No, because it has a theoretical limit, same as queues, back pressure, etc.
One cannot simply scale up indefinitely because it is not profitable.
No, because it has a theoretical limit, same as queues, back pressure, etc.
One cannot simply scale up indefinitely because it is not profitable.
You can't say what architecture is or isn't profitable in general, business is more complicated than that. But besides the realities of commerce, you can easily architect a system such that the autoscaling cost is a fraction of opex.
Nobody is making that product because nobody has money for it...(or the demand to supply that money).
You can auto-scale without AWS, actually, its called measuring server load and auto-ordering new machines when your load increases (and keeping machines turned off on standby for spikes).
Or you can go hybrid, and load-shed to a cloud...which would be the smart thing to do.
This isn't really true, and it's especially not true when specialized hardware comes into play. If you have a "web-scale" GPU workload, it's not unlikely that you'll hit resource availability constraints from time to time. The question isn't whether cloud capacity is larger than your demand for a particular resource, it's whether cloud capacity is larger than the aggregate peak demand for that resource. Cloud providers aren't magic. They engage in capacity planning, sometimes underestimate, and are sometimes unable to actually procure as much hardware as they want to.
While this may be true, autoscaling indefinitely is still not profitable.
> You can't say what architecture is or isn't profitable in general, business is more complicated than that. But besides the realities of commerce, you can easily architect a system such that the autoscaling cost is a fraction of opex.
Customer acquisition and retention cost more money than it should.
I cannot count how many times I got an email from the CTO asking to lower our cloud costs, while product and marketing refuse to raise prices, making the whole endeavor borderline unprofitable. You may then argue that the product suffers from either bad architecture, or bad pricing, or both, but the situation is far from uncommon.