Most enterprises don't use "the cloud," but rather an intricate mix of hybrid, multi, public and private clouds. Their success depends on their ability to orchestrate and automate this complex environment into a single, smooth workflow.

AppDynamics’ David Wadhwani Named to Glassdoor Top CEOs List for 2019

Many data science discussions focus on model development. But as any data scientist will tell you, this is only a small—and often relatively quick—part of the data science pipeline. An important, but often overlooked, component of model stewardship is monitoring models once they’ve been released to the wild. Here we’ll aim to convince any unbelievers that monitoring deployed models is as important as any other task in the data science workflow.