Flame graphs are a way of visualizing CPU time spent in functions. They can help you pin down where you spend too much time doing synchronous operations.
You might have heard creating a flame graph for Node.js is difficult, but that's not true (anymore). Solaris vms are no longer needed for flame graphs!
Flame graphs are generated from
If you want a single step that produces a flame graph locally, try 0x
For diagnosing production deployments, read these notes: 0x production servers
The purpose of this guide is to show steps involved in creating a flame graph and keep you in control of each step.
If you want to understand each step better, take a look at the sections that follow where we go into more detail.
Now let's get to work.
perf(usually available through the linux-tools-common package if not already installed)
- try running
perf- it might complain about missing kernel modules, install them too
- run node with perf enabled (see perf output issues for tips specific to Node.js versions)
perf record -e cycles:u -g -- node --perf-basic-prof app.js
- disregard warnings unless they're saying you can't run perf due to missing packages; you may get some warnings about not being able to access kernel module samples which you're not after anyway.
perf script > perfs.outto generate the data file you'll visualize in a moment. It's useful to apply some cleanup for a more readable graph
- install stackvis if not yet installed
npm i -g stackvis
stackvis perf < perfs.out > flamegraph.htm
Now open the flame graph file in your favorite browser and watch it burn. It's color-coded so you can focus on the most saturated orange bars first. They're likely to represent CPU heavy functions.
Worth mentioning - if you click an element of a flame graph a zoom-in of its surroundings will get displayed above the graph.
This is great for recording flame graph data from an already running process that you don't want to interrupt. Imagine a production process with a hard to reproduce issue.
perf record -F99 -p `pgrep -n node` -g -- sleep 3
Wait, what is that
sleep 3 for? It's there to keep the perf running - despite
-p option pointing to a different pid, the command needs to be executed on a process and end with it.
perf runs for the life of the command you pass to it, whether or not you're actually profiling that command.
sleep 3 ensures that perf runs for 3 seconds.
-F (profiling frequency) set to 99? It's a reasonable default. You can adjust if you want.
-F99 tells perf to take 99 samples per second, for more precision increase the value. Lower values should produce less output with less precise results. Precision you need depends on how long your CPU intensive functions really run. If you're looking for the reason of a noticeable slowdown, 99 frames per second should be more than enough.
After you get that 3 second perf record, proceed with generating the flame graph with the last two steps from above.
Usually you just want to look at the performance of your own calls, so filtering out Node.js and V8 internal functions can make the graph much easier to read. You can clean up your perf file with:
sed -i \ -e "/( __libc_start| LazyCompile | v8::internal::| Builtin:| Stub:| LoadIC:|\[unknown\]| LoadPolymorphicIC:)/d" \ -e 's/ LazyCompile:[*~]\?/ /' \ perfs.out
If you read your flame graph and it seems odd, as if something is missing in the key function taking up most time, try generating your flame graph without the filters - maybe you got a rare case of an issue with Node.js itself.
--perf-basic-prof-only-functions produces less output, so it's the option with least overhead.
Well, without these options you'll still get a flame graph, but with most bars labeled
The result is you might not get your function names right in the flame graph.
ByteCodeHandler: where you'd expect function names.
0x has some mitigations for that built in.
For details see:
Node.js 10.x addresses the issue with Turbofan using the
If you're seeing labels looking like this
it means the Linux perf you're using was not compiled with demangle support, see https://bugs.launchpad.net/ubuntu/+source/linux/+bug/1396654 for example
Practice capturing flame graphs yourself with a flame graph exercise!