the significance of distinguishing between correlation and causation, particularly in the context of software operations and feature deployment. The company highlights a case where feature flags were pivotal in identifying misleading correlations during the rollout of a storage format change. Initially, Honeycomb's deployment of a new "varstring" feature seemed to correlate with slower write speeds, sparking concerns that were later mitigated by understanding the role of a hidden factor – the volume of data writes. This scenario exemplifies Simpson's Paradox, where the apparent slowdowns were not due to the varstring feature itself but rather the shift in dataset composition, emphasizing the importance of critical analysis of data and not relying solely on surface-level metrics. Honeycomb's approach showcases the value of using feature flags and observability tools to gain precise insights into system performance and maintain confidence in progressive delivery strategies.