So, if the cost cap is defined as $n per day, once you deplete it you'll be down for the rest of the day (or if you take some manual action to increase the cap, if the cloud provider supports it).
This problem is a function of the granularity. Imagine a system that let you say:
"I want to spend max $n per second with a extra burst of $m per day/week"
You adjust your "$n" to match the throughput you'd have if you had a fixed size "pay what you provision" system and reserve $m for lucky events as landing on HN.
The amount of planning you have to do is similar to the traditional resource allocation, but with the benefit of paying less than provisioned if you're not getting all that traffic.
For more capacity based services, sure, but it's more likely to be down than just slow. When systems are run at their limit they rarely operate the way they did with a little less traffic.
When you're an individual, the potential for a $10k bill is much scarier than your hobby project going down.
When you're a small org/startup, the potential for a $75k bill is probably still scarier than your site going down.
It's endless bill monitoring and budget approval.
I'll stick to a flat rate DO droplet.