/performance

Launch Time Optimization

App Launch Phases

Cold Launch Timeline
────────────────────────────────────────────────────────
│  Pre-main                │  Post-main               │
│                          │                           │
│  DYLD        Runtime     │  App Init    First Frame  │
│  loading     init        │  UIKit/SwiftUI setup      │
│  ──────────  ──────────  │  ────────────  ──────────  │
│  dylibs      +load       │  AppDelegate   viewDidLoad│
│  rebasing    static      │  @main App     .body      │
│  binding     initializers│  scene setup   layout     │
│              ObjC setup  │  root view     render     │
────────────────────────────────────────────────────────
                                              ↑
                                    First Frame Rendered
                                    (launch complete)

Target Budgets

Cold launch: App not in memory — full DYLD load, runtime init, UI setup. Slowest, highest variance. Warm launch: Process spawned fresh, but app/data recently in memory and system services running. Resume: App was suspended in background — already running, not a launch; don't count it in launch measurements (WWDC19 423).

Apple's headline goal: first frame in 400ms — roughly the duration of the launch animation, so the app appears ready the moment it ends. Rough split: ~100ms of system-side work, leaving ~300ms for you to create views, load content, and render (WWDC19 423). Measure warm launches — they're more consistent than cold.

The Six Launch Phases (WWDC19 423)

There's also an optional extended phase after first frame: async-load remaining data while the app is already interactive, and instrument it with os_signpost so you know exactly what runs between first frame and fully loaded (WWDC19 423).

The session's demo went 2.5s → ~300ms by fixing phases 3, 5, and 6 — see the two case studies under Post-main Optimization below.

App Launch Instrument

Setup

1. Xcode > Product > Profile (Cmd+I)
2. Choose App Launch template
3. Record — the app launches and Instruments captures the entire timeline (the template runs the app for five seconds, gathering a Time Profile + Thread State Trace of the launch — WWDC21 10181)
4. Stop after app is fully interactive

Reading the Results

• Process Lifecycle lane shows app state transitions
• Thread State lane shows main thread activity during launch
• Time Profiler lane shows CPU work during launch
• Focus on the region between process start and first frame
• Timeline colors: purple = pre-main phases, green = post-main (UIKit init, app init, first frame). Thread states: gray = blocked, red = runnable but starved of CPU, orange = preempted, blue = running. The left pane narrates the selected phase; the event list shows which thread unblocked the main thread (WWDC19 423)
• Distinguish CPU time vs wall clock — the 423 demo's dyld phase showed 149ms wall clock but only 6ms CPU (the rest was profiling overhead)

Key Measurements

• Time to first frame: Total duration from process start to first CA commit
• Pre-main time: From process start to main() / @main entry
• Post-main time: From main() to first frame rendered

Pre-main Optimization

Reduce Dynamic Frameworks

Each dynamic framework adds ~10-30ms to launch:

Before: 15 dynamic frameworks → ~300ms DYLD loading
After:  3 dynamic frameworks  → ~50ms DYLD loading

How to fix:

• Convert dynamic frameworks to static libraries where possible
• Use Swift Package Manager (static by default) instead of dynamic frameworks
• Merge small frameworks into fewer larger ones
• Check with: otool -L YourApp.app/YourApp to list linked dylibs

More dylibs = more dyld work + more dirty DATA pages; too many static libs = slow iterative builds. The ld64 rewrite in Xcode 14 (~2× faster linking) moved the sweet spot toward fewer dylibs (WWDC22 110362). Play to dyld3's warm-launch caching: hard-link all dependencies, avoid dlopen/NSBundle.load (dynamic loading forfeits the cache), prune unused frameworks (WWDC19 423).

Remove Static Initializers

Static initializers (+load, __attribute__((constructor))) run before main():

// Bad — runs before main(), delays launch
class LegacyManager: NSObject {
    override class func load() { // ObjC +load
        setup()
    }
}

// Bad — C-style constructor
@_cdecl("initEarly")
func initEarly() { /* runs before main */ }

// Good — defer to first use
class LegacyManager {
    static let shared = LegacyManager() // Lazy, created on first access
}

• Move +load (runs on every launch) to +initialize (lazy, on first use); the 423 demo saved 300+ ms this way (WWDC19 423)
• If your framework needs setup, expose an explicit API instead of a static initializer
• ❌ Static initializers doing I/O, networking, or anything beyond a few milliseconds — they always run before main(); in the 110362 TextEdit measurement, static initializers dominated launch after fixups shrank to ~1ms (WWDC22 110362)

Minimize ObjC Metadata

• Large ObjC class hierarchies increase rebasing/binding time
• Swift classes without @objc are more efficient
• Reduce ObjC category usage (each category adds metadata)

Linker & Runtime Levers (WWDC22 110362 / 110363)

Raising your deployment target is itself a launch/size optimization:

Verify with dyld_usage (macOS, Simulator, Catalyst: per-launch dyld time breakdown) and dyld_info -exports / -fixups (inspect any binary, even inside the dyld shared cache) (WWDC22 110362).

