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Davanum Srinivas 954996e231
Move from glog to klog 
- Move from the old github.com/golang/glog to k8s.io/klog
- klog as explicit InitFlags() so we add them as necessary
- we update the other repositories that we vendor that made a similar
change from glog to klog
  * github.com/kubernetes/repo-infra
  * k8s.io/gengo/
  * k8s.io/kube-openapi/
  * github.com/google/cadvisor
- Entirely remove all references to glog
- Fix some tests by explicit InitFlags in their init() methods

Change-Id: I92db545ff36fcec83afe98f550c9e630098b3135
 		2018-11-10 07:50:31 -05:00
..
BUILD Move from glog to klog 2018-11-10 07:50:31 -05:00
OWNERS Aligned sched_perf owner. 2018-10-10 16:05:04 +08:00
README.md
…
main_test.go
…
scheduler_bench_test.go Move from glog to klog 2018-11-10 07:50:31 -05:00
scheduler_perf_types.go
…
scheduler_test.go Move from glog to klog 2018-11-10 07:50:31 -05:00
test-performance.sh
…
util.go create a new scheduler constructor 2018-10-10 17:10:10 +08:00

README.md

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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