This article walks you through the Go implementation of Bloom filters to optimize the performance of a recommender. It cover the architectural view, Bloom filter mechanics, Go integration, parameter tuning, and practical lessons learned from making it work under production constraints.

How can you focus in a sea of results from a large regression test suite? This article describes a stochastic approach that relies on some degree of redundancy in your CI regression test set. This approach does not guarantee you will catch every bug every time, but it gives you your best bet of not missing the subtle signatures of all the bugs uncovered by your CI regression test suite runs.