Ios performance engineering
Skill wei18/apple-dev-skills/apple-dev-skills/skills/ios-performance-engineering
Measure and fix iOS/macOS performance — Instruments (Time Profiler, Allocations, SwiftUI instrument, Hangs), os_signpost, MetricKit field telemetry, XCTMetric baselines, launch-time optimisation, memory footprint, binary size. Invoke when diagnosing slowness/hitches/high memory, setting up CI perf baselines, wiring MetricKit, or asking "why is my app slow / using too much memory / large".From its SKILL.md
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iOS Performance Engineering
When to invoke
- Diagnosing UI slowness, scroll hitches, or app hangs.
- Investigating high memory usage, leaks, or large binary size.
- Wiring MetricKit to receive field performance data from real devices.
- Setting up
XCTMetric/measure {}baselines in CI. - Deciding whether to move work off
@MainActorand how to do it safely. - Evaluating launch time before a release.
Instruments — the primary measurement tool
Never guess at a performance problem; profile first. Instruments ships with Xcode. Key templates:
Time Profiler — samples the call stack at ~1 kHz. Reveals which functions consume CPU time. After recording, invert the call tree and hide system libraries to surface your own hot paths. A function taking >5 ms on the main thread in an interactive path is a candidate for offloading.
Allocations — tracks every heap allocation. Use the "Generation" feature: take a snapshot before an action, perform the action repeatedly, take another snapshot, and diff. Any allocation that grew unboundedly across generations is a leak or an accumulation bug. The "Leaks" instrument detects reference cycles automatically but misses logical leaks (objects kept alive longer than needed).
SwiftUI instrument — records View body invocation counts, @State change propagation, and diffing cost. Available from Xcode 15+. A body that fires more than expected usually means a dependency is too coarse (e.g. observing the whole model when only one field is needed). The instrument shows which property change triggered each body re-render.
Hangs instrument (Xcode 14+) — captures main-thread spins longer than a configurable threshold (default 250 ms). Apple classifies blocks 250–500 ms as micro-hangs and ≥500 ms as full hangs. Pairs with the App Launch template for pre-first-frame blocking. The system also generates MXHangDiagnostic on-device (see MetricKit below).
Hitches — a hitch occurs when a frame takes longer than one vsync interval to deliver, causing a visual stutter. On 60 Hz displays the budget is ~16.67 ms; on ProMotion (120 Hz) it halves to ~8.33 ms. Use the Core Animation instrument to see committed frames and dropped frames. The hitch rate (ms of hitch per second of scrolling) is the standard metric: <5 ms/s is good; 5–10 ms/s is concerning (user notices interruptions); >10 ms/s is critical (greatly impacts UX) — per WWDC 2020 session 10077.
os_signpost — annotate your own intervals
import os
let log = OSLog(subsystem: "com.example.MyApp", category: .pointsOfInterest)
let id = OSSignpostID(log: log)
os_signpost(.begin, log: log, name: "ImageDecode", signpostID: id)
let image = decodeImage(data)
os_signpost(.end, log: log, name: "ImageDecode", signpostID: id)
Signpost intervals appear in the Instruments timeline as coloured spans. Use .event for instantaneous markers (user taps, cache misses). Prefer OSSignposter (iOS 15+/macOS 12+, introduced WWDC 2021; Swift-only wrapper over C os_signpost) from the os framework — it supports structured metadata:
let signposter = OSSignposter(subsystem: "com.example.MyApp", category: "Render")
let state = signposter.beginInterval("TileRender", id: signposter.makeSignpostID())
// ... work ...
signposter.endInterval("TileRender", state)
xctrace — Instruments from CI
xctrace record \
--template "Time Profiler" \
--launch -- /path/to/MyApp.app \
--output trace.xctrace \
--time-limit 30s
xctrace can drive any built-in or custom Instruments template headlessly and export the trace as a .xctrace bundle. Post-process with xctrace export to pull out human-readable XML. Wire this into a CI step on a dedicated Mac runner to catch regressions before they reach users.
Hangs and hitches
The system classifies a main-thread block of 250 ms or more as a hang and surfaces it in the Organizer → Hang Reports (Xcode 14+) and via MetricKit's MXHangDiagnosticPayload. The scroll hitch budget depends on display refresh rate (see above).
Moving work off @MainActor:
// Wrong — blocks the main thread
func loadData() {
let json = try! Data(contentsOf: remoteURL) // network I/O on main thread
items = try! JSONDecoder().decode([Item].self, from: json)
}
// Right — async, main actor only for the final UI update
func loadData() async throws {
let json = try await URLSession.shared.data(from: remoteURL).0
let decoded = try JSONDecoder().decode([Item].self, from: json)
await MainActor.run { items = decoded }
}
For CPU-heavy processing (image decoding, compression, sorting large arrays), use Task.detached(priority: .userInitiated) or dispatch to a background Actor. Never use DispatchQueue.global().async in new Swift 6 code — prefer structured concurrency.
