For experimenters, stopping rules can make or break the validity of statistical tests. They seem simple, however, we’ve all come across misconceptions about statistics that can alter the interpretation of the results. Here, we’ll dig deeper into the rules we follow within null hypothesis significance testing (NHST), and why.
When we were considering how to push 700k events per minute from Kafka into our data warehouse, Vertica, we learned these lessons about how to choose the best framework for high throughput.
At Credit Karma, my team maintains a service powered by a multi node Akka cluster. Akka is a framework for building distributed, concurrent, and message-driven systems in Scala. It helps us easily scale our service, and gives us some resilience when problems inevitably happen in production. In this post, I’ll cover two problems - auto down and quarantine - and share our lessons learned.