Performance Profiling

Decision Tree

What performance problem are you investigating?

+ App hangs, stutters, dropped frames, slow UI, high CPU
  -> Read references/time-profiler.md

+ High memory, leaks, OOM crashes, growing footprint
  -> Read references/memory-profiling.md

+ Slow cold launch, warm launch, resume, or time to first frame
  -> Read references/launch-optimization.md

+ Battery drain, thermal throttling, background energy, network waste
  -> Read references/energy-diagnostics.md

+ General "app feels slow"
  -> Start with references/time-profiler.md, then references/memory-profiling.md

+ Pre-release performance audit
  -> Read all reference files and use the review checklist below

Quick Reference

references/time-profiler.md

references/time-profiler.md

references/memory-profiling.md

references/memory-profiling.md

references/launch-optimization.md

references/energy-diagnostics.md

references/energy-diagnostics.md

references/energy-diagnostics.md

Workflow

1. Identify the performance category from the user report, traces, logs, or code path.
2. Read only the matching reference file unless the issue is broad or unclear.
3. Prefer real device profiling with a Release build and representative data.
4. Inspect the code path named by the profile before proposing a fix.
5. Apply the smallest targeted fix that addresses the measured bottleneck.
6. Re-profile or add a repeatable measurement to confirm the improvement.

Profiling Ground Rules

• Profile on device when possible; Simulator uses host CPU and memory.
• Use Release configuration because optimizations can change hot paths.
• Reproduce with representative data, not empty databases or toy assets.
• Close unrelated apps to reduce noise during profiling.
• Keep measurements before and after the fix so the outcome is concrete.
• Add

  os_signpost

  markers when a workflow needs ongoing timing visibility.

Xcode Diagnostics

MetricKit Hook

import MetricKit

final class PerformanceReporter: NSObject, MXMetricManagerSubscriber {
    func startCollecting() {
        MXMetricManager.shared.add(self)
    }

    func didReceive(_ payloads: [MXMetricPayload]) {
        for payload in payloads {
            if let launch = payload.applicationLaunchMetrics {
                log("Resume time: \(launch.histogrammedResumeTime)")
            }
            if let responsiveness = payload.applicationResponsivenessMetrics {
                log("Hang time: \(responsiveness.histogrammedApplicationHangTime)")
            }
            if let memory = payload.memoryMetrics {
                log("Peak memory: \(memory.peakMemoryUsage)")
            }
        }
    }

    func didReceive(_ payloads: [MXDiagnosticPayload]) {
        for payload in payloads {
            if let hangs = payload.hangDiagnostics {
                for hang in hangs {
                    log("Hang: \(hang.callStackTree)")
                }
            }
        }
    }
}

Review Checklist

• No synchronous work on the main thread over 100 ms.
• No file I/O or network calls on the main thread.
• Large Core Data or SwiftData fetches use background contexts.
• Images decode off the main thread.

• @MainActor

  is limited to code that truly needs UI access.

• No retain cycles in delegates, closures, observers, or async tasks.
• Large resources are released when no longer visible.
• Collections and caches are bounded.

• autoreleasepool

  is used in tight loops that create Objective-C objects.

• No heavy work in

  init()

  of the

  @main App

  struct.
• Non-essential initialization is deferred.
• Dynamic frameworks are minimized where practical.
• No synchronous network calls occur during launch.

• Background tasks use the appropriate

  BGTaskScheduler

  request type.
• Location accuracy matches the product need.
• Timers use tolerance so the system can coalesce wakeups.
• Network requests are batched and cached where possible.

References

• references/time-profiler.md

  : CPU profiling, hang detection, signpost API.

• references/memory-profiling.md

  : Allocations, Leaks, Memory Graph debugger.

• references/launch-optimization.md

  : Launch phases and cold/warm start optimization.

• references/energy-diagnostics.md

  : Battery, thermal state, and network efficiency.