The tricky science of Internet measurement

This post introduces the scientific practice of Internet measurement as a critical component of Cloudflare's data infrastructure and analytics. It highlights the inherent opacity of the Internet and the unique challenges it presents for measurement. The post details key measurement concepts like active vs. passive and direct vs. indirect measurement, and outlines the measurement lifecycle (data curation, modeling, validation). It uses an internal example of analyzing HTTP traffic spikes in Ukraine to illustrate the importance of context and avoiding erroneous conclusions, emphasizing the need for rigor, repeatability, and reproduction in measurement.