Discover 158 articles on Performance Profiling in mobile performance
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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.
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...
Tokopedia built an internal tool that automatically finds Android performance bottlenecks. No more manual trace analysis or guessing which methods are slowing you down.
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.
Tokopedia built an automated performance testing pipeline that catches regressions before they hit production. Here's how they measure every build, every night.
Tokopedia's Android team achieved a 40% improvement in app start time and page load speed. Here's the systematic approach that got them there.
Microsoft Teams Mobile merges 50+ commits daily from 350+ developers. How do they catch performance regressions before users feel the pain?
Tokopedia's mobile web was scoring 67-71 on PageSpeed during their biggest sale event. With most traffic on 3G, that meant 5-6 second load times when milliseconds matter most.
Pinterest relies on data to drive decisions and ML models. But what happens when a metric as simple as Daily Active Users gets counted wrong?
DoorDash's OpenTelemetry adoption hit a wall: 72% CPU utilization versus 56% without tracing. That's a costly tax for observability.
"My app is slow" - every engineer's nightmare. Slack's mobile team was tired of hitting dead ends when debugging performance issues.
Israel Abramov from Just Eat Takeaway tested 10 JSON serialization libraries across 8 scenarios. The results? Your default serializer might be costing you serious performance.
Dropbox's Android app was slowly dying by a thousand cuts. Over 4 months, startup time crept up unnoticed until they finally looked at the bigger picture.
Snap's engineering team obsesses over one metric: Time to Camera Ready. Miss the bear crossing the street because your app was too slow? That's exactly the problem they're solving.
Rico Harisin from Tokopedia reveals how their Android team shipped weekly releases while building a complete performance infrastructure from scratch. Their secret? Treating CI/CD like a product.