Post-main Optimization

Defer Non-Essential Initialization

@main
struct MyApp: App {
    init() {
        // Bad — all of this delays first frame
        AnalyticsManager.shared.configure()
        CrashReporter.shared.start()
        RemoteConfig.shared.fetch()
        ImageCache.shared.warmUp()
        DatabaseMigrator.run()
    }

    var body: some Scene {
        WindowGroup {
            ContentView()
        }
    }
}

// Good — only essential work at init, defer the rest
@main
struct MyApp: App {
    init() {
        // Only crash reporter is truly needed immediately
        CrashReporter.shared.start()
    }

    var body: some Scene {
        WindowGroup {
            ContentView()
                .task {
                    // Defer everything else to after first frame
                    await deferredSetup()
                }
        }
    }

    private func deferredSetup() async {
        AnalyticsManager.shared.configure()
        RemoteConfig.shared.fetch()
        ImageCache.shared.warmUp()
    }
}

Phase-5 rules from WWDC19 423: minimize (defer undisplayed views and speculative pre-warming; no network or file I/O on the main thread), prioritize (correct QoS everywhere), optimize (lazy compute, fetch only first-frame data, cache computed values), and share resources between scenes.

Priority Inversion at Launch (WWDC19 423)

The 423 demo's didFinishLaunching took 791ms — the main thread spent 754ms blocked on a semaphore waiting for a background worker: main runs at user-interactive QoS (47), the async'd worker at QoS 4, and the semaphore hid the dependency from the scheduler.

// ❌ async + semaphore — worker keeps background QoS; main (UI QoS) blocks on it
queue.async { result = loadAllStars(); semaphore.signal() }
semaphore.wait()

// ✅ queue.sync propagates the main thread's QoS to the worker (boosted to
//    user-interactive) — and load only what the first frame needs
queue.sync { firstScreenStars = loadStars(limit: 20) }   // ~20 visible rows, not 10,000
// remainder loads lazily in the background after first frame

Don't Pre-Warm Speculatively (WWDC19 423)

The demo's first frame took 951ms because cellForRowAt "cleverly" instantiated and cached a DetailViewController per row — 882ms of speculative pre-warming for screens the user might never open. Moving creation to didSelectRowAt fixed it. Measure, don't guess: profiling disproved the optimization the code was written around.

Lazy View Loading

// Bad — all tabs initialize their full view hierarchy at launch
TabView {
    HomeView()        // Heavy: fetches data, builds complex layout
    SearchView()      // Heavy: initializes search index
    ProfileView()     // Heavy: loads user data
}

// Good — use lazy containers, each tab builds only when selected
TabView {
    NavigationStack {
        HomeView()
    }
    .tabItem { Label("Home", systemImage: "house") }

    NavigationStack {
        SearchView()
    }
    .tabItem { Label("Search", systemImage: "magnifyingglass") }
}
// SwiftUI NavigationStack already lazy-loads destination views
// For custom containers, use LazyVStack instead of VStack

Reduce Initial View Complexity

// Bad — loading everything at once
struct ContentView: View {
    @State private var allItems: [Item] = []

    var body: some View {
        List(allItems) { item in
            ComplexItemView(item: item)
        }
        .onAppear {
            allItems = try! ModelContext(container).fetch(
                FetchDescriptor<Item>(sortBy: [SortDescriptor(\.date)])
            )
        }
    }
}

// Good — show skeleton immediately, load data async
struct ContentView: View {
    @State private var items: [Item]?

    var body: some View {
        Group {
            if let items {
                List(items) { item in
                    ItemRow(item: item)
                }
            } else {
                SkeletonListView() // Lightweight placeholder
            }
        }
        .task {
            items = await loadItems()
        }
    }
}

Database Migration at Launch

// Bad — blocking migration on main thread
let container = try ModelContainer(for: Item.self)
// If migration runs, this blocks until complete

// Good — show migration UI if needed
struct AppEntry: View {
    @State private var container: ModelContainer?
    @State private var isMigrating = false

    var body: some View {
        Group {
            if let container {
                ContentView()
                    .modelContainer(container)
            } else if isMigrating {
                MigrationProgressView()
            } else {
                ProgressView()
            }
        }
        .task {
            await setupContainer()
        }
    }

    private func setupContainer() async {
        // Check if migration needed
        if await needsMigration() {
            isMigrating = true
        }
        container = try? await Task.detached {
            try ModelContainer(for: Item.self)
        }.value
        isMigrating = false
    }
}

