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wip charts

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Adrien Beaudouin
2023-12-25 23:49:57 +01:00
parent db7655c4f8
commit 548a84ebe3
1 changed files with 237 additions and 79 deletions
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content/posts/22-web-api-benchmarks-2024/index.md
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@@ -249,22 +249,32 @@ export default function () {
| Max req/s | **140** |
| p(90) req duration | **544ms** |
{{< chart type="timeseries" title="Req/s count" datasets="Req/s|6,69,81,103,103,113,83,91,103,112,99,101,109,101,106,108,100,112,117,124,113,111,117,108,129,119,124,81,113,128,124,108,108,128,111,128,123,127,100,124,124,118,119,125,121,101,96,120,110,130,137,117,127,120,124,129,127,115,121,114,126,121,103,124,120,120,116,102,122,103,109,81" />}}
{{< chart type="timeseries" title="Req/s count" >}}
Req/s|6,69,81,103,103,113,83,91,103,112,99,101,109,101,106,108,100,112,117,124,113,111,117,108,129,119,124,81,113,128,124,108,108,128,111,128,123,127,100,124,124,118,119,125,121,101,96,120,110,130,137,117,127,120,124,129,127,115,121,114,126,121,103,124,120,120,116,102,122,103,109,81
{{< /chart >}}
{{< /tab >}}
{{< tab tabName="Req duration" >}}
{{< chart type="timeseries" title="VUs count" datasets="VUs|3,6,8,10,12,13,14,16,19,20,23,26,25,27,28,29,31,34,35,36,37,39,41,43,45,47,48,49,49,50,49,49,48,50,49,49,49,49,49,50,49,48,48,48,49,48,50,49,48,46,48,49,48,49,48,49,47,50,49,48,46,44,42,38,36,34,33,27,18,17,4" />}}
{{< chart type="timeseries" title="VUs count" >}}
VUs|3,6,8,10,12,13,14,16,19,20,23,26,25,27,28,29,31,34,35,36,37,39,41,43,45,47,48,49,49,50,49,49,48,50,49,49,49,49,49,50,49,48,48,48,49,48,50,49,48,46,48,49,48,49,48,49,47,50,49,48,46,44,42,38,36,34,33,27,18,17,4
{{< /chart >}}
{{< chart type="timeseries" title="Request duration in ms" datasets="Duration (ms)|36,37,71,70,93,104,145,152,157,171,186,224,224,265,223,295,256,260,323,286,309,324,322,353,365,350,409,454,475,408,400,395,495,414,421,391,415,394,458,391,422,416,414,400,382,443,440,494,433,376,372,381,401,410,384,382,393,381,454,369,402,438,393,378,319,316,307,304,254,212,151,80" />}}
{{< chart type="timeseries" title="Request duration in ms" >}}
Duration (ms)|36,37,71,70,93,104,145,152,157,171,186,224,224,265,223,295,256,260,323,286,309,324,322,353,365,350,409,454,475,408,400,395,495,414,421,391,415,394,458,391,422,416,414,400,382,443,440,494,433,376,372,381,401,410,384,382,393,381,454,369,402,438,393,378,319,316,307,304,254,212,151,80
{{< /chart >}}
{{< /tab >}}
{{< tab tabName="CPU load" >}}
{{< chart type="timeseries" title="CPU runtime load" datasets="User|0.03,0.34,0.37,0.36,0.38,0.36,0.03|#4bc0c0$System|0.02,0.08,0.07,0.09,0.08,0.08,0.02|#ff6384" stacked="true" max="1" step="15" />}}
{{< chart type="timeseries" title="CPU runtime load" stacked="true" max="1" step="15" >}}
User|0.03,0.34,0.37,0.36,0.38,0.36,0.03|#4bc0c0$System|0.02,0.08,0.07,0.09,0.08,0.08,0.02|#ff6384
{{< /chart >}}
{{< chart type="timeseries" title="CPU database load" datasets="User|0.03,0.89,0.9,0.91,0.91,0.53,0.03|#4bc0c0$System|0.02,0.07,0.07,0.09,0.09,0.05,0.02|#ff6384" stacked="true" max="1" step="15" />}}
