Capacity planning or capacity management is the process of determining the production needed by an organization to meet changing demands for its products and services. For marketing departments, the key to capacity management is to counterbalance the right number of users and the right performance at peak usage to ensure a great end-user experience. Rather than waiting for a dream solution to materialize, marketers need to find a system that enables them to make better decisions and support those decisions with verifiable data.
The Flexera 2020 State of the Cloud Report showed that organizations were wasting 30 percent of their cloud spend. IT capacity planning, which involves estimating the storage, computer hardware, software, and connection infrastructure resources required over some future period of time, should be able to help reduce wasted capacity. A common concern of enterprises is whether the required resources are in place to handle an increase in users or the number of interactions. Capacity management is concerned with adding CPUs, memory, and storage to a physical or virtual server. This has been the traditional and vertical way of scaling up web applications, however, IT capacity planning has been developed to forecast the requirements for this vertical scaling approach. In the context of capacity planning, design capacity is the maximum amount of work that an organization is capable of completing in a given period. In a nutshell, capacity planning aims to reduce unnecessary resources while utilizing necessary resources at full optimization.
This paper explores a capacity planning solution that can predict upcoming costs with advanced predictive analytics and forward-thinking what-if scenario modeling that can produce a healthy ROI as well as help companies go green.
Capacity planning, capacity management, real-time monitoring, AIOps, hyperautomation, application demand modeling, data tracking, cloud technology, cloud bursting, predictive resource scaling, prescriptive analytics, predictive analytics, activity-based costing.
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