There are two key areas in which companies should consider the economics of cloud computing: (1) how much an organization can save if it consumes cloud computing as an outsourced utility computing service and (2) how much it might save if cloud computing principles successfully reformulate data center strategies. Cloud computing services create savings relative to in-house computing from two primary sources; flexibility in handling unusual IT demand
Justifying cloud computing: Outsourcing resources
- Meeting variable IT demand. The near-term impetus for cloud computing services comes from the variation of IT demand according to business cycles and in response to unexpected events. In-house computing resources are normally maintained at a level sufficient to ensure that the IT needs of line departments can be met. The level of resources needed to meet those needs depends on a combination of the total resource requirements, the extent these needs vary in an uncontrolled way because of short-term project demands, and the speed with which new resources can be added. Often the variability of demand forces enterprises to create an oversupply of IT resources to carry through peak load periods. These periods can be periodic (quarterly earnings cycles) or episodic, and in many cases, some of the applications could be outsourced to cloud computing services.
- Reducing in-house capacity. It's fairly easy to see whether cloud computing services can reduce the cost of sustaining capacity reserves against peak requirements; an audit of the level of utilization of critical resources over time will normally show the range of variability. That lets organizations estimate the amount of cloud services needed to provide reserve capacity and the cost of those resources. This can be compared with the cost of sustaining excess resource capacity in-house. Generally, the more variable the demand on IT, the more savings can be generated by offloading peak demand into the cloud. But it's also true that large enterprises that achieve good resource economies internally are likely to save less than smaller ones.
- Creating operational efficiencies.Operations efficiencies for cloud computing are based on the presumption of support economy of scale, meaning that a support team managing a large cloud data center or a series of data centers is more efficient than one that manages a smaller set of resources. The corollary to this is that larger enterprises are likely to achieve good enough economies of scale with private resources, particularly private cloud computing, to reduce this benefit. That means cloud computing services are most likely to be economical for smaller organizations.
- Improving data center resource use. Private cloud computing strategies are justified by improved resource utilization and economy, and by operations savings, but as we've noted, the application of the principle is different. Organizing an enterprise data center around cloud computing principles is an extension of the virtualization concept, and the approach to validating the business case is much the same.
The question is whether a data center's resource pool is used in an unequal way, so that some servers or storage networks are overused, while others are underused. Auditing resource utilization quickly identifies situations that cloud computing (and in some cases simple virtualization) can cure, and the benefit is the cost of the resources that can be retired based on a cloud computing commitment. Remember that most IT equipment depreciates, and the residual depreciation on existing assets may make the business case marginal until assets age. The best time to consider a transition to a private cloud architecture is when a data center contemplates a major IT infrastructure refresh.
- Gaining operational efficiencies. Operational efficiencies gained from transitioning to a private cloud are linked to a more systematic approach to IT infrastructure assurance. Many enterprises create support silos today, built around key applications. This process wastes management tools and human resources. With private cloud infrastructure, support processes are built around supporting performance and availability requirements set for the cloud overall, and this tends to break down application silos. It also often shifts support from a reactive or incident-management focus to a planning/proactive focus, which is nearly always more efficient and also less likely to create operational disruptions.
|Tom Nolle, is president of CIMI Corporation, a strategic consulting firm specializing in telecommunications and data communications since 1982. He is a member of the IEEE, ACM, Telemanagement Forum, and the IPsphere Forum, and is the publisher of Netwatcher, a journal in advanced telecommunications strategy issues.td>|