We worked with a business unit to predict how many people they would migrate on to their new system week 1-2 … they controlled the migration through some complicated salesforce code they had written.
We were told “half a million first week”. We reserved capacity to be ready to handle the onslaught.
Companies hate OpEx and love CapEx. That's the main driver as companies loathe hardware life cycle costs and prefer a pay as you go model. It is more expensive but it's more budget friendly as you avoid sticker shock every 3-4 years.
Do you mean that it's still the case that more resources are allocated than actually used or that the code does not need to be optimized anymore due to elastic compute?
If I remember correctly, that was the original idea of AWS, to offer their free capacity to paying customers.
Do you think that AWS in particular has this problem or Azure and GCP as well? I have mainly worked with DWHs in Snowflake, where you can adjust the compute capacity within seconds. So you pay almost exactly for the capacity you really need.
Not having to optimize queries is a good selling point for cloud-based databases, too.
It is certainly still cheaper than self-hosted on-premises infrastructure.