One-shot bootstrapping on first appearance belongs in .task — the correct Apple-recommended modifier for async work tied to view lifetime. Verify async-lifecycle behavior on your toolchain if you encounter unexpected issues.
Launch time
Launch time splits into two phases:
Pre-main (dyld) — loading and linking dylibs before main() runs. Minimise by: keeping the embedded dylib count low (prefer static libraries for non-system frameworks), avoiding +load methods, and not registering large numbers of @objc classes at startup. The App Launch Instruments template shows the pre-main timeline. Target: under 400 ms on a cold launch on the slowest supported device.
Post-main / first frame — everything from application(_:didFinishLaunchingWithOptions:) through the first committed frame. Defer every initialisation that is not required to display the initial screen. CloudKit containers, network prefetches, and analytics SDKs should be lazy. Measure with the App Launch template and the os_signpost .begin/.end around your own startup phases.
Common traps: eager CKContainer.default() on the main thread (hangs until entitlement check completes), synchronous keychain reads at app start, and large SQLite PRAGMA operations before the first view renders.
Memory
Footprint vs leaks: Instruments Allocations shows the heap; use vmmap or the Memory Debugger in Xcode to see the full virtual memory map (dirty pages, compressed pages, mapped files). The OS terminates apps that exceed their footprint budget silently — JETSAM_REASON_HIGH_WATER_MARK in the crash log. Reduce by:
- Image downsampling: never decode a 4K image to display it at 100 pt. Use
ImageIOwithkCGImageSourceThumbnailMaxPixelSizeorUIGraphicsImageRendererto decode at display resolution.
func downsample(imageAt url: URL, to pointSize: CGSize, scale: CGFloat) -> UIImage {
let options: [CFString: Any] = [
kCGImageSourceShouldCacheImmediately: false,
kCGImageSourceShouldCache: false
]
let src = CGImageSourceCreateWithURL(url as CFURL, options as CFDictionary)!
let maxDim = max(pointSize.width, pointSize.height) * scale
let thumbOptions: [CFString: Any] = [
kCGImageSourceCreateThumbnailWithTransform: true,
kCGImageSourceCreateThumbnailFromImageAlways: true,
kCGImageSourceThumbnailMaxPixelSize: maxDim
]
let cgImage = CGImageSourceCreateThumbnailAtIndex(src, 0, thumbOptions as CFDictionary)!
return UIImage(cgImage: cgImage)
}
autoreleasepoolin tight loops that allocate many Objective-C objects (e.g. iteratingNSManagedObjectfetches, callingUIImage(named:)in a loop). The pool drains at the end of eachautoreleasepool { }block rather than at the runloop turn boundary.- Retain cycles:
[weak self]in closures stored onself;weak var delegatein delegation patterns. The Leaks instrument and the Memory Graph Debugger (product menu → Debug Memory Graph) visualise the reference graph and highlight cycles in red.
Binary size
Large binaries increase download time and App Store review scrutiny. Primary levers:
- Dead code stripping (
DEAD_CODE_STRIPPING = YESin Xcode build settings, default on for Release). Removes unreachable functions and data sections. -Osize(SWIFT_OPTIMIZATION_LEVEL = -Osize): optimises for binary size rather than speed. Typically 5–15% smaller than-Owith negligible runtime impact for most app code.- Asset catalog / app thinning: use asset catalog image sets with
@1x/@2x/@3xvariants and device-specific slices. The App Store strips variants irrelevant to the downloading device. Avoid embedding full-resolution assets in the bundle for cases where a downsampled or streamed version suffices. - Link Map + Organizer: use the Link Map (Build Settings: Write Link Map File = YES) and the Xcode Organizer's App Size report to identify which symbols contribute most to the binary. Tools such as Bloaty or the
nm/sizecommands can post-process the link map to locate unexpectedly large third-party frameworks or generated code. - Avoid shipping unused localisation bundles from third-party SDKs: set
SWIFT_PACKAGE_RESOURCE_BUNDLE_DEDUPLICATE = YESand review resource bundle sizes after each SDK update.
