It’s a fact of life within the SaaS world that some features will perform better or worse than others in terms of costs versus revenue. If it were possible to develop every single new release in a way that it would flawlessly maintain desired profit margins, everyone would be doing it. What separates the major players from companies that struggle year after year is how they monitor and respond to changing circumstances as they arise, and whether they learn from past mistakes.

Whether or not you take the oft-quoted statistic that 30% of companies’ cloud spend as gospel, one thing is for sure: Companies have been spending recklessly in the cloud ever since its inception. For (fairly) good reason — companies wanted to perfect their products and snatch up market share before an even more reckless spender did. But the chickens of overindulgence are finally coming home to roost.

In the early 2000s, Amazon faced an existential threat: Speed up their pace of software engineering, or risk losing eminence in the burgeoning e-commerce landscape.

In SaaS companies, engineers are the biggest influencers to cloud costs. They choose the infrastructure, build the products, and produce the code. Unfortunately, having this power means engineering managers are often asked to predict cloud spend months or even years into the future. An executive or a head of finance might approach the engineering head and ask how much the company will spend on cloud costs next year, thinking he or she should naturally have the answer.

It’s cloud earnings week this week for AWS, GCP, and Azure, and I have already heard the pundits warming up the hot takes. Some are even asking if this could be the end of the cloud. My advice to you: Don’t be that person unless you enjoy being horribly wrong. No, I'm not saying that when AWS, Azure, and GCP report their growth that it's going to be anything different than what we expect.

The first person to coin the term “Artificial Intelligence” predicted that someday people would buy software as a utility. The year was 1961 and that person was Professor John McCarthy, a computer scientist at Stanford University. After Salesforce began selling software programs this way in the late-1990s, the good professor witnessed his prophecy come true for over 12 years before his passing in 2011. Yet this is only one aspect of computing in the cloud as we know it today.

If you have trouble understanding Microsoft Azure Storage pricing, you’re not alone. Azure Storage options can feel like a multi-layered maze of storage account types, tiers, pricing pages, specs — and then some. Yet, understanding your cloud cost drivers begins with looking at where your money goes. Only then can you tell if you are getting value for your money.

As we were planning “Cloud Atlas,” our primary goal was to talk with someone who was “in the room” during the genesis of the cloud. Allan Vermeulen, who worked for Amazon from 1999-2021, and who proposed Amazon Simple Storage Service (S3), became that source. Allan is a born engineer. He has always enjoyed building things — whether “out of bits and software or boards and lumber,” Allan takes pleasure in creating useful things.

YouTube. Netflix. Uber. Spotify. TikTok. You name it. You sign up and get your own account. Once you set it up however you want, you can access it from any internet-enabled device, including smartphones and smartwatches. In case your device breaks, is lost, or you switch to a new one, you can still access the account, as well as the settings and information it contained, from another device without having to recreate everything from scratch.

It’s almost impossible to create an optimized cloud system out of the gate and keep it running at a perfect balance over the long term. There’s almost always something that could benefit from some tweaks and adjustments. Cloud costs have a way of creeping up slowly while you’re not paying attention. And if you’re not careful, they can spiral out of control before you realize anything is happening.