Measurement Discipline (WWDC19 423)

Launch numbers are only comparable under controlled conditions:

• Reboot the device and let it settle several minutes before measuring
• Kill network variance: Airplane Mode or mocked networking
• Pin iCloud state: fixed account/data, or signed out
• Use a Release build via the Profile scheme
• Measure warm launches (consistent); use consistent mock datasets (small + large)
• Keep a fixed device set that always includes the oldest supported device on the oldest supported OS
• Track longitudinally across the release cycle — regressions of 2–3ms compound

XCTApplicationLaunchMetric (CI Gate)

func testLaunchPerformance() {
    measure(metrics: [XCTApplicationLaunchMetric()]) {
        XCUIApplication().launch()
    }
}

One throwaway launch absorbs cold-launch variance, then 5 iterations by default with statistical output — CI-friendly and lower overhead than Instruments (WWDC19 423, WWDC21 10181). Set a baseline so regressions fail the test.

Measuring Launch Time in Code

Using os_signpost

import os

@main
struct MyApp: App {
    static let launchLog = OSLog(subsystem: Bundle.main.bundleIdentifier!, category: "Launch")
    static let launchSignpost = OSSignpostID(log: launchLog)

    init() {
        os_signpost(.begin, log: Self.launchLog, name: "AppLaunch", signpostID: Self.launchSignpost)
    }

    var body: some Scene {
        WindowGroup {
            ContentView()
                .onAppear {
                    os_signpost(.end, log: Self.launchLog, name: "AppLaunch", signpostID: Self.launchSignpost)
                }
        }
    }
}

Using CFAbsoluteTimeGetCurrent

// Quick and dirty launch measurement
@main
struct MyApp: App {
    static let launchStart = CFAbsoluteTimeGetCurrent()

    var body: some Scene {
        WindowGroup {
            ContentView()
                .onAppear {
                    let elapsed = CFAbsoluteTimeGetCurrent() - Self.launchStart
                    print("Launch time: \(String(format: "%.3f", elapsed))s")
                }
        }
    }
}

MetricKit Launch Metrics

Production launch time data from real users:

func didReceive(_ payloads: [MXMetricPayload]) {
    for payload in payloads {
        if let launch = payload.applicationLaunchMetrics {
            // Histogram of time-to-first-draw
            let histogram = launch.histogrammedTimeToFirstDraw
            for bucket in histogram.bucketEnumerator {
                guard let bucket = bucket as? MXHistogramBucket<UnitDuration> else { continue }
                print("[\(bucket.bucketStart) - \(bucket.bucketEnd)]: \(bucket.bucketCount) launches")
            }

            // Resume time histogram
            let resumeHistogram = launch.histogrammedResumeTime
            // Same enumeration pattern
        }
    }
}

The Xcode Organizer shows the same class of data aggregated: real-user launch-time histograms per app version/device over 24-hour windows from opted-in users — launch time is reported as average "time to first frame" across the last 16 versions (WWDC19 423, WWDC21 10181). Terminations also force a full cold launch next time, so watch the terminations metric alongside launch time (WWDC21 10181).

Launch Optimization Checklist

Pre-main

• Minimize dynamic frameworks (prefer static linking)
• No +load methods or static initializers (+load → +initialize; frameworks expose explicit setup APIs)
• Remove unused frameworks from Link Binary With Libraries
• Strip unused architectures in release builds
• No dlopen / NSBundle.load — hard-link dependencies so dyld3's warm-launch cache applies
• Deployment target ≥ iOS 13.4 (chained fixups / page-in linking); iOS 16 unlocks protocol-metadata precompute + retain/release convention

Post-main (App Init)

• Only essential setup in App.init() or AppDelegate (crash reporter only)
• Analytics, remote config, and prefetch deferred to .task {} after first frame
• No synchronous network calls at launch
• No blocking database migrations on main thread
• View controllers created in exactly one place (scene(_:willConnectTo:) OR didFinishLaunching, never both)
• No semaphore waits on async'd work (priority inversion) — use queue.sync for QoS propagation or async/await
• First frame fetches only first-frame data; no speculative pre-warming of unopened screens

First Frame

• Initial view is lightweight (skeleton/placeholder)
• Data loading is async with .task {}
• Heavy views (maps, web views, complex lists) lazy-loaded
• Images use thumbnails, not full resolution

Verification

• Measure with App Launch Instrument on oldest supported device (controlled conditions: reboot + settle, Airplane Mode, pinned iCloud, Release/Profile build)
• First frame < 400ms, measured on warm launches
• XCTApplicationLaunchMetric baseline set in CI
• No regressions after changes (compare Instruments traces)
• MetricKit / Organizer showing stable or improving launch times in production