Current design limitations Previous design choices have resulted in not meeting the needs of the business. In particular, these design choices have resulted in complexity, waste, performance barriers, and cost models that don't work for the business. Lack of understanding and transparency of what has been done in the past will continue to create misalignment with business needs if not addressed. The critical des Current design limitations Previous design choices have resulted in not meeting the needs of the business. In particular, these design choices have resulted in complexity, waste, performance barriers, and cost models that don’t work for the business. Lack of understanding and transparency of what has been done in the past will continue to create misalignment with business needs if not addressed. The critical design limitations include: Supply-driven management: Most datacenter infrastructure teams design and manage from the bottom up. The typical approach is to standardize, partition, allocate, and implement a “vanilla” solution of compute and storage that is attached to the network based on the topology of the datacenter floor. Provisioning is then designed for peak workloads leveraging a bottom-up-designed platform that has been selected for typical reasons of vendor rationalization, price, etc. The business workload and service requirements incorporating factors of performance, price, or efficiency are not incorporated and misalignment of needs and inconsistent service delivery begin to occur. One size fits all: Most datacenter infrastructures and typical vendor strategies are built around a perceived “standardized” footprint. The problem is that this is designed typically bottom up with little or no correlation to the workflows, workloads, information, content, and connectivity requirements of the business and its competitive needs. Such disconnects result in poor performance, unnecessary costs, waste, and in agility issues for both the business and IT. Spaghetti transaction flow: Transaction flow across traditional datacenter infrastructures must deal with a design that does not consider proximity of the various devices comprising a service unit that delivers processing to users. This results in significant performance impacts (user experience of the business suffers) whereby compute, memory, I/O fabric, disk, storage, and connectivity to external feeds are provided in terms of layout, not in terms of service delivery. Performance can be impacted by 30-fold due to this approach. Moreover, this creates waste in terms of unnecessary network traffic congestion and bandwidth usage (ROE suffers). Definition of “insanity”: The continuous use of a typical datacenter layout incorporates homogenous pooling of various classes of resources. Servers by multiple classes are typically in multiple pools; storage by file or block are in different pools in their own area of the datacenter; network load-balancers, network switches, and network routers are pooled/deployed across various areas of the datacenter. This approach is not designed for business impact, business needs, optimal workload throughput, or time to provision or optimal space/power usage. The average provisioning cycle in datacenters with this type of layout are measured in weeks or months versus the minutes or days needed to provision, troubleshoot, or perform to meet the needs of the business. Yet, firms continue to employ this strategy. Technology Industry