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Software-defined Composable Infrastructure for Remote Resource Management

Posted on
March 5, 2020
Written By

The ability to remotely target and deploy data center devices to suit the specific needs of high-value applications through software, as required or through automation, is a key driver to maximizing the value of AI, machine learning, and other evolving solutions driving revenue through a wide swath of vertical industries. It is also key in a work-from-home environment.

In centralized data center environments, 5G & edge computing facilities, or anywhere in between, composable infrastructure enables the remote, real-time management and automation of these common data center devices. GPU, FPGA, NVMe storage, CPU, NIC, and even Intel Optane memory technology resources are pooled and accessible through a simple pane-of-glass GUI, command line, or API. Administrators can create a bare-metal server with any hardware configuration they want, eliminating much of the need to send technicians out to manage a task on premises or in remote locations.

Liqid composable infrastructure solutions are also vendor-agnostic and fabric-agnostic, as well, and do not obligate the user to put any drivers, agents, or software modules on the compute nodes themselves. This also reduces the need to overprovision infrastructure to meet compute needs, as once static resources can be composed in near real-time and used for multiple purposes. The result is streamlined operations for employees who are freed from many tasks previously requiring manual intervention at remote locations.

Find out how to automate your infrastructure for dynamic, remote resource management. Download our new white paper, “Why Should Enterprises Move to a True Composable Infrastructure Solution,” today and begin mapping out your data center’s transformation free from vendor lock that can be detrimental to innovation.

Learn more about Liqid’s technology and contact us to discuss your specific data center needs with a representative.

Written by
Posted on
March 5, 2020
Remote Resource Management

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