MetricKit — field performance telemetry
MetricKit delivers on-device aggregated performance metrics to your app once per day (and immediately for diagnostic payloads on device disconnect from Xcode):
import MetricKit
final class MetricKitReceiver: NSObject, MXMetricManagerSubscriber {
func didReceive(_ payloads: [MXMetricPayload]) {
for payload in payloads {
// CPU time, memory, disk, network, display — aggregated over 24 h
let cpuTime = payload.cpuMetrics?.cumulativeCPUTime
let avgMemory = payload.memoryMetrics?.averageSuspendedMemory
// Forward to your telemetry sink
}
}
func didReceive(_ payloads: [MXDiagnosticPayload]) {
for payload in payloads {
// MXHangDiagnostic, MXCrashDiagnostic, MXCPUExceptionDiagnostic
let hangs = payload.hangDiagnostics // call trees for hang events
// Persist or upload for analysis
}
}
}
// Register at app start — one call, lives for the app lifetime
MXMetricManager.shared.add(receiver)
MetricKit data reflects real user conditions (actual device, network, battery state), making it the authoritative source for field performance signals. Key metric classes:
| Class | What it measures |
|---|---|
MXCPUMetrics | Cumulative CPU time (user + system) |
MXMemoryMetrics | Peak and average memory, average suspended memory |
MXDisplayMetric | Average pixel luminance (not hitch rate — use MXAnimationMetric — scrollHitchTimeRatio: ratio of hitch time while scrolling (field-measured)) |
MXDiskIOMetrics | Cumulative logical write bytes |
MXHangDiagnostic | Call tree for a main-thread hang > 250 ms |
MXCrashDiagnostic | Crash reason + call tree |
MXCPUExceptionDiagnostic | CPU runaway above system threshold |
Wire MetricKit as a sink in your telemetry facade (per telemetry-facade-pattern) — a MetricKitSink that subscribes to MXMetricManager.shared and broadcasts payloads as TelemetryEvent instances. This keeps MetricKit wiring out of AppDelegate and testable via protocol injection. Note that MetricKit complements but does not replace the analytics tracking covered in apple-three-piece-analytics: MetricKit is system-generated aggregate performance data, not user behaviour events.
XCTMetric and measure {} baselines in CI
func testScrollPerformance() {
let app = XCUIApplication()
app.launch()
measure(metrics: [XCTOSSignpostMetric.scrollDecelerationMetric,
XCTMemoryMetric(application: app),
XCTCPUMetric(application: app)]) {
// simulate the action
app.swipeUp()
}
}
measure {} runs the block 5 times (by default) and records the mean. On first run, set the baseline via the inline editor in Xcode. Subsequent runs fail if the result exceeds baseline * (1 + maxStandardDeviations) — configurable per metric. Commit baselines in .xcbaseline files alongside the test file.
For server-side CI (where a physical display is unavailable), use XCTCPUMetric and XCTMemoryMetric in unit tests that exercise logic without UIKit rendering. UI performance metrics require a simulator or device with an active display session.
Verification checklist
- Profile with Instruments before claiming a fix; never tune by guessing.
- Time Profiler run completed; hot paths on the main thread identified and either offloaded or bounded.
- Allocations generation diff shows no unbounded growth across repeated user actions.
- SwiftUI instrument checked for unexpected body re-render counts on the primary screen.
os_signpostintervals added around any operation expected to take > 16 ms.MXMetricManagerSubscriberregistered in the composition root; payloads forwarded to the telemetry sink.XCTMetricbaseline committed for the primary performance-sensitive test; CI fails on regression.- No synchronous network or file I/O on the main thread (audited via Thread Sanitizer and code review).
- Image assets decoded at display resolution, not source resolution.
- Binary size measured with
-Osizebefore each major release; asset catalog slices verified.
Related skills
telemetry-facade-pattern: wireMetricKitSinkas one sink in the fan-out facade; keepMXMetricManagerSubscriberregistration out ofAppDelegate.apple-three-piece-analytics: MetricKit covers system-level performance telemetry; the three-piece stack covers user behaviour and business events — they are complementary, not overlapping.swift6-concurrency: moving work off@MainActorcorrectly requires understanding actor isolation,Task.detached, andSendableconstraints — the primary tool for eliminating main-thread hangs.swiftui-expert(aggregated external): for the SwiftUI body-re-render slice specifically, it ships an Instruments.traceanalysis toolchain — prefer it for that profiling. This skill owns the broader surface (Time Profiler / Allocations / hangs / launch / memory / binary size / MetricKit / XCTMetric).
What ships with it
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Said here and by no other author read
- Profile the app before fixing performance problems
- Move heavy work off the main thread
- Annotate custom intervals using os_signpost
- Run xctrace in CI to catch regressions
- Wrap tight allocation loops in autoreleasepool
- Enable dead code stripping
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.