Xavier F. Gouchet
Senior Software Engineer
at Datadog
@xgouchet / @datadoghq
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Introduction
A few words about performance
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Mobile app
performance is still
critical today
- Low end devices
- Slow networks
- Short attention span
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@priscilladupreez
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Performance
(like Android)
are fragmented
If you develop on a Pixel 6, make sure your app also
works correctly on a Samsung Galaxy A10 (2019)
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Performance
must be measured
You can’t just base your
roadmap decision on
“a hunch”
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@youngprodigy3
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User will tell you it feels slow
Measurements will tell you what
part exactly is slow.
#MeasurementsMatter
Changes must be measured
Measurements will tell you how
much your PR improves (or
degrades) your feature’s
performance
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Making sure the code works
- Unit Testing
- Instrumented Testing
- Manual Testing
-
- …
In your toolbox
Making sure it works fast and
efficiently
- ???
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Developer Tools
Get a snapshot of your immediate performance
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Immediate snapshot
Get a full view of:
- network
- cpu
- heap
- rendering
- …
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@kmuza
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Tools
Android Studio Profiler Systrace Perfetto
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Android Profiler
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Android Profiler
Touch
Activities
Fragments
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Android Profiler
CPU usage
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Android Profiler
Memory usage
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Android Profiler
Network usage
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Android Profiler
Battery impact
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Android Profiler
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Launching systrace
$ systrace.py
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Launching systrace
$ systrace.py
Starting tracing (stop with enter)
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Pros 👍
▫ (Almost) no setup required
▫ Get full system state info
▫ Controlled scenario and
environment
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Profiler / Systrace / Perfetto
Cons 👎
▫ Performance measurements
are skewed
▫ Needs manual trigger
▫ Complex and dense UI/UX
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When should you use it ?
▫ When you have a specific performance issue
▫ When you want to optimize a specific part of the code
▫ To debug a tricky algorithm (nested loops, concurrency)
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Going Further
▫ Capture systrace from the device (API 28+)
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Capturing traces from the developer settings
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Benchmark
Standardized performance measurement
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Benchmark Overview
Measure timed performances
of specific operations
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@veri_ivanova
@RunWith(AndroidJUnit4::class)
class BenchmarkTest {
@get:Rule
val benchmarkRule = BenchmarkRule()
// …
}
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Benchmark Test Class
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@RunWith(AndroidJUnit4::class)
class BenchmarkTest {
@get:Rule
val benchmarkRule = BenchmarkRule()
// …
}
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Benchmark Test Class
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@RunWith(AndroidJUnit4::class)
class BenchmarkTest {
@get:Rule
val benchmarkRule = BenchmarkRule()
// …
}
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Benchmark Test Class
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@Test
fun benchmarkSomeWork() {
benchmarkRule.measureRepeated {
doSomeWork()
}
}
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Benchmark Test Function
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@Test
fun benchmarkSomeWork() {
benchmarkRule.measureRepeated {
doSomeWork()
}
}
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Benchmark Test Function
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@Test
fun benchmarkSomeWork() {
benchmarkRule.measureRepeated {
doSomeWork()
}
}
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Benchmark Test Function
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@Test
fun benchmarkSomeWork() {
benchmarkRule.measureRepeated {
doSomeWork()
}
}
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Benchmark Test Function
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@Test
fun benchmarkSomeWork() {
benchmarkRule.measureRepeated {
cleanState()
val data = createData()
doSomeWork(data)
}
}
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Benchmark Test Function
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@Test
fun benchmarkSomeWork() {
benchmarkRule.measureRepeated {
runWithTimingDisabled { cleanState() }
val data = runWithTimingDisabled { createData() }
doSomeWork(data)
}
}
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Benchmark Test Function
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$ gradlew :benchmark_module:connectedCheck
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Run the Benchmark
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▫ Stored in a JSON file
▫ Full timing information in nanoseconds
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Benchmark Results
Running Benchmark in the CI
▫ Emulators are unstable, use real devices
▫ Needs some tweaks in your gradle config
▫ Use the JSON to:
- Graph the evolution of performance
- Fail if the measurements exceed a threshold
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Pros 👍
▫ Accurate*, reliable and
consistent
▫ Measure just what you want
▫ Can be as high or low level as
needed
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Jetpack Benchmark
Cons 👎
▫ *Needs to be ran on a real
device
▫ The feature to be tested
must be repeatable and
called from code
▫ Takes a long time in CI
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When should you use it ?
▫ Monitor critical parts of your logic in CI
▫ When refactoring a specific feature
▫ When writing code executed on the main thread
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▫ Official Gradle plugin to lock the CPU clocks (root)
▫ Use CI script to fail on high measurements
Going Further
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Real User Monitoring
Live performance from the trenches
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What about the real
users?
Get performance and runtime
information from the
production environment
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@robin_rednine
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Tools
Real User Monitoring Error Tracking Android Vitals
Pros 👍
▫ Real data
- real use cases
- real devices
- real network conditions
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App Performance Monitoring
Cons 👎
▫ Need large enough user base
to have relevant data
▫ Can’t measure everything
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When should you use it ?
▫ Monitor key aspects of your app in the wild
▫ Understand how performance and crashes impacts
your users’ journey
▫ A/B testing / feature flags analytics
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Going Further
▫ Library is Open Source on GitHub
▫ Also provides Logging and Tracing
▫ More features coming soon…
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Wrapping up
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Key takeaways
“Measure twice,
cut once.”
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Choose the relevant
tool to your use case.
Always analyse your
measurements before
taking action.
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Thank You!
Any questions?
▫ @xgouchet
▫ @datadoghq
@theunsteady5
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CREDITS
Special thanks to all the people who made and released
these awesome resources for free:
▫ Presentation template by SlidesCarnival
▫ Photographs from Unsplash
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