Execute perf-record in a pod-in-cluster and pref-script in local and then generate a flame graph.

kperf.rb

#!/usr/bin/env ruby

require "json"

# https://github.com/brendangregg/FlameGraph
FG_SCRIPTS = raise "`FG_SCRIPTS` must be set by hand."

if ARGV.empty?
  $stderr.puts("Usage: ruby kperf.rb $POD [ $CONTAINER ] > out.svg")
  exit(-1)
end

pod = ARGV[0]
pod_spec = JSON.parse(`kubectl get pod "#{pod}" -o jsonpath='{.spec}'`)

cont = ARGV[1]
cont_spec =
  cont ? pod_spec["containers"].find { |e| e["name"] == cont } || raise("No container named '#{cont}'.")
       : pod_spec["containers"][0]

pid = nil

trap(:INT) {
  Process.kill("INT", pid)
}

$stderr.puts("kperf: Start profiling (Ctrl+C to stop)")

pid = spawn("kubectl exec -c '#{cont_spec['name']}' -it '#{pod}' -- perf record --call-graph dwarf -p 1 -o perf.data")
Process.waitpid(pid)

$stderr.puts("kperf: Start downloading 'perf.data'..")

pid = spawn("kubectl cp -c '#{cont_spec['name']}' '#{pod}':perf.data perf.data")
Process.waitpid(pid)

$stderr.puts("kperf: Start generating a flamegraph..")

exec("docker run -i -v $(pwd):/host --rm --entrypoint perf '#{cont_spec['image']}' script -i /host/perf.data | #{FG_SCRIPTS}/stackcollapse-perf.pl | #{FG_SCRIPTS}/flamegraph.pl")