Energy usage, Monitoring and Green IT

Energy usage

Is there a need to do something about the rising energy needs of data centers? Yes there is, some examples:

  • Increased energy costs for organizations;
  • Increased capital costs for expansion and construction of data centers;
  • Increased strain on the existing power grid;
  • Regulations, standards and compliance;
  • Corporate reputation;

For energy-efficiency , PUE and DCiE are one of the most commonly metrics and formulae ( But how to get these kind of figures for your company? A data center is a complex system so energy metering isn’t easy.

Once electricity is supplied to a data center, several and various devices consume the electrical power. A data center has from a power perspective a supply chain that consist of four large building blocks: the IT infrastructure (servers, storage and network), the primary power supply (UPS, PDU, etc.), the secondary support supply (cooling, generator, air handling) and the tertiary support supply (lighting, and everything else). Virtually all power consumed by the IT infrastructure is converted to heat. Typically about thirty to fifty percent of total power usage in a data center represents the load placed by IT infrastructure while the other percentage is for cooling, power distribution, lighting, etc.

Energy Paths

A practical example of using this kind of metrics is given by Google who made their energy usage public (

IT infrastructure is basically a value stack. A supply chain of stack elements who act as a service component ( (People, Process and IT that adds up to an IT service). For each element in the stack the IT organization has to assure quality as agreed on. In essence these quality attributes were performance, availability, confidentiality and integrity. One of the most big challenges for the IT organization was and is to coherently manage these quality attributes for the complete service stack or supply chain. Energy as quality attribute is a new kid on the block. This attribute is composed of the Power, Cooling, and Floor Space  sub attributes. These attributes are not independent from each other. For a given data center these resources are constrained therefore, together, these  attributes form a certain threshold. If the demand for IT capacity reach this threshold further growth of the IT load is inhibit because of technical (over heating, not enough power) and or financial (excessive capital investment) reasons.


To improve the energy efficiency of existing data centers, as well as making decisions on new data center there are some metrics being used: Power Usage Effectiveness (PUE), Data Center Infrastructure Efficiency (DCIE) and Data Center Productivity (DCP). Ideally, these metrics and processes will help determine if the existing data center can be optimized before a new data center is needed. To steer and control power usage successfully a power usage monitoring system should be in place to get this done.

For designing an efficient power usage monitoring framework, it is important to assemble a coherent system of functional building blocks or service components. Loose coupling and strong cohesion, encapsulation and the use of Facade and Model–View–Controller (MVC) patterns is strongly wanted because of the many proprietary energy metering solutions.

Building blocks

  • Most vendors have their own proprietary API’s  to interface with the metering devices. Because energy metering differ within and between data centers these differences should be encapsulated in standard ‘Power services‘. Services for the primary,secondary and tertiary power supply and usage.
  • For the IT infrastructure (servers, storage and network components) power usage we got the same kind of issues. So the same receipt, encapsulation of proprietary API’s in standard ‘IT Power services‘, must be used.
  • Environmental conditions outside the data center, the weather, has its influences on the power consumption of the data center so proper information about this must be available by a dedicated Outdoor service component.
  • For a specific data center an DC Energy Usage Service Bus must be available to have a common interface for exchanging energy usage information with reporting systems.
  • The Energy Data Store is a repository (Operational Data Store or Dataware House) for energy usage data across data centers.
  • The Configuration management database(s) (CMDB) is a repository with the system configuration information of the primary, secondary and tertiary power supply and the IT infrastructure of the data centers.
  • The Manufactures specification databases stores specifications/claims of energy usage of components as provided by the manufactures.
  • The IT capacity database stores the available capacity (processing power and storage) size that is available for a certain time frame.
  • The IT workload database stores the workload (processing power and storage) size that must be processed in a certain time frame.
  • The Energy Policy Base is a repository with all the policies, rules, targets and thresholds about energy usage.
  • The Enterprise DC Energy Usage Service Bus must be available to have a common interface for exchanging policies, workload capacity, CMDB, manufacturer’s  and energy usage information of the involved data centers, with reporting systems.
  • The Composite services deliver different views and reports of the energy usage by assembling information from the different basic services by means of the Enterprise Bus.
  • The Energy Usage Portal is the presentation layer to the different stakeholders that want to know something about the IT energy usage.

Usage of an architectural framework is a must to get an energy monitoring environment working. This assembly of service components gives you the opportunity to see the average or instantaneous energy usage and compare this with the average or instantaneous IT workload and available IT capacity. Comparisons with the Energy Policies and the manufacturer specifications/claims of energy usage are also possible.

Energy Monitoring Architecture

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