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The New Data Center Infrastructure Management Segment

Posted By Zen Kishimoto, Wednesday, July 06, 2011

When a new market segment starts to emerge, some analyst company tends to name it. The data center infrastructure management (DCIM coined by Gartner) segment is now emerging in the data center space.

DCIM solutions collect data from both the IT and the facility parts of a data center. I am familiar with companies like Sentilla, Modius, OSIsoft, and SynapSense. Arch Rock was spun off from Cisco and spun back in recently. Power Assure provides somewhat more sophisticated power management for data centers.

Those DCIM companies collect real-time data from actual operations and provide varying degrees of functions. Some collect data from both IT and facility equipment (like servers), aggregate it, and display the result to provide an overview of a data center’s power usage. Others receive data from somewhere else and provide more sophisticated analysis.

Romonet was founded by Zahl Limbuwala (CEO) and Liam Newcombe back in 2006, but they kept it in stealth mode until now. In conjunction with the recent DatacenterDynamics conference in San Francisco, Romonet came out of stealth mode and launched in the US. It launched in the UK late last year.

Zahl Limbuwala

Liam Newcombe

Wanting to coin a new term to accurately describe their segment, they came up with data center predictive model (DCPM). Rather than collecting real-time data, they predict data center configuration and architecture.

They showed the differences between DCIM and DCPM in the following slide.

Romonet’s product is called Prognose. Its function is summarized in the following slide.

The tool can provide "what if” scenarios for many different elements, such as PUE and power consumption. Two screenshots are shown below.

This display shows how PUE might change with different power loads and temperature.

This display shows the power usage information of different IT equipment.

The rationale for a tool like this is the complex interrelationship of elements in a data center. Changing one element may have an adverse effect on other elements. It would be nice if we could tell what the impact of a change might be before we make it. Prognose can be used for capacity planning. One of the case studies presented at the launch meeting was from Intel. A representative from Intel said that this tool could be used for choosing a data center location on the basis of temperature and humidity conditions in each geographical area in the world.

The tool is based on modeling algorithms, and its effectiveness depends solely on how good such modeling is. They surveyed many data centers of various sizes to fine-tune the model. Because I have not used this tool for a real data center, I withhold my judgment on it, but a tool like this is pretty handy when a data center goes through frequent changes, as they typically do.

Another area where I withhold my opinion is their claim of "only one DCPM in the world.” This is because I found Nlyte Software at the show the next day. Nlyte also provides predictive modeling. They also provide management and real-time monitoring of data center assets.

Claiming differentiation by just monitoring, aggregating, and displaying data from multiple sources at a data center is difficult. The differentiation is in the analytics and prediction. As Romonet said, the DCIM segment is crowded, and some consolidation is inevitable. It is not "if” but "when.”

Tags:  Datacenter  datacenter capacity  DCIM  DCPM  Prediction  Romonet 

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