How Peloton Rolls Out New User Features Using AWS

VC investors have historically targeted software businesses and shied away from hardware—perhaps you’ve heard the commonly repeated trope “Hardware is hard”? This is largely because software scales and can quickly be leveraged for use by millions, if not billions of people. Hardware, on the other hand, is more difficult to build in an agile way, since each change to the product requires a heavier lift, such as instituting updates to an entire supply chain.

Luckily for us, this hasn’t deterred a new wave of hardware-based companies from taking on the challenge—and succeeding. Startups like Dollar Shave Club (acquired by Unilever for $1 billion) and Away ($81 million in funding) have created popular new products while also raising and returning millions of dollars to investors.

Joining their ranks is Peloton, a New York-based company that has developed a line of tech-enabled exercise equipment, as well as a deep library of classes that users can work through either in the comfort of their own home or at the gym. Founded in 2012, they have pulled in just shy of $1 billion in funding, which includes a whopping $550 million round in August 2018 at a $4.1 billion valuation.

The startup initially launched with the Peloton Bike, which currently gives its users access to 14 daily, live classes taught by NYC instructors, along with over 8,000 recorded classes available on-demand and streamable through an attached 22” HD touchscreen. In 2018, the company plans to expand into the fitness equipment category with the Peloton Tread, a high-tech treadmill that features a 32” HD touchscreen that acts as a portal to 10+ daily, live classes or 1,000+ recorded courses.

Peloton’s combination of content, software, and hardware creates some interesting technical hurdles. For example, as the company rolls out new features across their platform, they can have varying levels of impact on different pieces of their API. While they can test these releases on a local machine, deploying at scale to its users brings challenges, such as slow response times and increased latency. To solve for this, Peloton utilizes AWS to scale elastically, enabling them to simulate the deploy experience to test where failure points might pop up before publicly releasing any updates.

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