The cloud is part of the natural evolution of the internet. Why run software locally when you can use a cloud app that’s automatically upgraded and patched, and that you can access from more than one workstation or device? Cloud services use hypervisors that allow one physical server to act as many, with each portion of a physical server being “rented” as a virtual machine.
Virtualization has much to offer: it allows users to scale capabilities up or down as needs dictate, it reduces the need for on-premises hardware and software management, and buying into a cloud solution for a business process is often far less expensive than implementing an on-site solution. Virtualization is terrific for highly dynamic workloads that aren’t overly dependent on performance. But virtualization has its drawbacks. And you might be surprised to learn that virtualization isn’t necessary to a cloud solution. Continue Reading
Companies cope with exponentially more data than they had just a few years ago. The sheer number of devices that create and transmit data has proliferated worldwide, and the volume of data produced has exploded. The world needs new, more powerful tools to make sense of all that data. IBM says that in 2012, 2.5 exabytes (2.5 billion GB) of data were generated every day, and it hasn’t exactly slowed down in the two years since. The amount of data being generated can only continue to grow.
Organizations that use big data quickly learn that a speed advantage that may be nice, but not noticeable in running everyday applications is critical when it comes to crunching big data. One way they can gain that critical speed advantage is with bare metal computing.