iOS Performance Monitoring with Datadog

Yassir Ramdani and Austin Lai from Datadog built a custom SwiftUI graphing library that renders thousands of data points without lag. Here's how they debugged performance bottlenecks that most iOS developers never see.

Datadog's mobile team needed native data visualization for their iOS app, but existing libraries couldn't handle their complex dashboards with thousands of data points. They built DogGraphs from scratch using SwiftUI, then had to solve serious performance issues when rendering graphs with 7,345+ data points across 113 lines.

Key Takeaways

• Reduced View body evaluations from 339 to 113 by restructuring coordinate system
• Batching shapes by style cut thousands of renders to just distinct styles count
• SwiftUI uses memcmp for POD types, Equatable when available, reflection as fallback
• Expensive logic in View bodies causes micro-hangs even with 15µs average duration

The team discovered that SwiftUI's diffing mechanism was causing double the expected View evaluations, and the fix required rethinking how their result builder worked.