Can a data centre-run application impact its behaviour to continually optimise the underlying infrastructure configuration and drive greater network performance every time?
It turns out that machine learning capabilities can enable applications to run faster and smarter and even reconfigure infrastructure to enhance efficiency and delivery – all by using reinforcement learning.
VMware’s Project Magna – part of the innovations presented at VMworld 2018 – could learn and understand application behaviour to the point that it could model, test and then reconfigure the network to a more optimal network frame size to improve performance.
The company’s Self-driving Data Centre (SDDC) is, in fact, a continually self-optimising data centre infrastructure. It is designed to configure the network processes to fit the apps and services running on its platform in the best way possible – thanks to machine learning – just like a self-driving car does, adjusting to the road.
It means configuring and managing network infrastructure becomes easier for organisations and IT teams. Also, machine learning, intelligence and analytics enhancements can extend to all components of the SDDC, including vSAN storage and the hypervisor configuration.
These can enable organisations to accelerate innovation and foster more powerful data-driven decisions to improve business performance while focusing on increasing current market and consumer demands.
The network data centre of the future will feature intelligent applications on a self-configurable infrastructure that easily adapts to meet its app and resource requirements, including storage, security access, and performance speed.
While the smart network data centre is pivotal in optimising business processes and the underlying infrastructure, management can finally adopt a more strategic role and focus on more important IT and critical business requirements.
Find out more about the latest innovations at VMworld 2018.
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