Dynamic capacity optimization is the practice of using automation to make real-time adjustments to virtual and cloud resources as needed to accommodate changing workload needs. Your application performance remains high and you can optimize the use of virtual and cloud infrastructure services (IaaS).
Integrating established and new technologies in the data center – such as private and public cloud, containers, micro services, and even AWS Lambda – requires new and real-time methods of optimizing infrastructure utilization.
Capacity management has evolved as IT technology and priorities have changed. The primary drivers for capacity management today are:
Organizations are looking to capacity management to help them understand the best place to run applications – on premises or in the cloud – based on infrastructure resource availability, performance requirements, business policies, and cost.
The practice of capacity management begins with simple, practical questions: exactly what capacity are you looking to manage, and to what end? The answers to these questions will help you create the blueprint for your capacity management efforts. The following three actions will provide the direction you need to get started.
Agility has become a centerpiece for competitive differentiation. For organizations to be agile, they need to be able to plan for future infrastructure resources as well as optimize the use of the ones they currently own.
“The rising need for an agile infrastructure, including cloud solutions, requires a mix of new and traditional infrastructure management techniques.” – Gartner, "12 Key Tasks to Govern the IT Infrastructure Capacity and Performance Management Process," February 2016
SLA compliance
payback
performance alerts
Capacity planning, capacity management, and dynamic capacity optimization are all required to balance the investment in infrastructure with the quality of service required for business growth and ongoing success.
