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The marginal cost of each of those is very low, especially stuff like S3 and Lambda. You used to have to rent enough dedicated servers or VMs to handle your tra

The marginal cost of each of those is very low, especially stuff like S3 and Lambda. You used to have to rent enough dedicated servers or VMs to handle your traffic and before that buy racks of storage and servers to run software. Now it's literally paid by the minute/gigabyte as you use it instead of having to invest in it upfront. Just because companies are bad at cost management and bloat their stacks in clouds doesn't mean that the marginal cost is high, just that their absolute budget is. The marginal cost of compute and the marginal cost of each new customer using it are different issues.

jcgrillo 2y ago
Yes, but the marginal cost isn't actually that low that you can use these things willy-nilly without actually calculating and thinking about it. So the idea that "dev time is expensive, computers are cheap" just isn't true. So a system which automatically generates a bunch of inefficient, poorly wrought crap quickly for low effort will make you pay for it in different ways. So it's not obviously advantageous, and it seems (to me at least) the disadvantages are greater.
- throwup238 2y ago
  I never said that you don't have to think about it nor did I say that "dev time is expensive, computers are cheap." What I said was that the "while [software is] expensive to develop, marginal cost to run it is very low." Those are completely different statements, although I could have been more specific. Low marginal cost is built into the cloud products like Lambda, S3, and autoscaling VMs. That's why they're popular, even though the servers running those services are much more expensive. Edit: I think I see the impedance mismatch here. Yes the marginal cost of spinning up another RDB instance or big VM is relatively high, but unless you’re spinning up one for each customer, the marginal cost per user is much lower. Sometimes the marginal cost is recalculated like when scaling up to more big DB instances, but the cost per unit is very low compared to say a factory that has to buy machines up front and train machinists when they need to grow. If a software company has enough servers already, the marginal cost of a new customer is often just the extra electricity used by existing compute
  - jcgrillo 2y ago
    What I was trying to get at is that although the absolute cost of e.g. S3 API calls seems low (you get 1M of them for $5), the marginal cost (cost increase from adding one customer) can actually be very large if you make a lot of API calls. So much so that it actually causes serious problems. Cloud pricing can be very sensitive to usage, so in data intensive industries--say security monitoring, where customers may send you 1TB of logs per day--the seemingly low cost of cloud conveniences actually can be very misleading if you're not using them properly. I agree that for example, serving a web page to users where almost everything happens on the client, the marginal cost of running the software is low. But it's not always true, and it's really important to measure and track these costs otherwise you can end up in a bad way. I've seen it happen ;).

jcgrillo 2y ago

Yes, but the marginal cost isn't actually that low that you can use these things willy-nilly without actually calculating and thinking about it. So the idea that "dev time is expensive, computers are cheap" just isn't true. So a system which automatically generates a bunch of inefficient, poorly wrought crap quickly for low effort will make you pay for it in different ways. So it's not obviously advantageous, and it seems (to me at least) the disadvantages are greater.

throwup238 2y ago
I never said that you don't have to think about it nor did I say that "dev time is expensive, computers are cheap." What I said was that the "while [software is] expensive to develop, marginal cost to run it is very low." Those are completely different statements, although I could have been more specific. Low marginal cost is built into the cloud products like Lambda, S3, and autoscaling VMs. That's why they're popular, even though the servers running those services are much more expensive. Edit: I think I see the impedance mismatch here. Yes the marginal cost of spinning up another RDB instance or big VM is relatively high, but unless you’re spinning up one for each customer, the marginal cost per user is much lower. Sometimes the marginal cost is recalculated like when scaling up to more big DB instances, but the cost per unit is very low compared to say a factory that has to buy machines up front and train machinists when they need to grow. If a software company has enough servers already, the marginal cost of a new customer is often just the extra electricity used by existing compute
- jcgrillo 2y ago
  What I was trying to get at is that although the absolute cost of e.g. S3 API calls seems low (you get 1M of them for $5), the marginal cost (cost increase from adding one customer) can actually be very large if you make a lot of API calls. So much so that it actually causes serious problems. Cloud pricing can be very sensitive to usage, so in data intensive industries--say security monitoring, where customers may send you 1TB of logs per day--the seemingly low cost of cloud conveniences actually can be very misleading if you're not using them properly. I agree that for example, serving a web page to users where almost everything happens on the client, the marginal cost of running the software is low. But it's not always true, and it's really important to measure and track these costs otherwise you can end up in a bad way. I've seen it happen ;).