One simple question. That’s all it took for Christophe Bisciglia to bewilder confident job applicants at Google (GOOG). Bisciglia, an angular 27-year-old senior software engineer with long wavy hair, wanted to see if these undergrads were ready to think like Googlers. “Tell me,” he’d say, “what would you do if you had 1,000 times more data?”
What a strange idea. If they returned to their school projects and were foolish enough to cram formulas with a thousand times more details about shopping or maps or—heaven forbid—with video files, they’d slow their college servers to a crawl.
At that point in the interview, Bisciglia would explain his question. To thrive at Google, he told them, they would have to learn to work—and to dream—on a vastly larger scale. He described Google’s globe-spanning network of computers. Yes, they answered search queries instantly. But together they also blitzed through mountains of data, looking for answers or intelligence faster than any machine on earth. Most of this hardware wasn’t on the Google campus. It was just out there, somewhere on earth, whirring away in big refrigerated data centers.
Folks at Google called it “the cloud.” And one challenge of programming at Google was to leverage that cloud—to push it to do things that would overwhelm lesser machines. New hires at Google, Bisciglia says, usually take a few months to get used to this scale. “Then one day, you see someone suggest a wild job that needs a few thousand machines, and you say: Hey, he gets it.'”