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Profiling Dendrite
If you are running into problems with Dendrite using excessive resources (e.g. CPU or RAM) then you can use the profiler to work out what is happening.
Dendrite contains an embedded profiler called pprof, which is a part of the standard Go toolchain.
Enable the profiler
To enable the profiler, start Dendrite with the PPROFLISTEN environment variable. This variable specifies which address and port to listen on, e.g.
PPROFLISTEN=localhost:65432 ./bin/dendrite-monolith-server ...
If pprof has been enabled successfully, a log line at startup will show that pprof is listening:
WARN[2020-12-03T13:32:33.669405000Z] [/Users/neilalexander/Desktop/dendrite/internal/log.go:87] SetupPprof
Starting pprof on localhost:65432
All examples from this point forward assume PPROFLISTEN=localhost:65432 but you may need to adjust as necessary for your setup.
Profiling CPU usage
To examine where CPU time is going, you can call the profile endpoint:
http://localhost:65432/debug/pprof/profile?seconds=30
The profile will run for the specified number of seconds and then will produce a result.
If you have Go installed and want to explore the profile, you can invoke go tool pprof to start the profile directly. The -http= parameter will instruct go tool pprof to start a web server providing a view of the captured profile:
go tool pprof -http=localhost:23456 http://localhost:65432/debug/pprof/profile?seconds=30
You can then visit http://localhost:23456 in your web browser to see a visual representation of the profile. Particularly usefully, in the "View" menu, you can select "Flame Graph" to see a proportional interactive graph of CPU usage.
If you don't have the Go tools installed but just want to capture the profile to send to someone else, you can instead use curl to download the profiler results:
curl -O http://localhost:65432/debug/pprof/profile?seconds=30
This will block for the specified number of seconds, capturing information about what Dendrite is doing, and then produces a profile file, which you can send onward.
Profiling memory usage
To examine where memory usage is going, you can call the heap endpoint:
http://localhost:65432/debug/pprof/heap
The profile will return almost instantly.
If you have Go installed and want to explore the profile, you can invoke go tool pprof to start the profile directly. The -http= parameter will instruct go tool pprof to start a web server providing a view of the captured profile:
go tool pprof -http=localhost:23456 http://localhost:65432/debug/pprof/heap
You can then visit http://localhost:23456 in your web browser to see a visual representation of the profile. The "Sample" menu lets you select between four different memory profiles:
inuse_space: Shows how much actual heap memory is allocated per function (this is generally the most useful profile when diagnosing high memory usage)inuse_objects: Shows how many heap objects are allocated per functionalloc_space: Shows how much memory has been allocated per function (although that memory may have since been deallocated)alloc_objects: Shows how many allocations have been made per function (although that memory may have since been deallocated)
Also in the "View" menu, you can select "Flame Graph" to see a proportional interactive graph of the memory usage.
If you don't have the Go tools installed but just want to capture the profile to send to someone else, you can instead use curl to download the profiler results:
curl -O http://localhost:65432/debug/pprof/heap
This will almost instantly produce a heap file, which you can send onward.