Computer Power
Before we continue I need to say that this is being written on a laptop, which draws a meager 10 to 15 watts of power. That translates to about 0.012 kilowatts and I would be drawing 0.012 kilowatthours in 1 hour. If the price of 1 kilowatt hour is $0.09, then the cost of running the laptop for an hour is $0.09 * 0.012 = 0.108, or about .11 cents.
If I ran the laptop for about a 10 hour work day then it would pull roughly $0.01 per day. (it’s hard to make a precise calculation because the device’s power demands change based on what you happen to be doing).
What about your honking desktop machine? It pulls a whopping 300 watts of power to do the same thing that your laptop does AND we are more likely to leave it running. How much does it cost per day to run a desktop CPU? $0.09 * 0.3 = $0.0270 per hour, or 3 cents per hour. But typically your newer machines (unless you are running a bot net virus) won’t pull all 300 watts so let’s say about 2 cents per hour.
Over a ten hour day that adds up to 20 cents. If you leave it running 24/7, that is $0.48 per day, which adds up to $14.40 a month.
Which brings us to server power. A server typically pulls more than a desktop because a serious server will have redundant power supplies and more aggressive cooling requirements. But let’s say due to software power management that each server pulls about $15 a month. A room of 10 servers then would pull $150/month, or $1,800 per year. A room of 100 servers, $18,000 per year.
As a foot note, Google runs about 450,000 servers in its facility, which comes out to about $81,000,000 per year. This figure does not take into account the enormous air handling systems and other infrastructure power needs of their data center. In perspective, that’s not a huge price to pay for managing so much knowledge.
Where virtualization fits in

Think of the bees as virtual machines and this box as a blade server. Each blade is a physical server. Each bee is a virtual server.
Chances are, you use your desktop or laptop often just to read email or look at a few web pages. But these machines, about which we frequently complain of their chronic slowness, become slow typically because they are waiting for outside things (like stuff on the net to come down). You are likely using less than 10% of your processor 90% of the time. Right now I have 2 text editors and 4 web browsers running and my CPU utilization barely spikes above 4%.
The wasted CPU cycles and power is scant with a laptop. But where this makes a difference is in a datacenter where there can be thousands of computers along a single wall.
Imagine a 20-story office building with only 20 people working, one on each floor. You still have to run the air handlers and send electricity through each floor of the building to keep those tenants happy. At this point, the building is under-utilized, or below its capacity. Yet the infrastructure still has to run as if the building were full.
What if (and this may never happen with real people) the workers in the building were told to make the most efficient use of the office spaces? They would all be required to work on one floor when there are only 20 of them there.
However, during the day time when there are 1,000 people working in the building, they will all scatter throughout the floors and pumping power and air through the entire building makes sense. The building is fully utilized, or at its capacity.
As people leave later in the day, people who stay move closer to others who are staying.
The vacant offices and floors can have their power and air handling shut down or at least minimized.
This is how virtualization works to save power. It makes better use of unused space. Simply put: 1 server running at 75% capacity accomplishes the same tasks as 3 servers running t 25% capacity. Yet, all 4 servers (whether running at 25% or 75%) will pull about the same amount of power and require as much cooling to handle generated heat.
Virtualization allows the 3 physical servers working at 25% to move into ONE physical server working at 75%. Yet to the outside world, there is no difference — all 3 servers are still accessible in the same way as they were when they lived in their own physical machines.
That is a 3 to 1 reduction, or consolidation. The power savings are considerable, especially if this scheme is multiplied out over, say 10,000 servers.
Consolidating servers at night and shutting down unused physical machines can save millions in power bills. That is the immediate effect.
But what if the demands don’t really increase a lot and the server room simply has more physical servers than it needs? Before virtualization for server class PC’s became mainstream, analysts had no choice but to account for future growth by adding more machines in anticipation of the growth. If they are wrong about their expectations, the company just bought a bunch of machines that will not be used, will waste power and will be likely obsolete in a matter of months.
With virtualization, if you had 20 machines in the room and you need to configure 100 separate servers, it can be done without purchasing more physical machines. Often the demand on servers that are built to pre-empt growth will not be used at full capacity from the beginning. Put your beefy existing servers to work at full capacity instead of buying new machines that are just going to run idle and then be obsolete by the time the anticipated growth shows up.
The indirect power savings are enormous. Fewer circuit boards need to be fabricated, fewer cases need to be cast, fewer cables and wires, fewer truck and cargo ship trips to handle fewer physical servers.

This barely scratches the surface on what virtualization can do for you. See VMWare’s TCO/ROI calculator at Alinean to play with some numbers and contact us if you want to know more.
kaht Green Industry