Why cloud computing success hinges on power management

Cloud computing models are based on gaining maximum yields for all resources that go into the data center. This is one of the keys to delivering services at a lower cost. And power is one of the biggest bills in a cloud environment. Cloud data centers now consume an estimated 1–2 percent of the world’s energy.[1] Numbers like that tell you the cloud’s success hinges on aggressive power management.

So let’s talk about some of the steps you can take to operate a more efficient cloud:

  • Better instrumentation. The basis for intelligent power management in your data center is better instrumentation at the server level. This includes instrumentation for things like CPU temperature, idle and average power, and power and memory states. Your management capabilities begin with access to this sort of data.
  • Better power management at the server and rack level. Technologies like dynamic power capping and dynamic workload power distribution can help you reduce power consumption and place more servers into your racks. One Intel customer, Baidu.com, increased rack-level capacity by up to 20 percent within the same power envelope when it applied aggregated power management policies. For details, see this white paper.
  • Better power policies across your data center. Put in place server- and rack-level power policies that work the rest of the policies in your data center. For example, you might allocate more power capacity to a certain set of servers that runs mission-critical workloads, and cap the power allocated to less important workloads. This can help you reduce power consumption while still meeting your service-level agreements.
  • Better power management at the facilities level. There are lots of things you can do to drive better efficiency across your data center. One of those is better thermal management through the use of hot and cold server aisles. Another is thermal mapping, so you can identify hot and cold spots in your data center and make changes to increase cooling efficiency.

Ultimately, the key is to look at power the way you look at all other resources that go into your data center: seek maximum output for all input.

[1] Source: Jonathan Koomey, Lawrence Berkeley National Laboratory scientist, quoted in the New York Times Magazine. “Data Center Overload,” June 8, 2009.