Kotlin/Native Build Performance
Turn "the iOS build is slow" into a measured diagnosis and a small set of safe fixes. Two rules apply throughout:
- Never trade away required release behavior. A faster local loop must not change what CI publishes.
- Measure before and after with the same command and the same build state. An unmeasured fix is a guess.
Step 0: Classify the Slow Scenario
Establish four facts before editing anything: where (local or CI), what (debug feedback loop or release/distribution artifact), state (first build, clean, warm, or no-op), and phase (which tasks dominate the log). Then match the dominant symptom:
Step 1: Audit and Measure
-
Run the static audit from the project root:
It is read-only and prints
file:linefindings (disabled caches, broad local tasks,transitiveExport, broad KSP configuration, missing CI.konancache), each pointing at the reference file with the fix. Findings are leads, not verdicts — confirm each against project policy. -
Find the command the user actually waits for: a script, a CI step, or the Gradle invocation inside an Xcode build phase. Optimize that command, not a task you picked yourself.
-
Run it twice when practical. The first build downloads Kotlin/Native components and fills caches; only the second and later runs are representative. Attribute time per task before blaming the compiler:
Gradle's
--scanor--profilework too. -
If you cannot run the build (no macOS host, no Xcode), analyze logs, build scans, or checked-in metrics instead — and state explicitly that the conclusion is static.
Step 2: Fix in Safe Order
Apply fixes one at a time, re-measuring as you go:
- Restore healthy defaults — remove cache/daemon workarounds, enable
Gradle build and configuration caches, keep
~/.konanwarm in CI, update Kotlin: references/caching-and-gradle.md [blocked] - Build only what the feedback loop needs — one specific task per loop, correct integration method, justified target matrix: references/artifacts-and-targets.md [blocked]
- Cut export and generated-code cost — drop
transitiveExport, narrowexport(...), scope KSP work to the native compilations that need it: references/exports-and-generated-code.md [blocked] - Experimental switches last, with the user's agreement: references/experimental.md [blocked]
Worked Example
A developer on an Apple Silicon Mac complains that "every shared-module
change costs 12 minutes". Their loop runs ./gradlew :shared:assembleXCFramework.
A build scan of the second (warm) run shows:
Reasoning chain:
- The loop is local + debug + warm, but ~690s goes to
linkRelease*— release linking is an order of magnitude slower than debug and only CI needs it. Replace the local command with:shared:linkDebugFrameworkIosSimulatorArm64(or the Xcode embed task if Xcode drives the build). (artifacts-and-targets) - All
iosX64work serves Intel simulators; ask whether the team still supports them before removing the target. (artifacts-and-targets) - 64s of configuration on every run disappears behind
org.gradle.configuration-cache=trueonce trialed. (caching-and-gradle) - Expected loop after the change: ~40s compile + ~40s link on warm builds — confirm by re-running the new command twice and comparing.
- CI keeps
assembleXCFrameworkuntouched; note that explicitly in the report.
Verify
- Re-run the exact baseline command; compare warm build against warm build, not warm against cold.
- Second run with the configuration cache reports it is being reused.
- The local development log no longer contains
linkRelease*,*ReleaseXCFramework, or removed generator tasks. - CI still produces every required release artifact, unchanged.
- Tests pass and the app still runs from Xcode.
-
scripts/audit-native-build.shreports no findings you have not consciously accepted and documented.
Report Your Changes
Close with a short performance note:
- The slow scenario (local/CI, debug/release, cold/warm) and the measured evidence — or a statement that the analysis was static.
- Each change, and why it is safe for release behavior.
- The before/after commands the user can run to confirm the win.
- Remaining tradeoffs: experimental flags enabled, targets removed under a policy assumption, worker limits, or generated-code work deferred.
- Links to the relevant official documentation below.


