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Опубликовано 5 сентября 2018, 16:12
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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. Watch to learn more.
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. Watch to learn more.
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