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    « The Virtual Data Center, VMware's next move? | Main | Staycations are In, My Project Featured in Sunset Magazine »
    Wednesday
    Jul302008

    EBay SW Developer Discusses Energy Efficient Applications

    Redmond Developer has an interview with Dan Pritchett, Technical Fellow at EBay who thinks about transactions per second per watt (TPS/W).

    It's no secret that power consumption is a worrying issue among datacenter managers. As system hardware becomes cheaper and energy costs continue to rise, IT managers might find that they'll spend more to power and cool a system over its lifetime than to actually buy it.

    Which is why guys like Dan Pritchett, a technical fellow at eBay, has moved beyond thinking about transactions per second (TPS) with his applications to focusing on transactions per second per watt (TPS/w).

    "One of the primary challenges we started to face in 2006 was power. The datacenters were maxed out and we were still running at capacity," said Pritchett, who noted that local municipalities were often physically incapable of delivering enough power to meet eBay's growing energy needs.

    Ideas discussed are database design and threaded code for parallel processing.

    Virtualization has played a huge role in datacenter operations, enabling companies like Google and eBay to maintain ample hardware redundancy while driving up utilization -- a key for energy-efficient design.

    But dev shops can do more, Pritchett said. He urged dev managers to look to established best practices and to focus on efficient, scalable designs. At eBay, for instance, databases are always sharded -- split into smaller pieces -- to produce. "Those things definitely come at a cost," Pritchett said. "But if you are wanting to move into hundreds of millions of entities in your system, and you're wanting to deal with tens or hundreds of millions of transactions per day, that's what you are going to move to."

    He also urged developers to work toward parallel programming, so that fully threaded code can work efficiently across multicore processors. "I think going forward this is definitely going to be a huge issue. We are going to start having to leverage the parallelization of the hardware into the app space," he said.

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