Big Data. Big Decisions
InformationWeek
Special Coverage Series


Microsoft's New Data Center: The Straight Poop

Microsoft plans zero-carbon data center in Wyoming that will use biogas from an adjacent wastewater treatment plant as its power supply.

Microsoft's planned Data Plant is a zero-carbon data center that may prove to be the blueprint for information facilities that run outside the power grid. Its environmentally friendly status comes from an unusual power source: human waste.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

Microsoft is investing $5.5 million on research and development in the pilot project at the Dry Creek Water Reclamation Facility in Cheyenne, Wyoming. The data center will use biogas from an adjacent wastewater treatment plant as its power supply.

"It provides an exciting, first-of-its kind opportunity to develop viable capabilities and best practices for capturing and reusing natural bi-products like biogas directly from wastewater treatment plants, agricultural farms, fuel refineries and waste landfill sites, etc., in the future," writes Microsoft senior research program manager Sean James in a blog post on the Data Center project.

Biogas is made mostly of methane and carbon dioxide, but may also contain small amounts of other gasses, including hydrogen sulfide and nitrogen. It's produced by anaerobic digestion, a process in which bacteria that live only in places without air break down organic, biodegradable matter, such as sewage, animal manure, municipal waste and plant material, according to the American Biogas Council.

[ Are data centers bad for the environment? See N.Y. Times Data Center Indictment Misses Big Picture. ]

As Microsoft sees it, data centers and waste treatment plants have a lot in common. "In a sense, wastewater treatment plants can be considered distant cousins of data centers -- they are mission-critical facilities with high availability infrastructure built into the plant. These plants cannot go offline any more than a community can stop flushing. The result ensures a very consistent and reliable flow of biogas to power our Data Plant," James writes.

Microsoft's data center is optimized to consume waste gasses. After filtering out trace contaminants and moisture, it uses a molten carbonate fuel cell to convert methane and carbon dioxide into electrical energy, which is used to power the data center.

The pilot project is clearly for test purposes, however. The 200-kW Data Plant will host only "non-production computing applications," Microsoft says.

"Although, this is of course only a fraction of the size of our typical data centers, the knowledge acquired will allow us to model how a large facility will react," James writes.

The Data Plant's fuel cell can produce up to 300 kW. Any power not consumed by the data center will be returned to the waste treatment plant to reduce its energy costs.

James notes that Microsoft's Wyoming facility isn't the first fuel-cell-powered data center running on biogas. What makes the Data Plant unique, however, is its direct integration with its biogas source.

"It will lessen the need for high-quality biogas filtration and reduces the demand on the natural gas pipeline," he writes.

Once the R&D project is complete, Microsoft will donate the Data Plant to the City of Cheyenne and the University of Wyoming for future research.

The ultimate goal of the Data Plant program is to free data centers from having to rely on expensive and potentially unstable power grids.

At first glance, the Data Plant may not seem like a big data project -- but that's only if you apply a rather narrow definition of "big data." A data center with its own economical and reliable power source could be a very appealing proposition to companies with cloud-based data services, which are growing rapidly.

Download the new issue of Must Reads, a compendium of our best recent coverage on IT-as-a-service. It includes articles on cloud computing myths, how to build an IT service catalog, security problems, and more. (Free registration required.)



Related Reading




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.