88 articles on Performance Profiling for iOS performance
Showing 20 of 88 articles (Page 3 of 5)
Snap's AR Lenses reach millions, but performance issues can kill engagement before users even see your creation. Here's how Snap ensures their AR experiences work across every device.
Filip Busic from DoorDash reveals how three targeted optimizations slashed iOS app launch time by 60%. The culprits? String operations, hashing strategies, and sneaky third-party framework initializers.
Strava's iOS app was slowing down as they scaled to 1 billion activities in 18 months. Their solution? A ruthless focus on "Time to Something Useful."
Swiggy's iOS app was taking forever to launch. Their mobile team spent 3 months hunting down bottlenecks and achieved a 12x improvement in cold start time.
Snap Research just proved that Vision Transformers can run as fast as MobileNet on actual mobile devices. Yes, really.
Klarna's A/B testing platform needed single-digit millisecond latency at 99.9%. Their Node.js service was spiking to seconds under load.
Indragie Karunaratne from Sentry reveals how they built a production-ready iOS profiler that runs on millions of real user devices. Most profilers only work locally, but this one collects real-world performance...
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.
Klarna's team removed their caching layer and saw a 25% performance boost. Wait, what?
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.
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.
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.
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 built a unified performance scoring system that works across all platforms. Here's how they instrumented it on iOS to track real user experience at scale.
Airbnb ditched single-metric performance tracking and built something better. Here's how they unified web, iOS, and Android performance into one 0-100 score.
Lyft was serving 17.1M riders while their Android app launched 15-20% slower than competitors. Time to fix that.
Victor Oliveira from Mercado Libre reveals a harsh truth: 53% of users uninstall apps due to performance issues. With 4.5 billion active Android and iOS devices worldwide, each performing differently, mobile pe...
Eric Robertson from AWS AppSync reveals how pipeline resolver caching slashed database requests by 99% for some customers. If your GraphQL API is hitting backend services too hard, this changes everything.