Hedging Your Options for the Cloud

With the second decade of the millennium now just weeks away, I thought I’d offer up some possibilities for the cloud computing market as it continues to evolve. Cloud services — whether infrastructure, platform or software — share similarities with other on-demand, pay-per-use offerings such as airlines or car rentals. But what’s past in those industries may be prologue for the cloud. Here are some key aspects of those services that could become integral to the cloud in the coming decade:

Non-uniform Pricing — Since the costs of real estate, power, cooling, carbon emissions and bandwidth may be location-dependent, shouldn’t prices of cloud services vary based on cost differences between locations? In addition, a hotel room with an ocean view is priced higher than the one across the hallway next to a parking lot, and not because the mattress costs more, but due to value-based pricing. Similarly, location can mean everything when latency is important, which is why some cloud providers are offering services near stock exchanges where microseconds might mean millions. Time-based pricing should also come into play. Shouldn’t computing cycles at 2 a.m be priced lower than ones at 2 p.m.?

Volume Discounts — Buying more resources at a given time, or the same quantity for a longer period, should entitle the customer to a lower price, since the risk of unused provider capacity is lower.

Reservation Protocols — Customers who show up at a hotel without a reservation risk sleeping in their car. Hotels that accept reservations with no or refundable deposits risk no-shows and lower utilization. Reciprocal commitment exacted via retainers, pre-payment, or non-refundable guaranteed reservations enhances provider financials and provides benefits to customers such as assured availability and discounts.

Oversubscription — Buying an airline ticket is different than flying. If not all reservations are used, providers can maximize revenue yield by overbooking, even if credits or penalties are occasionally paid. And, this is not a bad thing, since real users of limited resources are not blocked by users with unactualized intent.

Space-Available Upgrades — Airlines award empty business class seats to frequent flyers, enhancing customer loyalty. Perhaps cloud providers should consider the same, e.g., a free extra copy of a data object, space permitting?

Dynamic Pricing — Finite, perishable capacity — such as airline seats and hotel rooms — drives firms to use sophisticated yield management algorithms to maximize revenue, reducing prices to increase demand when utilization is low, and raising prices when utilization is high. Congestion pricing to discourage peak use — whether of city streets or electricity — and promotions, e.g., sales, to encourage use help smooth demand, improve utilization, and therefore optimize economics.

Capacity and Rate Transparency — Dynamic pricing requires rate transparency. No one wants to be surprised when the bill comes. “Click to view available seats” and “five seats left at this price” provide customers information that can help them plan, or accelerate, purchase decisions.

Discretionary Processing and Auctions — Much computing must be done on demand. However, in the same way that $79 fares to the Caribbean make people reconsider their weekend plans to shovel snow, companies increasingly will be able to decide how much processing to do for some workloads by placing auction bids or based on spot prices for computing — consider complex optimization problems where more computing results in better results, but with diminishing returns.

Derivatives and Hedging — Options and futures exist for equities, commodities and currencies ranging from pork bellies to pesos, so why not derivatives for network, compute and storage? Jet fuel is strategic to airlines just as IT is for many firms, and the same way airlines hedge against jet fuel price increases, an e-tailer might hedge against CPU core price increases for the holiday season. Such futures and “options for the cloud” could mitigate price risk, via hedges that protect against dynamic pricing and market vagaries.

Markets — How to trade capacity and derivatives? Why, spot markets and auctions and option markets, of course, such as BuySellBandwidth.com. Cloud service providers or enterprises may want to trade future capacity and protect against smoking hole disasters by acquiring options for capacity from other providers. Coming soon, the New York Server-Hour Exchange?

Volatility — As recent times no doubt illustrate, meltdowns and irrational exuberance are inherent to markets composed of traders with attitudes. In Ubiquity, Mark Buchanan reports on research conducted by two “econo-physicists,” who modeled a simple market in one stock, with three types of traders — optimists, pessimists, and value investors — who could shift their orientation. Even in such a simple model, bull, bear, and chaotically volatile market behavior emerged.

Aggregation, Cooperation, Brokerage, Arbitrage, VARs, and Other Intermediaries — New market ecosystem roles will evolve. Aggregators may buy capacity at volume discounts and resell smaller quantities (“break bulk”) to make money. Cooperatives such as the Enterprise Cloud Buyers Council may wield buying power to save money. Like travel web sites, brokers will arise to resell, package, compare, crowdsource reviews, and recommend providers, and VARS will add value to wholesale cloud computing capacity. Arbitrageurs and “high-frequency” traders may arise to make money on instantaneous market imbalances.

Virtual Cloud Operators — Airlines sell codeshare partners’ capacity, increasing the apparent breadth of their portfolio and boosting revenue. One model has SaaS (software as a service) providers white-labeling other SaaS providers’ offerings. Or SaaS might run on another provider’s infrastructure as a service (IaaS) — virtual IaaS operators might physically reside on other operators’ infrastructure.

Co-generation — If major companies can generate power for the grid from their generators during lulls in internal demand, they may also be able to sell their unused compute capacity, as GridEcon proposes.

Simplified Pricing — There is a natural cycle at work in market ecosystems, where fixed pricing drives the introduction of pay-per-use; pay-per-use becomes increasingly complex; and this may drive a return to simplified plans. In telephony, pricing started out as fixed (per-line), then became metered pay-per-use (per minute), then became simplified via tiered usage plans such as AT&T Digital One Rate. “Every day low pricing” and “all-inclusive” packages can replace dynamic pricing and pay-per-use. “Loss aversion” plays a role: Sometimes you’d rather pay slightly more for a fixed price plan than take the chance of paying a lot more should usage spike on a pay-per-use plan. Of course, when the spike is revenue-generating or otherwise beneficial, Cloudonomics tells us that total cost can be minimized by judiciously leveraging pay-per-use pricing.

Additional possibilities exist, for example, program trading, risk management, trusted third-party evaluation and reporting, and rollover minutes, and causal chains are bound to happen — perishable capacity leads to dynamic pricing which begets long-term hedges.

Joe Weinman
is Strategy and Business Development VP for AT&T Business Solutions.


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