Discover 155 articles on Performance Profiling in mobile performance
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Doni Winata from Traveloka's Android Infra team reveals how his team automated build benchmarking to catch performance regressions before they hit production. For projects with 300+ modules and 15-20 minute bui...
Coinbase scaled from a handful of engineers on one platform to four platforms with zero standardized performance measurement. How do you unify performance tracking across web, mobile, backend, and extensions?
Pinterest was bleeding user engagement on Android. With 75% of signups coming from outside the U.S. and 90% of global smartphones running Android, they had to fix their performance problem fast.
Grab's engineering team discovered their Go apps were mysteriously throttling at 1.94 CPU cores but flying at 2 cores. The culprit? A sneaky interaction between Kubernetes VPA and GOMAXPROCS.
OkCredit serves millions in India's Tier-2/3 cities where flaky networks are the norm. Their Android team just cut network call times by 30% with some clever client-side optimizations.
Klarna's team removed their caching layer and saw a 25% performance boost. Wait, what?
Mercado Libre's Android team achieved a 24% performance boost without using Google's recommended Baseline Profiles or Macrobenchmark tools. How did they pull it off?
OkCredit slashed their Android app cold startup time by 70%. Here's the engineering playbook that made it happen.
Instawork's Android app was taking 5-6 seconds to start while iOS clocked in at just 1.5 seconds. That performance gap was killing their user experience on low-to-mid range devices.
Mercado Libre's mobile apps serve 4.5 billion active devices. A Galaxy A10 might take 5 seconds to load a screen—or just 1.67 seconds, depending on conditions.
Dream11 handled 5.5 million concurrent users and 80 million requests per minute during IPL 2020. Their secret? A custom performance testing framework called Torque.
Slack's engineering team ran into a classic performance testing problem: spinning up load tests was so time-consuming that teams avoided doing it. Their solution? Never stop testing.
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.
Grab's engineering team just unlocked 30% memory savings and 38% storage reduction with a simple compiler flag. Here's how Profile-Guided Optimization (PGO) delivered massive gains with minimal code changes.
Booking.com discovered that standard performance monitoring tools from Apple, Google, and Firebase couldn't meet their needs. So they built their own—and just open-sourced it.
Building Flutter games? Very Good Ventures shows how combining Flame engine with Bloc state management creates cleaner, more testable game code without sacrificing performance.
The Paytm Editorial Team reveals how they measure the real cost of user friction: tracking payment flows down to the millisecond, excluding network delays that mask app performance issues.
Angus Croll from Netflix reveals how his team slashed false performance alerts by 90% while catching more real regressions. The secret? They stopped using static thresholds entirely.
React Native's bridge can be your bottleneck or your superpower. Callstack explores the critical tradeoff between JavaScript flexibility and native performance that determines whether your app flies or crawls.
Airbnb moved beyond Time To Interactive to measure what users actually see. Their Page Performance Score tracks visual wait time, not just code execution.