How to Optimise Cloud Costs for a Vibe-Coded App
July 2026
When to use this: The app is live, maybe gaining users, and the cloud or hosting bill is starting to feel unpredictable — or just higher than expected — and you don't actually have a clear picture of what's driving it.
Note: This guide covers general infrastructure and hosting costs. Model and LLM API cost management for AI features specifically is covered in the existing How to Move an AI Prototype into Production piece — left out here deliberately to avoid duplication.
Why this matters
Fast-built apps carry costs nobody chose on purpose. Defaults provision more than you need, because defaults are set to make sure something definitely works, not to make sure it's cheap. Inefficient database queries don't announce themselves as a problem — they just quietly cost more at scale. None of this shows up as a bug you'd notice. It shows up as a bill that's higher than it should be, with no clear reason why.
Get visibility before you try to optimise anything
You can't fix what you can't see. Set up a basic cost breakdown so you know which service or resource is actually driving the bill, instead of guessing based on what feels expensive.
Check for defaults you never actually chose
AI-generated infrastructure configuration, and default hosting tiers generally, tend to over-provision — bigger instance sizes than needed, resources running constantly instead of scaling to zero when idle, generous default storage. These weren't decisions. They were defaults that happened to you.
Look specifically at database usage
Missing indexes and inefficient queries don't just make things slow — they cost real money at scale, because you're paying for compute or read capacity to do work that a properly designed query wouldn't need. This is often the single biggest gap between what an app costs and what it should cost.
Find resources that are running with nothing actually using them
Old staging environments, services from an earlier version of the product that got replaced but never torn down, test infrastructure left running after the test was done. These accumulate quietly and cost the same whether anyone's using them or not.
Understand what scales with usage and what's fixed
Knowing which costs grow with your user count — and roughly how fast — lets you predict what the bill looks like at ten times the current traffic, instead of being surprised by it later.
Set budget alerts, not just after-the-fact bills
You want to know the moment spend crosses a threshold, while there's still time to do something about it — not find out at the end of a billing cycle when the only option left is damage control.
Revisit this periodically, not once
Cost creep happens gradually, one feature at a time. A cost review that happens once and never again just delays the same surprise instead of preventing it.
Common mistakes
Trying to optimise before getting visibility. Guessing at what's expensive usually means fixing the wrong thing while the actual cost driver goes unnoticed.
Treating infrastructure defaults as fixed. They were choices — just not choices anyone deliberately made. Almost all of them can be changed once you notice them.
Never tearing down what's no longer used. Unused resources cost exactly as much as used ones. The only way they stop costing money is if someone actually removes them.
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