The article explores effective techniques for measuring latency at scale, emphasizing the importance of choosing the right method to aggregate latency measurements when memory constraints prevent recording every individual measurement. It suggests creating a latency histogram and highlights the advantages of using a geometric sequence over an arithmetic sequence for bucketization, which offers more granular data at low latencies and is widely used by industry leaders like Google. Additionally, the text introduces the Split Feature Data Platform, which allows for safe feature deployment and experimentation through feature flags, helping teams move quickly and confidently by linking flags to contextual data and facilitating A/B testing without slowing down development.