kubernetes/test/integration/scheduler_perf
2019-12-19 09:08:11 +08:00
..
config Define workloads specs by YAML 2019-12-19 09:08:11 +08:00
BUILD Define workloads specs by YAML 2019-12-19 09:08:11 +08:00
main_test.go use testmain in integration tests 2017-07-12 17:34:55 -07:00
OWNERS Updated OWNERS files to include link to docs 2019-02-04 22:33:12 +01:00
README.md generate files before scheduler perf 2017-08-22 16:40:16 +08:00
scheduler_bench_test.go Fix inter-pod affinity scheduler benchmarks 2019-12-10 10:00:28 -05:00
scheduler_perf_test.go Define workloads specs by YAML 2019-12-19 09:08:11 +08:00
scheduler_perf_types.go # This is a combination of 2 commits. 2017-07-19 00:28:40 -04:00
scheduler_test.go fix: scheduler perf test with pod informer 2019-10-15 13:54:45 +08:00
test-performance.sh fix shellcheck in test/integration/... and test/kubemark/... 2019-02-18 01:16:39 -05:00
util.go fix: scheduler perf test with pod informer 2019-10-15 13:54:45 +08:00

Scheduler Performance Test

Motivation

We already have a performance testing system -- Kubemark. However, Kubemark requires setting up and bootstrapping a whole cluster, which takes a lot of time.

We want to have a standard way to reproduce scheduling latency metrics result and benchmark scheduler as simple and fast as possible. We have the following goals:

  • Save time on testing
    • The test and benchmark can be run in a single box. We only set up components necessary to scheduling without booting up a cluster.
  • Profiling runtime metrics to find out bottleneck
    • Write scheduler integration test but focus on performance measurement. Take advantage of go profiling tools and collect fine-grained metrics, like cpu-profiling, memory-profiling and block-profiling.
  • Reproduce test result easily
    • We want to have a known place to do the performance related test for scheduler. Developers should just run one script to collect all the information they need.

Currently the test suite has the following:

  • density test (by adding a new Go test)
    • schedule 30k pods on 1000 (fake) nodes and 3k pods on 100 (fake) nodes
    • print out scheduling rate every second
    • let you learn the rate changes vs number of scheduled pods
  • benchmark
    • make use of go test -bench and report nanosecond/op.
    • schedule b.N pods when the cluster has N nodes and P scheduled pods. Since it takes relatively long time to finish one round, b.N is small: 10 - 100.

How To Run

# In Kubernetes root path
make generated_files

cd test/integration/scheduler_perf
./test-performance.sh

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