If your business is growing, your AWS bill is probably growing with it. Yet, in conference rooms all over the world (or Zoom calls, these days), CFOs are asking “we’re spending how much?!” — while engineering leaders try to explain that the platform is twice as fast and they’ve added some machine learning that is going to absolutely change the game.
On a day-to-day basis, both engineering and product management in software companies involves constant trade-offs. Everyone has a long backlog of tasks and needs to make decisions about what to prioritize on a daily, weekly, and monthly basis. Figuring out what to tackle first, what to put off for later, and what to say no to is critical both to managing daily workloads as well as to creating product roadmaps that reflect what customers want.
This month, I made the decision to join CloudZero as their new chief revenue officer — a choice I’m incredibly excited about. In the past week, a number of colleagues have asked me to share why I joined the company. After answering the question a few times, I decided to take a minute to collect my thoughts and explain why this incredible company is the next step in my career.
It’s safe to say that cost per tenant (also known as cost per customer) on AWS has been a challenging metric to obtain. Until now, your best bet has usually been to either make a best guess or build some sort of homegrown system. As of November 4, 2020, when you google “cost per tenant,” you get a few things at the top of the page. The first is a couple of blogs by AWS, where they describe an extraordinarily complex system, which you can build yourself.
Do you know how much it costs to operate your software per customer, at each pricing tier? The past six months have been highly unusual to say the least. For some companies, the disruption and shift to work from home meant 100x in usage almost overnight; for others usage completely collapsed in the same time period. These sharp swings in utilization have been disruptive to cloud unit economics. Both scenarios are risky and require extreme elasticity from the technical infrastructure.
