Big Data. Big Decisions
InformationWeek
Special Coverage Series


EBay Launches New Digital Service Efficiency Standard

eBay's new dashboard-based DSE standard measures data center efficiency, allows IT managers to achieve cleaner operations.

eBay, which has operated one of the world's largest Web-based services for 16 years, knows a thing or two about efficient data center infrastructure. Accordingly, it's formulated a Digital Service Efficiency (DSE) measure to take a holistic view of how effectively a data center is running.

An earlier measure, the PUE (power usage effectiveness) appeared late last year. Both metrics resulted from work done by the Green Grid Alliance, a non-profit consortium of IT companies founded in 2007 that shares information on data center efficiency. The consortium includes the Open Data Center Alliance, another non-profit which combined with Green Grid in 2011.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

Power usage effectiveness is a measure of how much power is brought into a data center versus how much gets used by computing equipment. Traditional data centers consume about twice as much power as the computing equipment actually needs, giving them a PUE of 2.0. Facebook's new Prineville, Ore. data center, built for efficient operation, has a PUE that fluctuates between 1.06 to 1.08 -- a highly efficient compared to most.

DSE gives data center operators another efficiency metric, one that's more closely related to how systems are actually running, said Dean Nelson, VP of global foundation services at eBay, in an interview. PUE measures only power consumed by equipment, not how efficiently the service is actually running. DSE looks at system performance: How efficient is this service compared to other services?

[ To learn about how eBay's data centers rely on open source code, see Open Source Helps eBay Process $2,000 A Second. ]

DSE measures four different factors: a service's carbon footprint, its impact on the environment, how much revenue is generated per unit of power consumed, and its plain old-fashioned financial cost. In that sense, DSE yields multiple views -- a kind of Rubik's Cube -- that can be implemented separately from PUE rating. (For a more detailed explanation of DSE, see this eBay white paper.)

Nelson said while it's possible to concentrate on just one area, Digital Service Efficiency is meant to improve all four areas simultaneously. An overall DSE rating is dependent on effective performance in each of the four areas.

Sound complicated? Nelson compares DSE to an automaker's efforts to achieve the best mileage per gallon possible. No matter what the manufacturer intends, the driver's performance still makes a difference, and a DSE dashboard gives IT information about how it's driving relative to performance, revenue, carbon footprint and cost.

"If data centers are the engine of the new economy, then DSE provides the feedback on how the engine is performing to support current business conditions," concluded eBay's white paper.

Nelson cites the example of an eBay software engineer who looked at one of eBay's major ecommerce applications and concluded that it had probably been assigned more server memory than it needed. The programmer adjusted the server configuration and found that the application's performance was unaffected. When the tweak was added to eBay's infrastructure, it resulted in 400 relatively new servers being taken out of service for the application and put to use elsewhere.

"That was 400 servers we didn't have to buy, a capital expense saving of $2 million. It also reduced the amount of power that eBay was consuming by a megawatt over the course of a year. In 2012, eBay used of 18 megawatts of power (18,000 kilowatt hours). Without the software engineer's effort to streamline the application, that figure would have been 19 megawatts," said Nelson.

So shrinking memory affected cost, carbon footprint and revenue favorably, without slowing application response times or driving down performance -- a big win under the DSE standard. Nelson said the software engineer hadn't been assigned the specific task of making the application more efficient. He had looked at its setup and guessed that it was over-provisioned with memory as a precaution. A test drive proved him right. The payoff didn't come until it was applied to all the servers in the IT infrastructure devoted to the app.

"He didn't necessarily realize at first what he had done," Nelson said, suggesting there are more such gains to come by developers and engineers motivated to pursue them. In fact, eBay has started to build this possibility into its culture. After reviewing the 2012 results, eBay's management team set a target of a 10% gain in key DSE metrics in 2013 over 2012. These include increasing the number of transactions per kilowatt hour by 10%, reducing the cost per transaction by 10% and reducing the environmental impact, or carbon footprint, per transaction by 10%.

eBay has constructed a DSE dashboard that shows these measures and indicates how well each measure is doing. IT managers can turn the knobs and pull the levers on the dashboard, Nelson noted, to see what performance they'll get.

The basic unit of business conducted at eBay is buyer and seller transactions. Transactions-per-kilowatt-hour is now one of its standard measures. In 2012, eBay averaged 45,914 transactions per kilowatt hour, with most transactions cutting across several systems to complete the many steps of a typical buy or sell action. Thus, DSE links business process to power usage by employing the transaction as a unit of work.

Several additional measures of digital service efficiency can be taken by tying transactions to kilowatt hours used, transactions per user or transactions per server.

At eBay, the transaction unit of work can be used to evaluate the effectiveness of its 52,075 servers. Nelson says that while any business can set up the same metrics for its digital services, other businesses may face a more complex definition of business events to use as metrics.

eBay has spent two years developing and implementing the DSE. Now that the company has a set of statistics for 2012, it can shoot for specific measures of improvement in future years. "We want to be the cleanest ecommerce engine on the planet," said Nelson.

To improve its carbon footprint -- measured by the tons of carbon dioxide emitted to generate electricity -- eBay uses solar and fuel cell energy where it can. The fuel cells run off methane produced from biofuel contracts with large-scale feedlot operations. The company's goal is to set a high standard -- not just in power used for the amount of work done, but also in the percentage of renewable power used.

Nelson is proud of eBay's efforts. "I believe this is the first time anyone has connected power efficiency to the IT infrastructure [and derived metrics on how effectively digital services are being delivered]," he said.

Initiatives like this are important because most companies don't know how to measure such efficiency, and many companies will have to experiment and share the results in order to lead the way.

Recently, an eBay customer purchased a $369,000 Porsche Carrera GT from his smartphone -- a transaction that's unusual only for the price, given that 9,000 vehicles are sold every week using eBay's mobile applications. The transaction shows how much computing is being done when buyers and sellers are away from their desks and on the go.

"We have a nearly infinite appetite for all kinds of digital services," Nelson said. Therefore, it's more critical than ever for IT ensure that these services delivered in the most efficient and responsible manner possible. The DSE metric is one of the first standards to make this happen.


Attend Interop Las Vegas May 6-10 and learn the emerging trends in information risk management and security. Use Priority Code MPIWK by March 22 to save an additional $200 off the early bird discount on All Access and Conference Passes. Join us in Las Vegas for access to 125+ workshops and conference classes, 300+ exhibiting companies, and the latest technology. Register today!



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.