At CloudZero, we believe that you should be able to see where your cloud spend goes. By doing this, you can pinpoint who, why, and what is driving your cloud costs. With this insight, you can more easily make informed decisions, such as reduce unnecessary spend or increase investment where you can earn more. In that regard, we recently covered Azure Storage pricing and Amazon S3 pricing. As a continuation of our pricing series, here's a bookmarkable guide to Google Cloud Storage pricing.

The Amazon Simple Storage Service (Amazon S3) is a cloud storage platform that provides highly scalable, low-latency, and relatively affordable cloud storage. Plus, developers can use S3 to save, archive, and retrieve data anywhere on the web at any time with a user-friendly web interface. Amazon S3 is a simple key-based object store you can use to store any type of data, structured or unstructured.

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.

Spiraling costs are causing organizations to look for ways to reduce their monthly spend – hidden charges and unexpected bills are surprises that CFOs can no longer afford. With current costs from hyperscaler cloud providers skyrocketing, many are now asking whether going cloud-native is the right move for them. There are, however, a number of tips and tricks that you can action today that will help you reduce your cloud bill at any provider.

You’ve convinced your organization that cloud native is the way forward. You’ve championed Kubernetes and sworn by Prometheus. You’ve onboarded multiple teams to your centralized observability platform. Then you open your latest bill and see a lot of commas in your invoice, and a sinking feeling sets in. Sound familiar? We’re keenly aware of the pain this can bring. As metric cardinality grows in cloud native environments, so does the cost to store and retrieve the data.

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.