{{< chart type="timeseries" title="CPU database load" stacked="true" max="1" step="15" >}}
User|0.03,0.89,0.9,0.91,0.91,0.53,0.03|#4bc0c0$System|0.02,0.07,0.07,0.09,0.09,0.05,0.02|#ff6384
{{< /chart >}}
{{< /tab >}}
{{< /tabs >}}
@@ -284,22 +294,32 @@ As expected here, database is the bottleneck. We'll get slow response time at fu
| Max req/s | **360** |
| p(90) req duration | **117ms** |
{{< chart type="timeseries" title="Req/s count" datasets="Req/s|1,38,40,137,150,211,216,255,247,269,285,299,294,291,295,322,322,327,308,314,329,329,341,324,318,336,341,344,328,329,349,347,353,329,333,352,360,351,339,330,355,359,353,328,340,355,348,355,340,334,356,347,356,346,337,347,358,353,336,341,347,347,350,328,345,355,351,351,349,341,354,351,353,340,343,343,353,362,336,333,353,344,362,338,335,353,353,355,339,320,304" />}}
{{< chart type="timeseries" title="Req/s count" >}}
Req/s|1,38,40,137,150,211,216,255,247,269,285,299,294,291,295,322,322,327,308,314,329,329,341,324,318,336,341,344,328,329,349,347,353,329,333,352,360,351,339,330,355,359,353,328,340,355,348,355,340,334,356,347,356,346,337,347,358,353,336,341,347,347,350,328,345,355,351,351,349,341,354,351,353,340,343,343,353,362,336,333,353,344,362,338,335,353,353,355,339,320,304
{{< /chart >}}
{{< /tab >}}
{{< tab tabName="Req duration" >}}
{{< chart type="timeseries" title="VUs count" datasets="VUs|1,1,2,2,3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,11,11,12,12,13,13,14,14,15,15,16,16,17,17,18,18,19,19,20,20,21,21,22,22,23,23,24,24,25,24,25,25,26,25,26,26,27,27,28,28,29,29,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,27,27,27,26,26,26,26,26,26,26,26,26" />}}
{{< chart type="timeseries" title="VUs count" >}}
VUs|1,1,2,2,3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,11,11,12,12,13,13,14,14,15,15,16,16,17,17,18,18,19,19,20,20,21,21,22,22,23,23,24,24,25,24,25,25,26,25,26,26,27,27,28,28,29,29,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,27,27,27,26,26,26,26,26,26,26,26,26
{{< /chart >}}
{{< chart type="timeseries" title="Request duration in ms" datasets="Duration (ms)|30,26,26,14,13,13,13,15,16,18,17,19,20,24,23,24,24,27,29,31,30,32,32,36,37,38,37,40,42,45,42,45,45,51,50,50,50,53,56,57,58,58,60,65,64,65,65,66,71,73,70,71,70,75,71,76,72,76,80,78,82,83,82,83,82,78,79,79,79,81,78,80,78,81,78,85,79,77,83,81,75,77,76,75,76,74,73,73,76,80,74" />}}
{{< chart type="timeseries" title="Request duration in ms" >}}
Duration (ms)|30,26,26,14,13,13,13,15,16,18,17,19,20,24,23,24,24,27,29,31,30,32,32,36,37,38,37,40,42,45,42,45,45,51,50,50,50,53,56,57,58,58,60,65,64,65,65,66,71,73,70,71,70,75,71,76,72,76,80,78,82,83,82,83,82,78,79,79,79,81,78,80,78,81,78,85,79,77,83,81,75,77,76,75,76,74,73,73,76,80,74
{{< /chart >}}
{{< /tab >}}
{{< tab tabName="CPU load" >}}
{{< chart type="timeseries" title="CPU runtime load" datasets="User|0.27,0.69,0.76,0.77,0.77,0.77,0.03|#4bc0c0$System|0.08,0.16,0.2,0.2,0.19,0.21,0.02|#ff6384" stacked="true" max="1" step="15" />}}
{{< chart type="timeseries" title="CPU runtime load" stacked="true" max="1" step="15" >}}
User|0.27,0.69,0.76,0.77,0.77,0.77,0.03|#4bc0c0$System|0.08,0.16,0.2,0.2,0.19,0.21,0.02|#ff6384
{{< /chart >}}
