Consequences of an Inefficient Information Factory aka Data Center

I posted on the concept of data centers being information factories.  Philip Petersen of wrote.

But when you mention "companies like Google" - are there really many companies like Google? I don't think so - not today.

I’ve actually had a few skype conversations with Philip and last year at Data Center Dynamics London I met Philip. So, I know he is a regular reader.

I agree there are not many companies like Google.  Here are a few things I think Google does that fit the model of an information factory.

  1. Urs Hoelzle as executive and influential in the company running data centers understands the role of Google’s information factories.  Once I asked Urs why he doesn’t shut down idle servers, his response was he would rather think how does he use the servers while they are idle.  And, Urs can think this way given his position and influence in Google.  What Google knows that few do is turning on and off servers, is not reliable enough for a lights-off type of operation. Desktops, laptops, mobile devices, and phones all have this problem as well, but people are pushing the buttons and can try again when turning on fails.
  2. Their focus on PUE accuracy and reporting demonstrates their thinking in process control and statistical accuracy.
  3. Google knows the shell of a building is cheap, and 85% of the costs in data centers is in the power and cooling infrastructure.
  4. The cost of electricity is greater the the cost of a server over a typical 3 year lifespan.
  5. The vendors – data center, server, network are just as silo’d as companies IT organizations and don’t drive for overall system efficiencies.  So, Google designs their own systems, and uses the vendors as subcontractors to their designs.  It may not be totally accurate analogy, but Boeing designs the plane and subcontracts out pieces and components.  There are some pieces that are off the shelf, like engines (for servers processors), but many time parts don’t perform as advertised when integrated.

I could go on, but these are just a few ideas that demonstrates Google runs their data centers as computers, see this paper.  The information factory metaphor communicates the scale, power, and complexity.



As Philip says there are not many like Google.  Which means they have inefficient information factories that are a drain on the companies revenue.  And, in this economy cost reduction is a priority.  Do you cut costs by making the system more efficient?  No.  You cut costs by limiting headcount, budgets and capital expenditures which ironically many times will increase your costs long term as you grow and decrease your overall performance per watt.  Right now many companies don’t need the performance so you are removing capacity from the system to cut costs.  Makes sense, but I bet the company executives did not consciously decide to reduce the capacity of their information factory.  How can you not think reducing costs capital and operating expenses reduces capacity?

In this economy Google may reduce the rate of their expansion, but overall their information factory capacity is growing and performance per watt is improving.

Philip asked a good question.  “are there really many companies like Google”? 

No, but there will be more.  Google can do this because the company itself is an information factory.  And, the future successes in internet services will be those who have the most efficient information factories that can produce information at the lowest costs.