![Close [x]](http://dw1.s81c.com/i/c.gif){kind=small}
Introduction
Today, a database server is likely to be implemented on a virtual machine (VM), where processor, memory, disk and network components are allocated from a shared pool of available resources on a physical machine. This provides the ability to consolidate multiple workloads onto a single server. Despite potentially higher upfront costs for larger physical machines, the ability to consolidate many workloads onto a single server can mean more efficient use of system resources, which can help lead to less power consumed, less data center floor space occupied and ultimately, a lower total cost of ownership (TOC).
The nature of this paradigm, however, introduces a coordination mechanism within the physical machine that assigns, maps and manages the physical resources to the virtual hosts, or logical partitions (LPARs) as they are known on IBM Power Systems™ severs. The implementation of this mechanism — usually known as the hypervisor — can provide a robust, scalable and manageable virtualization solution that can help maximize clients' return on investment (ROI).
That hypervisor, part of the IBM PowerVM™ virtualization solution, is able to take LPAR profiles and deploy them onto IBM Power Systems in an efficient and seamless manner. It can virtualize multiple operating systems (OS), has the scalability to deploy up to a thousand VMs on a single server and integrates with a full suite of tooling to plan, deploy and manage the LPARs quickly and easily.
For example, with the IBM PowerVM solution, not only can you set the quantity of resources LPARs receive, but you can also control — from the same interface — how those resources, such as processors and memory, are shared among the other system LPARs. If you have unimportant LPARs that are frequently idling, they would be best implemented with a shared-processing LPAR profile. This means, unused processing resources are deposited back into a shared processing pool for other LPARs to consume. If you have LPARs that are mission-critical, despite having some idle time, you might want to set up a dedicated-processing profile, where processing resources are strictly coupled with that LPAR and no other.
There are volumes of literature available (see the References section below) on virtualization, from short articles to comprehensive books; targeting a variety of scenarios, from specific database and application middleware workloads to generalized host deployment strategies. This article will provide a short list of LPAR planning and deployment best practices, followed by a series of optimization steps using a sample database environment running an IBM DB2® pureScale® installation on IBM POWER7® servers, to demonstrate the advantages of such best practices.
