benchmark

README

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

Density tests

# In Kubernetes root path
make test-integration WHAT=./test/integration/scheduler_perf KUBE_TEST_VMODULE="''" KUBE_TEST_ARGS="-alsologtostderr=true -logtostderr=true -run=." KUBE_TIMEOUT="--timeout=60m" SHORT="--short=false"

Benchmark tests

# In Kubernetes root path
make test-integration WHAT=./test/integration/scheduler_perf KUBE_TEST_VMODULE="''" KUBE_TEST_ARGS="-alsologtostderr=false -logtostderr=false -run=^$$ -benchtime=1ns -bench=BenchmarkPerfScheduling"

The benchmark suite runs all the tests specified under config/performance-config.yaml.

Once the benchmark is finished, JSON file with metrics is available in the current directory (test/integration/scheduler_perf). Look for BenchmarkPerfScheduling_YYYY-MM-DDTHH:MM:SSZ.json. You can use -data-items-dir to generate the metrics file elsewhere.

In case you want to run a specific test in the suite, you can specify the test through -bench flag:

Also, bench time is explicitly set to 1ns (-benchtime=1ns flag) so each test is run only once. Otherwise, the golang benchmark framework will try to run a test more than once in case it ran for less than 1s.

# In Kubernetes root path
make test-integration WHAT=./test/integration/scheduler_perf KUBE_TEST_VMODULE="''" KUBE_TEST_ARGS="-alsologtostderr=false -logtostderr=false -run=^$$ -benchtime=1ns -bench=BenchmarkPerfScheduling/SchedulingBasic/5000Nodes/5000InitPods/1000PodsToSchedule"

To produce a cpu profile:

# In Kubernetes root path
make test-integration WHAT=./test/integration/scheduler_perf KUBE_TIMEOUT="-timeout=3600s" KUBE_TEST_VMODULE="''" KUBE_TEST_ARGS="-alsologtostderr=false -logtostderr=false -run=^$$ -benchtime=1ns -bench=BenchmarkPerfScheduling -cpuprofile ~/cpu-profile.out"

Documentation

Index

• type DataItem
• type DataItems

Types

type DataItem

type DataItem struct {
	// Data is a map from bucket to real data point (e.g. "Perc90" -> 23.5). Notice
	// that all data items with the same label combination should have the same buckets.
	Data map[string]float64 `json:"data"`
	// Unit is the data unit. Notice that all data items with the same label combination
	// should have the same unit.
	Unit string `json:"unit"`
	// Labels is the labels of the data item.
	Labels map[string]string `json:"labels,omitempty"`
}

DataItem is the data point.

type DataItems

type DataItems struct {
	Version   string     `json:"version"`
	DataItems []DataItem `json:"dataItems"`
}

DataItems is the data point set. It is the struct that perf dashboard expects.