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by femto113
1295 days ago
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Cloud providers aren't guessing at demand to plan capacity, they're literally building new data centers and then wheeling new racks into them as fast as they physically can (short-term decisions are more likely made at the other end, e.g. when to retire old systems, not add new ones). AWS was born out of the fact that Amazon's own compute needs are inherently variable so to meet peak demand they had to "over-provision" compared to average demand--this in turn meant they had a lot of excess compute power most of the time. At the point when Amazon still was a dominant consumer of AWS, spot instances were actually a deliberate convenience to Amazon, since it meant AWS could monetize resources while still ensuring Amazon could claim them instantly when needed (later they added a two minute warning, but early on they could literally disappear at any moment, and regularly did). |
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They are constantly guessing at cloud capacity. Short, medium, and long term models with forecasting galore, all under constant recalculation based on customer actions (they literally take live feeds of creation/termination actions), and yes they also take in to account hardware failure and repair rates. Consolidating racks of equipment is a pain in the neck and tends to be avoided, unless you can safely live migrate away all instances.
They all build up various models, using all sorts of forecasting techniques. The longer range forecasts are involved in data center provisioning, along with other business analysis, market research, legal analysis etc. that helps define where future regions should be.
It's still a guess. They can't tell what the actual demand will be, and they can't tell what is going to happen with the supply chain (supply chain issues are the biggest nightmare for capacity planning teams). Sometimes they get it wrong.
The capacity management teams spend a lot of time and expertise to keep the company just sufficiently ahead of demand. It's a crucial part of keeping costs under control.