Does the title sound familiar? Probably yes, because ... 👇
... it was the title of a 2014 Google paper, except the paper was about Machine Learning.
But the title also easily applies to today's cloud-native infrastructure.
👀 Today, developers face pressure to ship new products and services.
As a result, they run lots of experiments. They adopt new cloud services that drive forward innovation, combined with accelerated deployment through infrastructure-as-code and CI/CD pipelines.
😱 The flip side of that innovation is that companies now have an inventory problem
👉 It's much easier to deploy new resources than figuring out which ones are running and why. The result is a growing number of resources that run in your cloud.
It's a new type of technical debt, where you lose track of the assets running in your infrastructure and how they relate to your business.
Ward Cunningham first defined the metaphor of technical debt in 1992.
💸 Just like financial debt, inventory debt compounds.
💰With modern cloud-native infrastructure, it's remarkably easy to incur massive recurring cloud spend - without understanding what you're actually spending it on.
A Cloud Asset Inventory has a lot of the answers. It's also a forward-looking tool that allows platform teams to stay in control while giving developers liberal permissions.
In a post "What is Cloud Asset Inventory?", I summarize the challenges that come along with adoption of cloud-native infrastructure, and how a cloud asset inventory is a strategic tool to
📉 pay off you inventory debt,
🚀 increase development velocity, and
📈 grow infrastructure's contribution to profitability.
💪 ✌️ 👌
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