In the more than five years since launching Pure’s first commercial product, the team had developed a deep understanding of its customers’ pain points. Most competitors offered complex storage tools with thousands of settings—and often, hours-long delays before data was delivered. But Pure was laser-focused on simplicity and approached storage as a customer product—and the customer was royalty.
Instead of forcing users to wade through dozens of performance metrics, for example, Pure developed a single, actionable number called “load,” which dramatically simplifies capacity management. As the team worked to further optimize events like upgrades and migration, they realized that machine learning (ML) would be key.
“We backed our way into ML,” Abrol says. “We’d zoned in on capacity and performance forecasting was the hardest problem facing our customers. Then it was, ‘Okay, how do we solve it?’ And we realized we had this data.”