Why can't all virtual machines just get along?

Managers have to be cognizant of the personalities in play on their work teams. They aim for a mix of complementary characters to maximize team depth and minimize friction and conflict. When building a virtualized server environment, network architects and administrators face the same challenge teaming up applications on a single server.

“It’s almost like you’ve got a horoscope chart, where different Zodiac signs like to go together,” says Andrew Hillier, co-founder and CTO of data centre analytics company Cirba.

The Richmond Hill, Ont.-based company has been in the data centre analysis business since 1999. Now, the 55-person staff – about half of them engineers – focuses on virtualization. The company launched Version 4.4. of its Data Center Intelligence software, with increased integration with VMware’s Virtual Infrastructure. The November release of 4.5 was full Unicode, responding to international demand.

DCI brings together configuration information, business attributes and utilization data of servers, representing them as a three-dimensional cube and finding opportunities to optimize their use through virtualization or consolidation. That’s more than a question of slapping applications together on a physical server.

“They all have different affinities for each other, they all normalize differently to each other,” Hillier says. Hence, the need to know your workload personalities -- the traits processes have.

The four big factors

“The whole trick about virtualization is to efficiently utilize the various resources,” says Scott Elliott, senior systems network specialist with Christie Digital Systems Inc. and leader of the Southwest Ontario VMware User Group. There are four main categories to consider – CPU, memory and network and disk I/O.

“At a very generic level, you have to watch out for those four big boys,” Elliott says.

“If you have a footprint that’s very high in one or more of those areas, putting another application that has a similar type of footprint could cause contention if you don’t map out or provision out your hardware correctly,” Elliott says.

Hillier says there are a finite number of archetypes or personalities. Data warehousing, for example, is largely read activity throughout the day, with bursts of write activity and moderate CPU strain. An online transaction processing (OLTP) app, on the other hand, has balanced read and write, with network activity mirroring the I/O.

The upside of similarity

But there’s also a school of thought that says familiarity doesn’t breed contempt: Similar virtual machines can make more efficient use of some resources, says Burton Group analyst Chris Wolfe.

“One of the issues that comes into play is sometimes you have separation of security zones on physical systems,” Wolfe says. “Security separation may trump any type of performance load-balancing issues that you’re trying to achieve.”

There is an upside to running similar VMs. “It’s not just necessarily trying to make sure you don’t have any overlapping performance spikes when you consolidate, but the other benefit that you really get from like applications in the planning analysis is consistency of a memory footprint,” Wolfe says. “You might actually wind up being able to run more VMs on a given physical host due to a consistency either with the applications or the host operating system. There would be a high degree of redundancy in the read-only memory pages the applications would need as well as their like operating systems.”

Memory mapping does give an efficiency advantage, says Elliott. “If they’re consistently accessing a spot in memory that is the same thing … if you have two Windows applications and they’re always hitting the same DLL again and again and again, you can get some memory savings if that DLL’s just loaded once and you just have pointers to it,” he says.