Data Bores
Sampling is a method to reduce the volume of data processed and stored by observability tools. There’s a variety of methods and algorithms that can be employed to do this, and most observability practices will wind up using a blend of them, but this blog isn’t necessarily about how to implement any individual technique. No, what I’m interested in discussing is the why of sampling, the outcomes that we’re looking for when we implement it, and some of the novel work that I’m seeing around the subject.