88 articles on Performance Profiling for iOS performance
Showing 20 of 88 articles (Page 4 of 5)
Microsoft Teams Mobile merges 50+ commits daily from 350+ developers. How do they catch performance regressions before users feel the pain?
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.
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.
At Farfetch, a 0.1 second delay in warm app launch costs $4.2M annually. That's less time than it takes to blink.
Expedia's iOS team breaks down the complete performance monitoring toolkit every mobile team needs. Your users notice lag after just 300ms—here's how to stay ahead.
Slack processes 8.5 billion spans daily, but their tracing system looks nothing like traditional distributed tracing. Here's why they rebuilt it from scratch.
Spotify's mobile infrastructure team turned build time chaos into predictable performance. Their secret? Making every engineer a data scientist.
First impressions matter. For iOS apps, that means every millisecond between tap and first screen counts.
Mercari's iOS team needed to monitor performance without building an entire infrastructure team. Here's how they did it in under a week.
Grab reduced their super app's startup time by 60% while shipping dozens of new features. Here's how they saved users 59,582 hours per day.
Grab cut app startup time by 60% while shipping dozens of new features. Here's how they did it without compromising velocity.
AWS just shipped two features that solve opposite problems: making GraphQL APIs blazing fast and keeping DynamoDB writes bulletproof. Here's how they change the game for mobile backends.
Uber's Android team hit a wall: their profiling tools were either too slow or too inaccurate to debug real performance issues.
Uber operates across 600+ cities on 4,500+ mobile carriers. Their HTTP/2 stack was failing users in lossy wireless networks.
Joel Sole and the Netflix encoding team reveal why codec comparison studies often contradict each other—and how they're fixing the problem. Their findings challenge conventional wisdom about H.264, H.265, and V...
Slack's engineering team faced a classic scale problem: three platforms, three definitions of 'app launch,' and zero ability to compare performance meaningfully.
Skyscanner's iOS team discovered their app was lagging on nearly half their user base. The culprit? Testing only on high-end devices.