Explore 17 articles from Lyft on mobile performance
Showing 17 of 17 articles (Page 1 of 1)
Oleksii Chyrkov from Lyft just closed the book on a 7-year migration journey. The final push to eliminate Java from their entire Android codebase revealed some brutal truths about automated tooling.
Lyft's iOS team built an Apple Maps extension that lets users book rides without leaving Maps. But the initial version added 45MB to their app—nearly a quarter of Apple's 200MB cellular download limit.
Lyft built Live Activities that update millions of users per week—but iOS sandboxing, 4KB payload limits, and image rendering nearly killed the project.
Michael Ramdatt and the Lyft team reveal how they beat every competitor to launch the first rideshare app on CarPlay and Android Auto. The secret? Building their own mapping platform from scratch.
Lyft Bikes & Scooters was drowning in complexity: 3 vehicle types, multiple markets, and endless switch statements. Their solution? Move the UI logic to the server.
Lyft discovered memory leaks affecting only 1% of users—issues that would never show up in local testing. Here's how they built a production monitoring system to catch what profiling tools miss.
Lyft engineers faced a nightmare scenario: feature flags causing infinite crash loops on app launch, requiring emergency hotfixes and losing revenue. They built Safe Mode to break the cycle.
Lyft's iOS tests were spending 93% of their time on steps that had nothing to do with what they were actually testing. Sound familiar?
JP Simard from Lyft reveals how they replaced URLSession and OkHttp across all their mobile apps with a single networking library—and the results weren't what anyone expected.
Lyft's Android app serves millions of users daily, but how do you track CPU performance when hundreds of engineers ship code constantly? The team built a custom monitoring system from scratch.
One Android developer at Lyft cut app startup time by 21% in just 30 days. Here's how they convinced leadership to prioritize performance over features.
Lyft was serving 17.1M riders while their Android app launched 15-20% slower than competitors. Time to fix that.
Pierce Johnson from Lyft reveals how a custom IntelliJ plugin transformed productivity for 60+ Android developers. The secret? Automating the repetitive tasks that were quietly draining engineering velocity.
Keith Smiley from Lyft just announced something that could change how we all build mobile apps. Instead of every company rebuilding the same infrastructure in silos, major tech players are finally collaborating...
Jingwei Hao from Lyft reveals how real-time stats APIs caught a production crash spike at 9:55am, enabling engineers to ship a hotfix before most users even noticed the problem.
Lyft's mobile apps used to poll a single endpoint every 5 seconds for everything. That "Universal Object" became their biggest reliability nightmare.
Michael Rebello from Lyft reveals how they scaled from hand-written APIs to a unified networking architecture serving 500+ endpoints. The journey involved killing technical debt, slashing payload sizes by 50%, ...