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Historical Context

Is it possible to attain levels of service in terms of security, reliability, and performance for cloud-based applications that rival implementations using corporate-owned infrastructure? Today it is challenging not only to achieve this goal but also to measure that success except in a very general sense. For example, consider doing a cost rollup at the end of a fiscal year. There's no capability today to establish operational metrics and service introspection. A goal for security in the cloud, therefore, is not to just match this baseline but to surpass it. In this book, we'd like to claim that is possible.

Cloud technology enables the disaggregation of compute, network, and storage resources in a data center into pools of resources, as well as the partitioning and re-aggregation of these resources according to the needs of consumers down the supply chain. These capabilities are delivered through a network, as explained earlier in the chapter. A virtualization layer may be used to smooth out the hardware heterogeneity and enable configurable software-defined data centers that can deliver a service at a quality level that is consistent with a pre-agreed SLA.

The vision for enterprise IT is to be able to run varied workloads on a software-defined data center, with ability for developers, operators, or in fact, any responsible entity to use self-service unified management tools and automation software. The software-defined data center must be abstracted from, but still make best use of, physical infrastructure capability, capacity, and level of resource consumption across multiple data centers and geographies. For this vision to be realized, it is necessary that enterprise IT have products, tools, and technologies to provision, monitor, remediate, and report on the service level of the software-defined data center and the underlying physical infrastructure.

Traditional Three-Tier Architecture

The three-tier architecture shown in Figure 1-2 is well established in data centers today for application deployment. It is highly scalable, whereby each of the tiers can be expanded independently by adding more servers to remove choke points as needed, and without resorting to a forklift upgrade.

Figure 1-2. Three-tier application architecture

While the traditional three-tier architecture did fine in the scalability department, it was not efficient in terms of cost and asset utilization, however. This was because of the reality of procuring a physical asset. If new procurement needs to go through a budgetary cycle, the planning horizon can be anywhere from six months to two years. Meanwhile, capacity needs to be sized for the expected peak demand, plus a generous allowance for demand growth over the system's planning and lifecycle, which may or may not be realized. This defensive practice leads to chronically low utilization rates, typically in the 5 to 15 percent range. Managing infrastructure in this overprovisioned manner represents a sunk investment, with a large portion of the capacity not used during most of the infrastructure's planned lifetime. The need for overprovisioning would be greatly alleviated if supply could somehow be matched with demand in terms of near-real time—perhaps on a daily or even an hourly basis.

Server consolidation was a technique adopted in data centers starting in the early

2000s, which addressed the low-utilization problem using virtualization technology to pack applications into fewer physical hosts. While server consolidation was successful at increasing utilization, it brought significant technical complexity and was a static scheme, as resource allocation was done only at planning or deployment time. That is, server consolidation technology offered limited flexibility in changing the machine allocations during operations, after an application was launched. Altering the resource mix required significant retooling and application downtime.

 
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