PR Performance Report

Warp(workload=delete, args=--concurrent=1,--duration=10m,--obj.size=32MiB,--obj.randsize=false,--objects=8192)

Throughput
2023-04-05T15:43:03.940688 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:03.997116 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Warp(workload=delete, args=--concurrent=20,--duration=10m,--obj.size=256,--obj.randsize=false,--objects=100000)

Throughput
2023-04-05T15:43:04.051684 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:04.111532 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Warp(workload=delete, args=--concurrent=20,--duration=10m,--obj.size=32MiB,--obj.randsize=false,--objects=8192)

Throughput
2023-04-05T15:43:04.168774 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:04.223289 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Warp(workload=get, args=--concurrent=1,--duration=10m,--obj.size=256,128MiB,--obj.generator=random,--obj.randsize=true,--objects=2048)

Throughput
2023-04-05T15:43:04.276883 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:04.354757 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Warp(workload=get, args=--concurrent=1,--duration=10m,--obj.size=32MiB,--obj.randsize=false,--objects=8192)

Throughput
2023-04-05T15:43:04.409061 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:04.465457 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Warp(workload=get, args=--concurrent=1,--duration=10m,--obj.size=32MiB,--obj.randsize=false,--objects=8192,--range)

Throughput
2023-04-05T15:43:04.519773 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:04.574533 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Warp(workload=get, args=--concurrent=20,--duration=10m,--obj.size=256,128MiB,--obj.generator=random,--obj.randsize=true,--objects=2048)

Throughput
2023-04-05T15:43:04.627264 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:04.680996 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Warp(workload=get, args=--concurrent=20,--duration=10m,--obj.size=32MiB,--obj.randsize=false,--objects=8192)

Throughput
2023-04-05T15:43:04.735211 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:04.789282 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Warp(workload=get, args=--concurrent=20,--duration=10m,--obj.size=32MiB,--obj.randsize=false,--objects=8192,--range)

Throughput
2023-04-05T15:43:04.843440 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:04.901287 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Warp(workload=list, args=--concurrent=1,--duration=10m,--obj.size=256,--obj.randsize=false,--objects=1000)

Throughput
2023-04-05T15:43:04.958858 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:05.012597 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Warp(workload=list, args=--concurrent=1,--duration=10m,--obj.size=256,--obj.randsize=false,--objects=10000)

Throughput
2023-04-05T15:43:05.066708 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:05.125015 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Warp(workload=list, args=--concurrent=20,--duration=10m,--obj.size=256,--obj.randsize=false,--objects=1000)

Throughput
2023-04-05T15:43:05.182082 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:05.237340 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Warp(workload=list, args=--concurrent=20,--duration=10m,--obj.size=256,--obj.randsize=false,--objects=10000)

Throughput
2023-04-05T15:43:05.298572 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:05.360091 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Warp(workload=list, args=--concurrent=20,--duration=10m,--obj.size=256,--obj.randsize=false,--objects=100000)

Throughput
2023-04-05T15:43:05.420026 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:05.478016 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Warp(workload=put, args=--concurrent=1,--duration=10m,--obj.size=32MiB,--disable-multipart,--obj.randsize=false)

Throughput
2023-04-05T15:43:05.534889 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:05.589199 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Warp(workload=put, args=--concurrent=1,--duration=10m,--obj.size=32MiB,--obj.randsize=false)

Throughput
2023-04-05T15:43:05.671178 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:05.726190 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Warp(workload=put, args=--concurrent=20,--duration=10m,--obj.size=256,128MiB,--obj.generator=random,--obj.randsize=true)

Throughput
2023-04-05T15:43:05.781200 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:05.839383 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Warp(workload=put, args=--concurrent=20,--duration=10m,--obj.size=32MiB,--disable-multipart,--obj.randsize=false)

Throughput
2023-04-05T15:43:05.896225 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:05.952128 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Warp(workload=put, args=--concurrent=20,--duration=10m,--obj.size=32MiB,--obj.randsize=false)

Throughput
2023-04-05T15:43:06.007756 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:06.062530 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Comparision Tables

> 1 faster, = 1 no change, < 1 slower, > 1.3x 😎

Test Environment

suite_id 6ac2da8d-e4da-40e3-8386-5c21cdf790a7
description Warp: Single Operation Benchmarks
name warp-single-op
under-test-image-id sha256:a0b92c1b5c38e46660ed56d473121ac64fca58969c10fbdea97ad8b3e9aad0ad
under-test-s3gw-version ceph version Development (no_version) reef (dev)
under-test-image-tags quay.io/s3gw/s3gw:latest;quay.io/s3gw/s3gw:v0.14.0
avg_test_runtime 20.608515766890424
cpu-count 8
cpu-model Intel(R) Xeon(R) CPU E3-1260L v5 @ 2.90GHz
disk-model INTEL SSDPED1K375GA
finished 2023-04-01 03:09:24.839
memtotalkb 65666824
n_tests 19
node-name ares
os-release 5.14.21-150400.24.41-default
runtime_min 392.0
start 2023-03-31 20:37:51.013
test-image-id sha256:eb1125ee330e00ada295530ab338db29d369d8b229246188d2850493a6308fde
test-image-tags minio/warp:latest
test-warp-version warp version 0.6.7 - 6e801f5

