iOS × Performance Profiling
iOS Performance Profiling, page 3
iOS Performance Profiling articles 61–88 of 88
Spotting Latency Regressions Ahead of Time at Teams Mobile
Microsoft Teams Mobile merges 50+ commits daily from 350+ developers. How do they catch performance regressions before users feel the pain?
Trusting Metrics at Pinterest
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?
Optimizing OpenTelemetry's Span Processor for High Throughput and Low Latency
DoorDash's OpenTelemetry adoption hit a wall: 72% CPU utilization versus 56% without tracing. That's a costly tax for observability.
Client Tracing: Understanding Mobile and Desktop Application Performance at Scale
"My app is slow" - every engineer's nightmare. Slack's mobile team was tired of hitting dead ends when debugging performance issues.
JSON Serialization Libraries Performance Comparison
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.
Time to Camera Ready
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.
Mobile App Launch Performance II
At Farfetch, a 0.1 second delay in warm app launch costs $4.2M annually. That's less time than it takes to blink.
Monitoring App Performance on iOS
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.
Tracing at Slack: Thinking in Causal Graphs
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.
Leveraging Mobile Infrastructure with Data-Driven Decisions
Spotify's mobile infrastructure team turned build time chaos into predictable performance. Their secret? Making every engineer a data scientist.
Understanding the aspects of iOS App Launch Time | by Ravi Aggarwal | Medium
First impressions matter. For iOS apps, that means every millisecond between tap and first screen counts.
One Approach to Monitoring iOS Application Performance
Mercari's iOS team needed to monitor performance without building an entire infrastructure team. Here's how they did it in under a week.
Journey to a Faster Everyday Super App
Grab cut app startup time by 60% while shipping dozens of new features. Here's how they did it without compromising velocity.
Journey to a Faster Everyday Super App: Where Every Millisecond Counts
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.
Improving GraphQL API performance and consistency with AWS AppSync Caching and DynamoDB Transactions support
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.
Introducing Nanoscope: An Extremely Accurate Method Tracing Tool for Android Development
Uber's Android team hit a wall: their profiling tools were either too slow or too inaccurate to debug real performance issues.
Employing QUIC Protocol to Optimize Uber’s App Performance
Uber operates across 600+ cities on 4,500+ mobile carriers. Their HTTP/2 stack was failing users in lossy wireless networks.
Performance comparison of video coding standards: an adaptive streaming perspective
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...
Unified Cross-Platform Performance Metrics
Slack's engineering team faced a classic scale problem: three platforms, three definitions of 'app launch,' and zero ability to compare performance meaningfully.
3 Techniques We Used to Improve Skyscanner for iOS Performance
Skyscanner's iOS team discovered their app was lagging on nearly half their user base. The culprit? Testing only on high-end devices.
React Native Performance In Marketplace
Facebook cut React Native Time to Interaction in half on low-end Android devices. The secret? They stopped trusting their testing tools and went straight to production data.
Detecting List Items Observed by User
Zalando's engineering team faced a tricky challenge: how do you know if a user actually *saw* an item in a scrolling list, not just flew past it?
The Mobile Device Lab at the Prineville Data Center
Facebook built a 2,000-device testing lab inside a data center. The journey from tangled cables to custom EMI racks is a masterclass in scaling mobile performance testing.
Getting to Slack Faster with Incremental Boot
Slack was making 4.2 million users wait through loading screens every single day. Time to fix that.
Dive Into React Native Performance
The React Native team made their app startup twice as fast. Here's how they tackled one of mobile's most critical performance challenges.
Solving the Problem of One Billion Computations
Skyscanner needed to store 1.6 billion weights to rank hotel prices. Their in-memory approach couldn't scale, so they turned to AWS.
Optimizing Facebook for iOS start time
Meta's iOS team achieved multi-second improvements in Facebook app startup by rethinking when work actually needs to happen.
Mobile Performance: Tooling Infrastructure at Facebook
Facebook processes thousands of mobile code changes weekly. How do they catch performance regressions before users feel the pain?