How virtual servers make the cloud more elastic

The secondary decision for customers looking to deploy virtualisation for aggregation is to determine the application requirements for optimal performance. Does the application perform better with a large number of processing cores? How many? Do application file sizes exceed in-the-box maximums? Application parameters are pretty critical for systems like visualisation. While additional processing cores are beneficial, most of these systems are restricted by available RAM. It's not uncommon to see multiterabyte files rendered in real time. It's critical to get system sizing right for the application -- shape the system to the workload rather than the workload to the system.

InfoWorld: And what are the best practices that should be considered?

ScaleMP: An organisation should identify their target applications before deployment and configure their hardware accordingly. By clearly identifying the target workloads, systems can be properly optimised to suit the particular needs of the application. By using virtualisation technology, customers have the flexibility to create cost effective "unbalanced" systems: many processing cores with a small amount of RAM or few processors with a very large amount of RAM. These kinds of systems may be higher performing and, more importantly, far more cost-effective than a balanced system for specific workloads.

InfoWorld: Can virtualisation for aggregation and virtualisation for consolidation be used together? And if so, what is the result?

ScaleMP: These two distinct virtualisation technologies -- one for partitioning and one for aggregation -- seem to address very different use cases: one for multiple parallel workloads and one for high-performance computing, or HPC workloads.

However, these two distinct uses of virtualisation are not mutually exclusive and can be used in tandem to enable a very powerful set of server resource capabilities -- capabilities that empower end-users to shape compute resources to fit their workloads on the fly.

As already mentioned, virtualisation for partitioning and aggregation already reside in the same infrastructure when it comes to cloud deployments. As customers demand different workload services, IT administrators can provision whatever system resources are necessary, within a single system or across a set of systems, to provide the optimal performance and SLAs for their end-user.

InfoWorld: What could this lead to? Is there a future where there can be a virtual machine running on top of a virtual machine?

ScaleMP: Yes. There are two obvious use cases, but as the technology matures there will certainly be more  The first use case places many small VMs on top of a large virtual machine, which is essentially a large SMP created using a hypervisor to aggregate multiple nodes into a large server and then splitting that system into multiple VMs using a hypervisor for partitioning. Provisioning smaller VMs from this larger pool provides a better platform for load balancing, dynamic system provisioning, and hardware migration. Ultimately, IT can also dynamically add and remove resources to the pool. In VMware's world, this is called vMotion. There is no equivalent technology to provide this functionality for competitive hypervisors. Running partitioning VMs on top of a large SMP would provide this functionality.

The second use case creates one large VM out of many small VMs -- partitioning many servers into multiple virtual machines and then aggregating some of those VMs into a larger virtual SMP system. This circumstance may develop when an IT manager has deployed multiple virtual servers taking up a certain amount of CPU power, but is also setting aside CPU capacity in case the need arises. By running a hypervisor for aggregation, an IT administrator can collect and aggregate all this available yet unused computing resource across the data centre to create a new larger or customised system that can be utilised for another workload.

Many organisations have begun to deploy their on-premise resources in a cloud-like fashion. And to realise the full benefits of their private cloud, they want to have the flexibility of deploying any kind of workload on the fly. With server virtualisation for consolidation, IT could partition their servers to run more workloads. But now, if IT has a workload that requires more than the CPU power or memory found in any given box, it can aggregate resources and provision a virtual SMP. And as Fultheim talks about in the two VMs on top of VMs use case, you can begin to see how server virtualisation for aggregation can make the cloud much more elastic.