How Google Does It: Fleet-wide, large-scale A/B experimentation
When most people think of A/B experimentation, they think of button colors, landing page layouts, or checkout flows. At Google, many fundamental infrastructure improvements also need the rigor of A/B experimentation. Optimizing a memory allocator or a kernel scheduler can unlock massive savings in compute resources and slash latency for millions of users. But experimenting with such critical changes is inherently risky; a buggy kernel update doesn't just result in an unhappy user, it can take do
