PR Performance Report

Warp(workload=mixed, args=--duration=30m,--get-distrib=45,--stat-distrib=30,--put-distrib=15,--delete-distrib=10,--objects=30000,--obj.size=10MiB)

Throughput
2023-04-05T15:43:43.777318 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
Operations
2023-04-05T15:43:43.856704 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/

Comparision Tables

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

a3bb6a0d- âž™ 73da5613-

Warp mixed 30m âž™ Warp mixed 30m

Test
 delete-bw-mean
byte/s 		delete-iops-mean
iops 		read-bw-mean
byte/s 		read-iops-mean
iops 		write-bw-mean
byte/s 		write-iops-mean
iops
Warp(workload=mixed, args=--duration=30m,--get-distrib=45,--stat-distrib=30,--put-distrib=15,--delete-distrib=10,--objects=30000,--obj.size=10MiB) - 1.00x 1.00x 1.00x 0.97x 0.97x

a3bb6a0d- âž™ 3a581939-

Warp mixed 30m âž™ Warp mixed 30m

Test
 delete-bw-mean
byte/s 		delete-iops-mean
iops 		read-bw-mean
byte/s 		read-iops-mean
iops 		write-bw-mean
byte/s 		write-iops-mean
iops
Warp(workload=mixed, args=--duration=30m,--get-distrib=45,--stat-distrib=30,--put-distrib=15,--delete-distrib=10,--objects=30000,--obj.size=10MiB) - 0.50x 0.50x 0.50x 1.58x 1.58x

73da5613- âž™ 3a581939-

Warp mixed 30m âž™ Warp mixed 30m

Test
 delete-bw-mean
byte/s 		delete-iops-mean
iops 		read-bw-mean
byte/s 		read-iops-mean
iops 		write-bw-mean
byte/s 		write-iops-mean
iops
Warp(workload=mixed, args=--duration=30m,--get-distrib=45,--stat-distrib=30,--put-distrib=15,--delete-distrib=10,--objects=30000,--obj.size=10MiB) - 0.50x 0.50x 0.50x 1.63x 1.63x

Test Environment

description Warp mixed 30m Warp mixed 30m Warp mixed 30m
suite_id a3bb6a0d-b424-447e-ad0e-590b914c25a9 73da5613-3e34-4552-bd23-470db2c0b545 3a581939-a24b-4086-9818-1a20085e05ae
name warp-mixed-long warp-mixed-long warp-mixed-long
under-test-s3gw-version ceph version 9e26cc7 (9e26cc7fe7f5daf510205794ed0c2707794f375c) reef (dev) ceph version s3gw-v0.13.0 (7fa0c195642b49bc2dba00347990685514507882) reef (dev) ceph version Development (no_version) reef (dev)
under-test-image-tags quay.io/s3gw/s3gw:v0.12.0 quay.io/s3gw/s3gw:v0.13.0 quay.io/s3gw/s3gw:latest;quay.io/s3gw/s3gw:v0.14.0
under-test-image-id sha256:e9d23c2f0935f01d907b8085e943a6d1937fe76a7aa4d1ef3f41ce57391abea5 sha256:0141faf9eb856d632cb3600bed5195f21fc034c6c9b67f814ca61980d31cff56 sha256:a0b92c1b5c38e46660ed56d473121ac64fca58969c10fbdea97ad8b3e9aad0ad
avg_test_runtime 72.82290011644363 73.62191677093506 42.29033321142197
cpu-count 8 8 8
cpu-model Intel(R) Xeon(R) CPU E3-1260L v5 @ 2.90GHz Intel(R) Xeon(R) CPU E3-1260L v5 @ 2.90GHz Intel(R) Xeon(R) CPU E3-1260L v5 @ 2.90GHz
disk-model INTEL SSDPED1K375GA INTEL SSDPED1K375GA INTEL SSDPED1K375GA
finished 2023-03-31 18:41:40.621 2023-03-31 19:55:27.431 2023-03-31 20:37:47.879
memtotalkb 65666824 65666824 65666824
n_tests 1 1 1
node-name ares ares ares
os-release 5.14.21-150400.24.41-default 5.14.21-150400.24.41-default 5.14.21-150400.24.41-default
runtime_min 73.0 74.0 42.0
start 2023-03-31 17:28:51.209 2023-03-31 18:41:50.074 2023-03-31 19:55:30.420
test-image-id sha256:eb1125ee330e00ada295530ab338db29d369d8b229246188d2850493a6308fde sha256:eb1125ee330e00ada295530ab338db29d369d8b229246188d2850493a6308fde sha256:eb1125ee330e00ada295530ab338db29d369d8b229246188d2850493a6308fde
test-image-tags minio/warp:latest minio/warp:latest minio/warp:latest
test-warp-version warp version 0.6.7 - 6e801f5 warp version 0.6.7 - 6e801f5 warp version 0.6.7 - 6e801f5

Latency Graphs

Warp(workload=mixed, args=--duration=30m,--get-distrib=45,--stat-distrib=30,--put-distrib=15,--delete-distrib=10,--objects=30000,--obj.size=10MiB)

Test
a3bb6a0d-
2023-04-05T15:43:43.990498 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
DELETE 3 19236 64 54
2023-04-05T15:43:44.146030 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
GET 8 20634 111 102
2023-04-05T15:43:44.279021 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
PUT 1569 2762 2034 2024
2023-04-05T15:43:44.412300 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
STAT 1 19880 53 44
73da5613-
2023-04-05T15:43:44.544724 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
DELETE 2 15592 65 56
2023-04-05T15:43:44.674452 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
GET 8 22167 110 102
2023-04-05T15:43:44.807765 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
PUT 1596 2791 2112 2107
2023-04-05T15:43:44.941232 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
STAT 1 17578 52 44
3a581939-
2023-04-05T15:43:45.074282 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
DELETE 24 2598 176 168
2023-04-05T15:43:45.239046 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
GET 65 4070 264 256
2023-04-05T15:43:45.387538 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
PUT 140 639 281 274
2023-04-05T15:43:45.517690 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/
op fastest [ms] slowest [ms] avg [ms] median [ms]
STAT 49 3687 232 223