Every structural workaround in these deals are filling a gap where a standardized instrument would sit in a mature market. These may work at this stage. But it stops working at scale, under stress and if/when the relationships get stressed.
What changes this is an independent compute rental reference rate, a standardized depreciation methodology by generation, and residual value instruments with real market depth. Early infrastructure exists but it's oriented toward derivatives settlement, not credit document reference. The credit-specific analytical layer is still missing.
Your closing question is the right one. The window to build that infrastructure is probably shorter than it looks.
Does this type of market exist on more humdrum compute like standard x86 processor-hours or cloud RAM reservations?
In my work I see customers that implement chargeback, internal-dollar accounting that managers track, minimize and are bonused on. They use “gigabyte hours” - an app reserving a gigabyte for an hour. Similar to AWS ECS, but since cpu is shared and can be very over provisioned for business apps, memory reservation is a better proxy for app size.
Great question, and the short answer is: no. There's no liquid external derivatives or residual value market for conventional cloud compute, despite 20+ years of cloud pricing history. AWS reserved vs on-demand pricing creates something like a crude term structure, but it's not tradeable.
Your point about gigabyte-hours chargebacks is a great illustration of the gap. Enterprises built internal compute pricing mechanisms because no external market exists.
The reason it matters less for x86 is the depreciation curve. Commodity servers don't become obsolete in 18 months because Intel shipped a 3x better chip. Lenders can finance that hardware convenionally. GPUs obsolesce more quickly, which is why GPU-collateralized lending requires bespoke backstop structures.
Finally, if cloud compute never developed these markets after two decades, that tells you something about the odds of a GPU derivatives market arriving in time to close the financing gap I describe in the post.
Agreed. This was a credit substitution.
Every structural workaround in these deals are filling a gap where a standardized instrument would sit in a mature market. These may work at this stage. But it stops working at scale, under stress and if/when the relationships get stressed.
What changes this is an independent compute rental reference rate, a standardized depreciation methodology by generation, and residual value instruments with real market depth. Early infrastructure exists but it's oriented toward derivatives settlement, not credit document reference. The credit-specific analytical layer is still missing.
Your closing question is the right one. The window to build that infrastructure is probably shorter than it looks.
Does this type of market exist on more humdrum compute like standard x86 processor-hours or cloud RAM reservations?
In my work I see customers that implement chargeback, internal-dollar accounting that managers track, minimize and are bonused on. They use “gigabyte hours” - an app reserving a gigabyte for an hour. Similar to AWS ECS, but since cpu is shared and can be very over provisioned for business apps, memory reservation is a better proxy for app size.
Great question, and the short answer is: no. There's no liquid external derivatives or residual value market for conventional cloud compute, despite 20+ years of cloud pricing history. AWS reserved vs on-demand pricing creates something like a crude term structure, but it's not tradeable.
Your point about gigabyte-hours chargebacks is a great illustration of the gap. Enterprises built internal compute pricing mechanisms because no external market exists.
The reason it matters less for x86 is the depreciation curve. Commodity servers don't become obsolete in 18 months because Intel shipped a 3x better chip. Lenders can finance that hardware convenionally. GPUs obsolesce more quickly, which is why GPU-collateralized lending requires bespoke backstop structures.
Finally, if cloud compute never developed these markets after two decades, that tells you something about the odds of a GPU derivatives market arriving in time to close the financing gap I describe in the post.