The industry is
coalescing around standard design and run time platforms for next generation software
applications. These cloud-based platforms
promise to deliver true workload portability across hypervisor options and
private/public cloud compute capacity.
Once workload portability becomes a reality, variable workload pricing
is the logical next step and markets for transacting workload capacity will
follow.
It stands to reason that e-markets for workload pricing will
emerge no different than markets today for securities, foreign exchange, and
power (energy). Enterprises will seek
and are procuring fixed and variable capacity to run workloads, acquiring that
capacity from internal IT or the public domain.
It also stands to reason if a cash/spot market has been established, a
futures (and options) market will also evolve, providing enterprises with the
ability to buy (or acquire the option to transact) technology capacity at
future points in time. These two markets
will make enterprise technology far more economically efficient than it is
today.
Current generation outsourcers like HP, CSC, and Accenture
will shift their models from building all of their capacity (and increasing
that capacity in step-wise fashion) to owning a fixed portion (for certain
workload types) of their capacity and acquiring variable (or all) capacity in
the spot and futures markets. Today’s
service providers (e.g., Verizon, ATT, and Rackspace) will compete (via
commodity hardware) with or resell web-scale capacity (from the likes of Amazon,
Google, and Microsoft) to both outsourcers and large enterprises. The web-scale providers will become
wholesalers of compute capacity but will also sell direct.
This development will result in the integration of fixed
internal private capacity with variable external public capacity. Enterprise IT will be challenged by their
business users to optimize technology utilization by workload profile. And, as workload portability becomes a
reality, firms will need to balance the fixed/variable component. IT risk managers will adopt hedging
strategies for technology capacity acquisition.
And the logical evolution of that hedge is a futures/options market for
technology capacity.
A Short History
Legacy workload processing was built around acquiring fixed
capacities of technology (compute, storage, and network). That same legacy workload processing had
minimal pricing variability. Enterprise
IT bought/built capacity and charged it back to business to recover costs. The emergence of faster and more flexible
technology capacity provisioning, with more transparent (and variable) pricing,
has had significant appeal to the business.
Capacity providers like Amazon Web Services and SaaS providers like
Salesforce.com have emerged as attractive alternatives for variable or dynamic compute
provisioning, application delivery, and pricing.
The Emergence of the Cloud
Cloud computing has created internal and public resource
pools of technology capacity (private and public clouds). Enterprises need the ability to transact
workloads on a fixed and variable cost basis.
While workloads can be profiled, to date they are not truly fungible
(company A reporting workload is NOT identical to company B reporting workload). On the other hand, technology capacity is
fungible (fixed amount of compute capacity for a finite duration). Regulatory and legal requirements limit the
ability of enterprises today to move workloads to alternative compute capacity
venues. Security and network concerns
have also constrained production workload outsourcing.
Enterprise workloads today are designed for a specific
technology capacity and specification. Workload
portability (brokering) has been challenged by the inability to move workloads
(internally or externally) across fixed or variable technology capacity boundaries. Technology capacity is
pooling around internal (private) and public (cloud service providers) venues. Public cloud services are offered by the
likes of Amazon, IBM, Rackspace, Microsoft, VMware, and Google. Enterprises want the ability to process
workloads in the most efficient manner. Finally,
workload efficiency is influenced by a number of factors including size,
performance demands, security requirements, and network transfer rates.
The X Factor
Workload portability is an aspirational statement. Significant obstacles have existed which
challenge this aspiration. Technologies
like BOSH from the CloudFoundry project change the rules of the game. BOSH allows an operations team to describe
the entire software stack (from OS to software packages to processes) and then
permits the team to change the configuration to permit horizontal scaling. And any of these changes can be deployed to a
running system. The implications for
workload cost optimization are staggering.
This capability will theoretically permit real-time, in-flight workload
portability and migration. An enterprise
could start a process in-house and then finish it at Rackspace.
Market Reality Check
Large enterprises are moving to second and third generation
private clouds. These clouds may be
built around converged or hyper-converged infrastructure – built or bought. Capacity, confidentiality, and complexity are the factors
that will influence decisions around public or private. Firms will mature their private/public cloud
strategies and experience, and will then look to optimize. Once true workload portability is a reality,
price discovery will start as a bilateral process. And once that matures, it will move to a
multi-lateral process. Enterprises will
conduct reverse auctions to obtain time/price/size capacity. Concepts such as market continuity and
access, order flow, liquidity, trading costs, pricing dynamics, and
transparency will all emerge in the market for transacting a compute asset. The estimated timeframe for this evolution is
2-4 years. Compute capacity (server,
storage, and network) will emerge as a fungible, tradable asset.
(This was also published July 31, 2014 on Tabb Forum, QuantForum at http://tinyurl.com/k9eemgb)
