Swift Performance Monitoring Best Practices
Swift applications need performance monitoring to ensure smooth user experiences on iOS, macOS, and server-side deployments.
Use signposts for Custom Instrumentation
import os
let logger = Logger(subsystem: "com.app", category: "performance")
let signposter = OSSignposter(logger: logger)
func loadDashboard() async throws -> DashboardData {
let state = signposter.beginInterval("loadDashboard")
defer { signposter.endInterval("loadDashboard", state) }
async let profile = fetchProfile()
async let stats = fetchStats()
async let notifications = fetchNotifications()
return try await DashboardData(
profile: profile,
stats: stats,
notifications: notifications
)
}View signpost data in Instruments' Points of Interest timeline.
Track Memory Usage
func reportMemoryUsage() {
var info = mach_task_basic_info()
var count = mach_msg_type_number_t(MemoryLayout<mach_task_basic_info>.size) / 4
let result = withUnsafeMutablePointer(to: &info) {
$0.withMemoryRebound(to: integer_t.self, capacity: Int(count)) {
task_info(mach_task_self_, task_flavor_t(MACH_TASK_BASIC_INFO), $0, &count)
}
}
if result == KERN_SUCCESS {
let usedMB = Double(info.resident_size) / 1024.0 / 1024.0
logger.info("Memory usage: \(usedMB, format: .fixed(precision: 1))MB")
}
}Network Performance
class NetworkMonitor: NSObject, URLSessionTaskDelegate {
func urlSession(_ session: URLSession, task: URLSessionTask,
didFinishCollecting metrics: URLSessionTaskMetrics) {
for metric in metrics.transactionMetrics {
let dns = metric.domainLookupEndDate?.timeIntervalSince(
metric.domainLookupStartDate ?? Date()) ?? 0
let connect = metric.connectEndDate?.timeIntervalSince(
metric.connectStartDate ?? Date()) ?? 0
let response = metric.responseEndDate?.timeIntervalSince(
metric.requestStartDate ?? Date()) ?? 0
logger.info("Network: dns=\(dns)s connect=\(connect)s total=\(response)s")
}
}
}Key Metrics
- App launch time — cold and warm starts
- Frame drops — CADisplayLink monitoring for jank
- Memory warnings — track
didReceiveMemoryWarningfrequency - Network latency — per-endpoint timing
- Disk I/O — large reads/writes block the main thread
Crash and Error Monitoring
Integrate Bugsly to capture crashes, hangs, and non-fatal errors in production. Swift's crash reports need symbolication to be useful — Bugsly handles this automatically, giving you readable stack traces from user devices.
Try Bugsly Free
AI-powered error tracking that explains your bugs. Set up in 2 minutes, free forever for small projects.
Get Started FreeRelated Articles
Nuxt Production Best Practices
Essential Nuxt best practices for production covering SSR configuration, caching strategies, security headers, and deployment optimization.
Read moreFastAPI Logging Best Practices
Set up production-ready logging in FastAPI with structured output, request tracing, middleware integration, and performance monitoring.
Read moreKotlin Production Best Practices
Essential Kotlin best practices for production including null safety, coroutine patterns, sealed classes for errors, and testing strategies.
Read moreLog Levels Explained: DEBUG, INFO, WARN, ERROR — When to Use Each
A practical guide to choosing the right log level — with framework-specific mappings for Python, Java, Node.js, and Go.
Read more