Every "AWS vs Azure vs GCP" article is a feature table, and every feature table is useless, because all three can do essentially everything you need. Compute, storage, databases, networking, managed Kubernetes, serverless, ML. If your decision comes down to which one has a particular service, you're comparing at the wrong altitude, because they'll all have caught up within a release or two anyway.
So ignore the tables. Here's what actually decides it.
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What does your team already know
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This is the most underrated factor and usually the most important. The best cloud for you is frequently the one your people can already operate. A team fluent in AWS will ship faster and break less on AWS than on a "technically better" platform they have to learn from scratch. The learning curve is a real, expensive cost that feature comparisons pretend doesn't exist. Don't discount it to chase a marginal service advantage.
Where's your gravity already
Look at what you're already tied to. If you're a heavy Microsoft shop, Office, Active Directory, the whole enterprise stack, Azure's integration with all of that is a genuine, day-to-day advantage, not marketing. Identity alone can justify it. If your world is data and ML and you love the developer experience, GCP has a real pull, its data tooling and the fact that Kubernetes came out of Google show. And if you just want the broadest, most mature everything with the biggest ecosystem and the most people who've hit your exact problem before you, AWS is the safe default for a reason, it's the largest and it shows in the depth.
None of that comes from a feature checkbox. It comes from where your existing gravity already sits.
The honest one-liners
Stripped of the marketing, here's how I'd describe each to a friend.
AWS is the biggest and most complete. Most services, most maturity, most third-party support, most Stack Overflow answers when you're stuck. The tradeoff is that it's sprawling and the console is a lot, and the sheer surface area can be overwhelming.
Azure is the enterprise and Microsoft-integration play. If your company already lives in Microsoft's world, it slots in cleanly and the identity story is hard to beat. If you don't, some of that advantage evaporates.
GCP is the data, ML, and developer-experience one. Strong Kubernetes and data tooling, generally cleaner to work with, but a smaller ecosystem and fewer services at the edges, so you occasionally reach for something and find it isn't there yet.
The lock-in reality nobody likes
Here's the thing the "just stay multi-cloud to avoid lock-in" crowd undersells. The moment you use a cloud's managed services properly, and you should, that's most of the value, you're somewhat locked in. Rewriting off a provider's managed database and queue and auth is real work. That's not a reason to avoid managed services, using raw VMs everywhere to stay portable usually costs you more than lock-in ever would. It's a reason to go in clear-eyed. Pick a primary, commit to it, and get good at it.
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The multi-cloud trap
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Which leads to the trap. "We'll go multi-cloud" sounds prudent and is usually a mistake for teams that aren't forced into it. Running well on one cloud is already hard. Running well on two or three means multiplying your operational complexity, your expertise requirements, and your ways to get it wrong, in exchange for a portability you'll probably never exercise. Real multi-cloud exists, but it's driven by specific requirements (regulation, acquisitions, a particular workload that genuinely runs better elsewhere), not by a vague wish to hedge. Don't take on that cost speculatively.
How to actually decide
Skip the feature table. Ask what your team already knows, where your existing gravity sits, and which provider's strengths match the workloads you actually run. Then pick one, commit, and get deep. A team that's excellent on one cloud beats a team that's mediocre across three, every time.
The best cloud isn't the one that wins the comparison. It's the one your team can run in their sleep.
