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https://github.com/Huang-Wei/k8s-sched-perf-stat
A tool to analyze the result(s) of Kubernetes Scheduler Integration Performance test
https://github.com/Huang-Wei/k8s-sched-perf-stat
Last synced: 2 months ago
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A tool to analyze the result(s) of Kubernetes Scheduler Integration Performance test
- Host: GitHub
- URL: https://github.com/Huang-Wei/k8s-sched-perf-stat
- Owner: Huang-Wei
- License: apache-2.0
- Created: 2021-02-05T23:18:08.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2021-02-06T01:17:15.000Z (over 3 years ago)
- Last Synced: 2024-01-20T21:51:37.211Z (5 months ago)
- Language: Go
- Size: 23.4 KB
- Stars: 9
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Lists
- awesome-cloud-native - k8s-sched-perf-stat - A tool to analyze the result of Kubernetes Scheduler Integration Performance test. (Test)
README
# k8s-sched-perf-stat
A tool to analyze the result(s) of [Kubernetes Scheduler Integration Performance test](https://github.com/kubernetes/kubernetes/tree/master/test/integration/scheduler_perf).
## Preparation
Firstly, collect the results of a particular scheduler performance test. It's recommended to run it for 10+ times. (This tool will eliminate the outliers automatically.)
```bash
# Run the test for 10 times
for i in {1..10}; do
make test-integration WHAT=./test/integration/scheduler_perf KUBE_TEST_VMODULE="''" KUBE_TEST_ARGS="-alsologtostderr=false -logtostderr=false -run=^$$ -benchtime=1ns -bench=BenchmarkPerfScheduling/Unschedulable/500Nodes/200InitPods/1000PodsToSchedule -data-items-dir /tmp"
done
```
Then concatenate the results into a file:
```bash
rm -f /tmp/old.txt
ls /tmp/BenchmarkPerfScheduling*.json | while read f; do
cat $f >> /tmp/old.txt
echo >> /tmp/old.txt # append newline
done
```
## Usage
You can use this tool to analyze the results against a fixed codebase, by providing one argument:
```shell
$ go run *.go testdata/old1.txt
+--------------------------+------------------------------------+----------+--------+---------+
| METRIC | GROUP | QUANTILE | UNIT | MEDIAN |
+--------------------------+------------------------------------+----------+--------+---------+
| SchedulingThroughput | Unschedulable/500Nodes/200InitPods | Average | pods/s | 133.93 |
| SchedulingThroughput | Unschedulable/500Nodes/200InitPods | Perc50 | pods/s | 30.00 |
| SchedulingThroughput | Unschedulable/500Nodes/200InitPods | Perc90 | pods/s | 564.50 |
| SchedulingThroughput | Unschedulable/500Nodes/200InitPods | Perc99 | pods/s | 564.50 |
| scheduler_e2e_scheduling | Unschedulable/500Nodes/200InitPods | Average | ms | 458.46 |
| scheduler_e2e_scheduling | Unschedulable/500Nodes/200InitPods | Perc50 | ms | 15.53 |
| scheduler_e2e_scheduling | Unschedulable/500Nodes/200InitPods | Perc90 | ms | 1288.26 |
| scheduler_e2e_scheduling | Unschedulable/500Nodes/200InitPods | Perc99 | ms | 1749.03 |
| scheduler_pod_scheduling | Unschedulable/500Nodes/200InitPods | Average | ms | 3153.33 |
| scheduler_pod_scheduling | Unschedulable/500Nodes/200InitPods | Perc50 | ms | 3074.85 |
| scheduler_pod_scheduling | Unschedulable/500Nodes/200InitPods | Perc90 | ms | 4742.60 |
| scheduler_pod_scheduling | Unschedulable/500Nodes/200InitPods | Perc99 | ms | 5783.46 |
+--------------------------+------------------------------------+----------+--------+---------+
```
Or, by providing two arguments, this tool will compare them and show the diff:
```shell
$ go run *.go testdata/old1.txt testdata/new1.txt
+--------------------------+------------------------------------+----------+--------+---------+---------+---------+
| METRIC | GROUP | QUANTILE | UNIT | OLD | NEW | DIFF |
+--------------------------+------------------------------------+----------+--------+---------+---------+---------+
| SchedulingThroughput | Unschedulable/500Nodes/200InitPods | Average | pods/s | 133.93 | 152.68 | +14.00% |
| SchedulingThroughput | Unschedulable/500Nodes/200InitPods | Perc50 | pods/s | 30.00 | 49.00 | +63.33% |
| SchedulingThroughput | Unschedulable/500Nodes/200InitPods | Perc90 | pods/s | 564.50 | 515.50 | -8.68% |
| SchedulingThroughput | Unschedulable/500Nodes/200InitPods | Perc99 | pods/s | 564.50 | 515.50 | -8.68% |
| scheduler_e2e_scheduling | Unschedulable/500Nodes/200InitPods | Average | ms | 458.46 | 334.55 | -27.03% |
| scheduler_e2e_scheduling | Unschedulable/500Nodes/200InitPods | Perc50 | ms | 15.53 | 13.64 | -12.14% |
| scheduler_e2e_scheduling | Unschedulable/500Nodes/200InitPods | Perc90 | ms | 1288.26 | 1004.83 | -22.00% |
| scheduler_e2e_scheduling | Unschedulable/500Nodes/200InitPods | Perc99 | ms | 1749.03 | 1472.26 | -15.82% |
| scheduler_pod_scheduling | Unschedulable/500Nodes/200InitPods | Average | ms | 3153.33 | 3339.24 | +5.90% |
| scheduler_pod_scheduling | Unschedulable/500Nodes/200InitPods | Perc50 | ms | 3074.85 | 3346.54 | +8.84% |
| scheduler_pod_scheduling | Unschedulable/500Nodes/200InitPods | Perc90 | ms | 4742.60 | 5580.41 | +17.67% |
| scheduler_pod_scheduling | Unschedulable/500Nodes/200InitPods | Perc99 | ms | 5783.46 | 6009.02 | +3.90% |
+--------------------------+------------------------------------+----------+--------+---------+---------+---------+
```