Latency Graphs

Warp(workload=delete, args=--concurrent=1,--duration=10m,--obj.size=32MiB,--obj.randsize=false,--objects=8192)

Test
6ac2da8d-
2023-04-05T15:43:06.179700 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
PUT 288 368 321 320
2023-04-05T15:43:06.310583 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
DELETE 974 1102 1031 1037

Warp(workload=delete, args=--concurrent=20,--duration=10m,--obj.size=256,--obj.randsize=false,--objects=100000)

Test
6ac2da8d-
2023-04-05T15:43:06.442183 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
PUT 24 1041 118 112
2023-04-05T15:43:06.573505 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
DELETE 40074 43469 41917 41900

Warp(workload=delete, args=--concurrent=20,--duration=10m,--obj.size=32MiB,--obj.randsize=false,--objects=8192)

Test
6ac2da8d-
2023-04-05T15:43:06.704700 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
PUT 1056 2208 1560 1555
2023-04-05T15:43:06.869455 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
DELETE 8396 8755 8539 8755

Warp(workload=get, args=--concurrent=1,--duration=10m,--obj.size=256,128MiB,--obj.generator=random,--obj.randsize=true,--objects=2048)

Test
6ac2da8d-
No data
No data

Warp(workload=get, args=--concurrent=1,--duration=10m,--obj.size=32MiB,--obj.randsize=false,--objects=8192)

Test
6ac2da8d-
2023-04-05T15:43:07.002402 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
PUT 288 388 321 316
2023-04-05T15:43:07.132219 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
GET 26 91 33 33

Warp(workload=get, args=--concurrent=1,--duration=10m,--obj.size=32MiB,--obj.randsize=false,--objects=8192,--range)

Test
6ac2da8d-
2023-04-05T15:43:07.263276 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
PUT 288 380 320 316
No data

Warp(workload=get, args=--concurrent=20,--duration=10m,--obj.size=256,128MiB,--obj.generator=random,--obj.randsize=true,--objects=2048)

Test
6ac2da8d-
No data
No data

Warp(workload=get, args=--concurrent=20,--duration=10m,--obj.size=32MiB,--obj.randsize=false,--objects=8192)

Test
6ac2da8d-
2023-04-05T15:43:07.399030 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
PUT 1079 2335 1558 1553
2023-04-05T15:43:07.528662 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
GET 40 527 229 227

Warp(workload=get, args=--concurrent=20,--duration=10m,--obj.size=32MiB,--obj.randsize=false,--objects=8192,--range)

Test
6ac2da8d-
2023-04-05T15:43:07.660292 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
PUT 1101 2165 1572 1563
No data

Warp(workload=list, args=--concurrent=1,--duration=10m,--obj.size=256,--obj.randsize=false,--objects=1000)

Test
6ac2da8d-
2023-04-05T15:43:07.795403 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
PUT 3 9 4 4
2023-04-05T15:43:07.965642 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
LIST 2097 3268 2156 2123

Warp(workload=list, args=--concurrent=1,--duration=10m,--obj.size=256,--obj.randsize=false,--objects=10000)

Test
6ac2da8d-
2023-04-05T15:43:08.096156 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
PUT 3 17 6 6
2023-04-05T15:43:08.226629 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
LIST 79432 83540 80197 79504

Warp(workload=list, args=--concurrent=20,--duration=10m,--obj.size=256,--obj.randsize=false,--objects=1000)

Test
6ac2da8d-
2023-04-05T15:43:08.354580 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
LIST 14062 17975 15234 15207

Warp(workload=list, args=--concurrent=20,--duration=10m,--obj.size=256,--obj.randsize=false,--objects=10000)

Test
6ac2da8d-
2023-04-05T15:43:08.484779 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
PUT 4 232 61 58

Warp(workload=list, args=--concurrent=20,--duration=10m,--obj.size=256,--obj.randsize=false,--objects=100000)

Test
6ac2da8d-
2023-04-05T15:43:08.618809 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
PUT 24 758 118 111

Warp(workload=put, args=--concurrent=1,--duration=10m,--obj.size=32MiB,--disable-multipart,--obj.randsize=false)

Test
6ac2da8d-
2023-04-05T15:43:08.755039 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
PUT 193 262 205 205

Warp(workload=put, args=--concurrent=1,--duration=10m,--obj.size=32MiB,--obj.randsize=false)

Test
6ac2da8d-
2023-04-05T15:43:08.888887 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
PUT 284 348 315 312

Warp(workload=put, args=--concurrent=20,--duration=10m,--obj.size=256,128MiB,--obj.generator=random,--obj.randsize=true)

Test
6ac2da8d-
No data

Warp(workload=put, args=--concurrent=20,--duration=10m,--obj.size=32MiB,--disable-multipart,--obj.randsize=false)

Test
6ac2da8d-
2023-04-05T15:43:09.067223 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
PUT 963 1895 1389 1384

Warp(workload=put, args=--concurrent=20,--duration=10m,--obj.size=32MiB,--obj.randsize=false)

Test
6ac2da8d-
2023-04-05T15:43:09.201499 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
PUT 1114 2210 1555 1551