Virtualization Technology News and Information
ScaleMP: 2011 - The convergence of clouds and virtual machines

What do Virtualization and Cloud executives think about 2011?  Find out in this series exclusive.

Contributed Article By Shai Fultheim, Founder and CEO, ScaleMP

2011 - The Convergence of Clouds and Virtual Machines

The convergence of clouds and virtual machines (VMs) will become an increasingly prevalent conversation in 2011 and we will see the concept of server aggregation marry cloud computing quite nicely. VMs running on partitioned servers are currently used in cloud and static environments. However, another approach to server virtualization has begun to emerge, benefiting a variety of industries, from financial analytics and data warehousing to bioinformatics, numerical simulation, structural analysis and other large-memory workloads.

Traditionally, server virtualization partitions a physical system into multiple virtual systems, enabling multiple workloads to share the same hardware.  It allows for enhanced server utilization and much higher ROI on the hardware. This type of server virtualization works great for independent workloads that have limited CPU and memory requirements - ones that in aggregate do not exceed what the hardware has to offer. It is not effective, however, for applications that need more resources (CPU and memory) than available from the hardware.  Such applications require proprietary, large-scale systems.  These specialized and expensive shared-memory systems are known as symmetric multi-processing (SMP) systems.

In 2011 we will see the need for SMPs grow beyond the usual HPC domain, and the aggregation of systems become more pervasive. Virtualization for aggregation, or server aggregation, applies virtualization techniques similar to those used by traditional server virtualization, only reverses them, aggregating multiple x86 servers with their CPU, memory and I/O into one virtual server. It's a sum that's greater than its parts: delivering a large scale-up system solution for large workloads - those that require more processing power (like numerical simulations) or memory (like genomics) for better performance - while leveraging commodity components' price and performance advantages. 

Aggregation permits IT to shape the system to fit the workload, rather than shaping the workload to the limitations of a given system. With this new type of virtualization, IT will be able to aggregate resources within a cloud environment on demand for a given workload and manage them from a single end-point, simplifying administration and reducing expenses. With an on-demand model, smaller organizations can pay as they grow, avoiding the prohibitive investments required for proprietary systems.

In 2011, with both traditional server virtualization and virtualization for aggregation VMs available, IT can run VMs on top of VMs to enable a very powerful set of server resource capabilities. The first use case places many small VMs on top of a large VM, which can provide a better platform for load balancing, dynamic system provisioning and hardware migration. Ultimately, IT can also dynamically add and remove resources to the pool.

The second use case creates one large VM out of many small VMs, which can enable an IT administrator to collect and aggregate all available yet unused computing resources across the data center to create a new larger or customized system that can be utilized for another workload. Used in tandem, the two types of server virtualization deliver greater elasticity and flexibility in the data center and private cloud, simplifying operations and reducing CAPEX and OPEX. 

About the Author

As founder and CEO of ScaleMP, Shai designed and architected the core technology behind ScaleMP and is responsible for the company's strategy and direction. Shai has more than 15 years of experience in technology and business roles in IT and venture-backed firms. Before founding ScaleMP Shai was CTO of BRM Capital, a first-tier Israeli venture-capital fund. Shai defined the fund's technology roadmap, which formed the foundation of BRM's investment strategy.

Prior to BRM, Shai was co-founder, CTO and VP R&D at several technology startups. He has also served in the Israeli Defense Force's prestigious central intelligence unit, where he led a large IT organization of hundreds of engineers and programmers. Shai managed a broad range of complex IT projects in the areas of security, systems and network infrastructure and knowledge management, gaining significant experience in the domain of scalable computing and large-scale IT infrastructure.

Shai has been an active member of several open source initiatives such as Apache, Jakarta Tomcat, Amanda and the Linux kernel.

Shai holds a B.Tech and BASc from the Jerusalem College of Technology.

Published Thursday, December 09, 2010 5:00 AM by David Marshall
2011 Prediction: ScaleMP « mindsharepr - (Author's Link) - February 15, 2011 11:47 AM
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