How We Reduced iOS App Launch Time by 60%
Source: Dev.to
Introduction
App launch time is your first impression. If your app takes more than 2–3 seconds to open, users notice; at 5 seconds they leave. We faced this on a production iOS app where cold launch time hovered around 4.8–5.2 seconds on mid‑range devices. After a focused optimization sprint we reduced launch time by ≈ 60 % (down to ~2 seconds).
Step 1 — Measure Before You Optimize
Never guess—measure. We used:
- Xcode Instruments → Time Profiler
- App Launch Metric (Xcode Organizer)
- DYLD_PRINT_STATISTICS
- Custom logging for
application(_:didFinishLaunchingWithOptions:)
Baseline Numbers
| Metric | Before |
|---|---|
| Cold launch | 5.1 s |
| Warm launch | 2.7 s |
| Main thread blocked | 3.4 s |
Insight – Most of the time was spent before the first frame rendered, meaning startup work was blocking the main thread.
Step 2 — Find What Blocks the Main Thread
Problems we discovered:
- Heavy dependency injection at launch
- Database migration during startup
- Synchronous network calls
- Large storyboard initialization
- Too many dynamic frameworks
All happening before the first screen.
Optimizations That Gave Us 60 % Improvement
1. Defer Non‑Critical Work (Biggest Win)
Before
func application(_ application: UIApplication,
didFinishLaunchingWithOptions launchOptions: [UIApplication.LaunchOptionsKey: Any]?) -> Bool {
setupAnalytics()
migrateDatabase()
preloadImages()
fetchRemoteConfig()
return true
}
After
DispatchQueue.global(qos: .background).async {
self.setupAnalytics()
self.migrateDatabase()
self.preloadImages()
self.fetchRemoteConfig()
}
// Or, even later:
DispatchQueue.main.asyncAfter(deadline: .now() + 1) {
// non‑critical work
}
Result – Saved ≈ 1.8 seconds immediately.
2. Lazy Load Dependencies
Before
let networkManager = NetworkManager()
let cacheManager = CacheManager()
let analytics = Analytics()
After
lazy var networkManager = NetworkManager()
Result – Saved ≈ 400 ms (cost only incurred when the feature is used).
3. Reduce Storyboard Complexity
Initial storyboard contained 20+ view controllers, heavy Auto Layout, custom fonts, and embedded navigation.
Fixes
- Split the storyboard into smaller pieces.
- Use a lightweight launch screen.
- Move heavy views to programmatic UI.
Result – Saved ≈ 300–500 ms.
4. Optimize Dynamic Frameworks
Each dynamic framework adds launch overhead (dyld linking, symbol resolution). We had 18 frameworks.
Actions
- Merged small frameworks.
- Converted some to static libraries.
- Removed unused pods.
Result – Saved ≈ 700 ms.
5. Move Database Migration Off Startup
We were migrating SQLite on every launch.
Fix
- Run migration only if the schema version changed.
- Perform migration after the first screen appears, on a background queue.
Result – Saved ≈ 600 ms.
6. Image & Asset Optimization
Problems
- Large PNGs and unnecessary @3x assets.
- Images preloaded on launch.
Fixes
- Convert assets to WebP/HEIF.
- Load images on demand.
- Remove preloading.
Result – Saved ≈ 200–300 ms.
Final Metrics
| Metric | Before | After |
|---|---|---|
| Cold launch | 5.1 s | 2.0 s |
| Warm launch | 2.7 s | 1.1 s |
| Main thread blocked | 3.4 s | 0.9 s |
Total improvement: ≈ 60 % faster launch.
Key Lessons Learned
Do
- Defer everything non‑critical.
- Lazy‑load dependencies.
- Measure with Instruments.
- Minimize dynamic frameworks.
- Keep the launch screen lightweight.
Don’t
- Call APIs on startup.
- Migrate the database on the main thread.
- Eagerly initialize all services.
- Load heavy storyboards.
- Block the main thread.
Quick Startup Optimization Checklist
- Use a lightweight launch screen.
- Lazy‑load services.
- Remove unnecessary frameworks.
- Defer analytics initialization.
- Perform DB work in the background.
- Avoid heavy DI containers at launch.
- Profile regularly with Instruments.
Final Thoughts
Launch time directly impacts:
- Retention
- Ratings
- Perceived quality
- Conversions
Users judge your app in seconds—literally. Treat startup performance as a feature, not an afterthought. By smartly deferring work, lazy‑loading, and removing bloat, we achieved a 60 % improvement without changing core functionality.