
Anam Hira
@anamhira • 2,015 subscribers
@tryrevyl - proactive reliability | prev uber ai 🏎️
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At Uber, one bug reaching production could cost millions in a single day. So quality was solved with headcount. Rooms of people would manually tap through the app before every release. Request a ride, add a card, cancel a trip, in 50+ languages, release after release. Now coding agents have increased the throughput of changes by an order of magnitude. A room of people can't keep up anymore. Nobody can. Here we used Revyl to run those same flows on Ubert (demo uber), sending our mobile use agent through the app on a cloud iOS device. Every step verified, with CPU, network, and state traces attached when something breaks. What took a room of testers hours per release runs in 16 minutes, asynchronously. Get started with our free trial and put an agent on your own app.
Anam Hira377,204 views • 25 days ago

Uber had entire floors of people doing manual testing and manually clicking through the app, checking whether the app worked. It still wasn't enough, and it was too expensive They used deterministic script frameworks like Appium and XCUITest, but engineers ended up spending 50% of their time just maintaining test cases because of their brittle nature. This is a clip from a conversation with one of my DragonCrawl teammates and the overall goat, Juan Lopez Marcano, discussing the problems Uber faced at scale with end to end mobile testing.
Anam Hira233,602 views • 8 months ago
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