September, 2009
by Annie Shum, Ph.D. - Twitter: @insightspedia
The Emergence of Cloud Computing: the Genesis and the Convergence of Catalyst Factors
With the advent of Cloud Computing, the long-standing vision of "Computing as a Utility" is beginning to emerge. Since the early days of mainframe time-sharing computing, that vision has taken a quantum leap towards reality. One of the earliest references to Cloud Computing occurred in 1961 at the MIT Centennial when Turing award winner, John McCarthy, presented his vision of computing organized as a public utility. Just as the telephone system had developed into a major industry, Professor McCarthy envisioned Computing as a Utility could one day become the basis of a new and important public industry.
In essence, the genesis of Cloud Computing goes back a long way. So despite the growing enormous intensity and velocity of all thing's connected to Cloud Computing, in retrospect, mainstream commercial Cloud Computing is not a novel concept but rather, an old vision whose time may have finally come. There is no single factor that solely contributes to the recent rise of Cloud Computing. Instead there is a myriad of diverse factors that catalyze its mushrooming growth. Besides technology, the other catalysts at work include factors spanning the social, economic, environmental and generational tectonic shifts that are now underway. This kaleidoscope of converging events, trends and shifts is fueling today's rise of Cloud Computing.
A Measured Approach To Cloud Computing - ITIL based Capacity Planning and Performance Assurance
By now the need of ITI- based Capacity Planning is well-established for enterprise datacenters. But while its need is not unique to Cloud Computing, Capacity Planning for Cloud Computing is fundamentally essential because it directly impacts budget planning. In June 2009, Gartner acknowledged the essential role of Capacity Planning for Cloud Computing with this succinct observation, "as capacity is planned, the budget is also planned". This reminder is critical because similar to the "Cloud Computing is a black box" myth, another popular misconception to debunk is the following: "Cloud Computing offers infinite resources on demand - Capacity Planning/Management is not required."
Analogous to Virtualization, enterprise IT should be prepared that with Cloud Computing, reaping the benefits of infinite computing resources usually comes with a caveat and/or cost. Put differently, although the "pay-per-use" utility model of Cloud Computing can indeed provide what may seem to appear to be an infinite supply of resource on demand, in reality the consumers must determine, obtain and pay for only their own finite demand. To wit, they get only what they pay for. As Gartner observes, consumers using elastic services will have to carefully decide how much to use based on their own budget. In principle, a cost effective service delivery model based on Cloud Computing is not about getting infinite resources but about reducing the risks of resource under-provisioning and/or the waste of resource over-provisioning. With proper Capacity Planning, Cloud Computing could empower enterprises to achieve the much coveted goal of elasticity/fluidity with "right" scaling/sizing.
In addition to budget planning, Capacity Planning will also impact Cloud service performance assurance and how service level objectives/agreements will be met. Currently, to achieve elasticity and the illusion of infinite computing resources available on demand, Cloud Computing providers will typically rely on statistical multiplexing algorithms and load balancing mechanisms that in turn will require various forms of "virtualization[1]/abstraction" to mask the physical implementations of how resources are multiplexed and shared; regardless of whether commercial server virtualization technology is actually in use. Hence, IT professionals should underscore the critical roles played by integrated virtualized service oriented management, performance assurance and analytics-based feedback loops for safeguarding the successful adoption and ultimately, the viability of Cloud Computing in Enterprise IT.
Cloud Computing is Not "One Size Fits All" - Workload Characterization is Key for Hybrid Clouds
Although Cloud Computing has the potential to transform businesses, nonetheless, irrational exuberance over the current deafening hype should be avoided. A measured approach is called for and it is essential and perhaps even critical, to obtain (and maintain) a clear understanding of workload profiles to determine the proper workload mix for a cost-effective Hybrid Cloud strategy: by identifying and continuously monitoring workloads with appropriate Cloud attributes versus those that should be run in-house. Put simply, not all workloads are created equal and certainly not all workloads are Cloud-friendly or ready. As a starting point, here is a high level, general guideline:
[1] To drive home the point one more time: Although Cloud Computing in general would use "virtualization /abstraction" techniques, Cloud Computing is not the same as and does not require commercial Virtualization offerings (such as VMware etc). However, current Virtualization tech. offerings (server or storage) can/will facilitate Cloud Computing providers to support on demand elasticity and dynamic provisioning of resources.
[2] Additional "Not Cloud Ready" attributes include the following: when the core internal enterprise architecture needs work; when the applications are legacy. (Credit for all but one of the five listed attributes : Dave Linthicum)