Modius Data Center Blog

The challenge with data center capacity management lies not in what to do, but how to do it in a dynamic and complex environment. Traditional data centers typically were housed in one giant room with a single, integrated power and cooling system to service the entire room. This meant the energy expended to cool the room was fairly constant regardless of the actual IT load. Today’s modularized data center architecture is more energy efficient. It is designed to scale with the deployment volume of IT equipment. As IT equipment and computational workloads fluctuate with business demand, so too should the power and cooling of the data center.

Modularization helps the data center’s power and cooling systems run truly proportional to the computational demand and, thus, is less wasteful. By optimizing infrastructure performance, more servers can be supported in the data center with the same power and cooling. To fully appreciate its impact on capacity gains, first consider the how the principles of modularization can be applied throughout the entire facility:

Physical Layout – Just as one manages power usage in a home by turning out the lights in unoccupied rooms, one can also manage data center power. By compartmentalizing the data center into energy zones or modules, with independent controls for power, cooling, and humidity, each module can be independently “lit up” as needed. Modularization can be achieved by erecting walls, hanging containment curtains, or by using pods, i.e., enclosed compartments of IT racks that employ a centralized environmental management system to provide cool air at intake and keep warm air at the exhaust.

IT Systems Architecture – IT infrastructure can be modularized, and should be done in conjunction with IT staff and end-user customers (business units) who own the applications deployed on servers. IT modularization involves grouping together servers, storage, and networking equipment that can be logically deployed in the same module. For example, when business computational demand is low, all corporate applications—such as the corporate intranet, internal email, external Web presence, e-commerce site, ERP applications, and more—can be deployed on the same module while the other modules in the data center remain “unlit” to save energy. As the business grows, more servers can be deployed and additional modules commissioned for IT use. For instance, all corporate intranet applications can be deployed in one module with external applications deployed in another module.

Power and Cooling Infrastructure – Right-sizing the facilities infrastructure follows the modularization of the physical layout. As the modules—zones or pods—are created
for the physical layout, the power and cooling infrastructure are deployed in corresponding units that independently service each module. Separate UPSs, PDUs and power systems, along with CRAC units, condensers, or chillers, are sized appropriately for each module. This allows the scalable expansion of the facilities infrastructure as IT equipment expands.

The principles of modularization summarized above are proven optimization strategies that can extend the life of the data center. Optimizing in near real-time delivers a higher yield from existing resources. It enables us to get more utilization out of power, cooling and space.  

If your data center infrastructure management tools fall short enabling continuous optimization, then let us show you how OpenData can help in this 20-minute Modius OpenData webcast: http://info.modius.com/data-center-monitoring-webcast-demo-by-modius

One of the key power usage metrics that I often find our customers requesting is  Available Redundant Capacity (ARC). This metric can mean different things to different people, but in simple terms, we at Modius like to define it as the amount of IT load that can be added to a data center system as a whole without sacrificing redundancy.

When viewed from the rack, row, room, or building level (or even across a network of data centers at the enterprise level), ARC provides a simple way to answer the question: “Where can I safely add new IT equipment without overloading and potentially bringing down my facility?”

Typically, most data centers don’t calculate ARC. Instead, operators set a simple alarm threshold on the Actual Loadof each device. For example, if the power load reaches 50% on a device (or more often 40% when de-rating), then the device or the monitoring system will throw an alarm.

However, this simple approach to thresholding based on device power usage doesn’t effectively capture all the conditions of the broader power distribution system. There can be hidden capacity that allows for safe failover, even though simple device-level thresholding suggests otherwise.

The goal of system ARC is to identify where you can handle additional load without sacrificing system redundancy. To calculate ARC for power of a device in a dual-feed situation, the calculation is simply:

ARC = {Device Capacity}/2 – {Actual Load}

In most cases, the Device Capacity will be de-rated to allow for some margin. In the case of power capacity, it is common to de-rate apparent power (kVA) capacity by 80%. ARC can also be expressed in real power (kW) if you know or can estimate the power factor of the load. It is even more important to de-rate the capacity in the case kW measurements to allow for potential load problems that could degrade power factor.

Below is an ARC-based dashboard in action:

Here, the top panel shows how ARC has been calculated for 6 different data centers, along with a measure of cooling overhead. The lower panel shows the drill down for one of the sites.

When calculating the overall ARC for devices in parallel, you can add the ARCs of the individual units. For instance:

UPS A has 10 kVA ARC
UPS B has 8 kVA ARC
Together, they have 18 kVA ARC
Interestingly, it is possible to have a safely redundant system even though one of the individual devices has a negative ARC. For example:

UPS A has 3 kVA ARC
UPS B has −2 kVA ARC
The net ARC of the system is a small but safely positive 1 kVA
In this case, even though one UPS is nominally overloaded according to the simple one-device threshold, either UPS can fail without dropping any load.

Calculating system ARC from the individual device ARCs in this way assumes that the capacities of both parallel components are the same. This is most often the case, but in the rare instance that it is not, then you have to total the actual load across the devices, and compare it to the (de-rated) capacity of the smaller device. This ensures that the most-limited device can handle the entire load.

Some questions may arise when the load is imbalanced, as in the examples above. Such imbalances may arise because some of the load is not configured redundantly. Some loads also do not balance themselves between the two power paths. The ARC calculation doesn’t depend on knowing such details. Of course, any non-redundant load will be dropped if it loses its power source; however, as long as the system ARC is positive you know that any redundant load will be protected regardless of which power source is lost.

In summary, the goal of system ARC is to identify where you can handle additional load without sacrificing system redundancy. With parallel equipment, you can total the ARC of all components if they have the same capacity rating. When looking at ARC along the power chain, the correct system value will be the minimum ARC of any one set of components.

Kind regards,

Jay H. Hartley, PhD
Director of Professional Services
Jay.Hartley@Modius.com