{{< chart type="timeseries" title="CPU database load" datasets="User|0.14,0.2,0.2,0.2,0.21,0.22,0.03|#4bc0c0$System|0.11,0.14,0.15,0.17,0.14,0.14,0.02|#ff6384" stacked="true" max="1" step="15" />}}
{{< chart type="timeseries" title="CPU database load" stacked="true" max="1" step="15" >}}
User|0.14,0.2,0.2,0.2,0.21,0.22,0.03|#4bc0c0$System|0.11,0.14,0.15,0.17,0.14,0.14,0.02|#ff6384
{{< /chart >}}
{{< /tab >}}
{{< /tabs >}}
@@ -319,22 +339,32 @@ Now we have a very runtime intensive scenario, with workers as bottleneck, API i
| Max req/s | **70** |
| p(90) req duration | **1.24s** |
{{< chart type="timeseries" title="Req/s count" datasets="Req/s|31,62,60,64,63,68,66,63,64,64,67,66,64,65,65,64,66,63,55,69,65,66,63,66,65,65,65,60,64,66,65,63,64,58,56,59,53,52,56,60,52,53,47,50,53,56,50,45,54,56,54,49,47,47,52,56,47,44,51,58,53,43,51,48,48,45,45,40,44,41,46,41,43,43,38,42,36,38,36,35,29" />}}
{{< chart type="timeseries" title="Req/s count" >}}
Req/s|31,62,60,64,63,68,66,63,64,64,67,66,64,65,65,64,66,63,55,69,65,66,63,66,65,65,65,60,64,66,65,63,64,58,56,59,53,52,56,60,52,53,47,50,53,56,50,45,54,56,54,49,47,47,52,56,47,44,51,58,53,43,51,48,48,45,45,40,44,41,46,41,43,43,38,42,36,38,36,35,29
{{< /chart >}}
{{< /tab >}}
{{< tab tabName="Req duration" >}}
{{< chart type="timeseries" title="VUs count" datasets="VUs|2,4,6,8,10,10,12,14,15,17,18,20,21,22,24,26,28,29,31,32,33,35,37,37,39,40,42,44,45,47,48,49,50,50,49,50,49,49,50,50,50,50,49,50,49,50,50,50,49,50,49,50,49,50,49,49,50,49,50,48,48,48,47,45,43,42,39,38,37,35,30,30,25,21,20,19,17,15,12,8" />}}
{{< chart type="timeseries" title="VUs count" >}}
VUs|2,4,6,8,10,10,12,14,15,17,18,20,21,22,24,26,28,29,31,32,33,35,37,37,39,40,42,44,45,47,48,49,50,50,49,50,49,49,50,50,50,50,49,50,49,50,50,50,49,50,49,50,49,50,49,49,50,49,50,48,48,48,47,45,43,42,39,38,37,35,30,30,25,21,20,19,17,15,12,8
{{< /chart >}}
{{< chart type="timeseries" title="Request duration in ms" datasets="Duration (ms)|50,56,89,114,147,148,169,210,231,239,253,284,333,352,344,364,431,458,448,497,483,534,558,573,561,597,628,693,689,687,715,743,780,879,847,848,916,929,892,905,944,941,989,954,979,944,932,979,1009,929,934,940,1059,981,1001,962,989,1047,963,1015,911,925,1046,1008,962,905,970,910,894,877,792,725,730,584,515,505,474,459,382,289,186" />}}
{{< chart type="timeseries" title="Request duration in ms" >}}
Duration (ms)|50,56,89,114,147,148,169,210,231,239,253,284,333,352,344,364,431,458,448,497,483,534,558,573,561,597,628,693,689,687,715,743,780,879,847,848,916,929,892,905,944,941,989,954,979,944,932,979,1009,929,934,940,1059,981,1001,962,989,1047,963,1015,911,925,1046,1008,962,905,970,910,894,877,792,725,730,584,515,505,474,459,382,289,186
{{< /chart >}}
{{< /tab >}}
{{< tab tabName="CPU load" >}}
{{< chart type="timeseries" title="CPU runtime load" datasets="User|0.02,0.31,0.29,0.28,0.28,0.27,0.03|#4bc0c0$System|0.01,0.06,0.06,0.06,0.06,0.06,0.01|#ff6384" stacked="true" max="1" step="15" />}}
{{< chart type="timeseries" title="CPU runtime load" stacked="true" max="1" step="15" >}}
User|0.02,0.31,0.29,0.28,0.28,0.27,0.03|#4bc0c0$System|0.01,0.06,0.06,0.06,0.06,0.06,0.01|#ff6384
{{< /chart >}}
{{< chart type="timeseries" title="CPU database load" datasets="User|0.04,0.8,0.82,0.85,0.86,0.87,0.36,0.03|#4bc0c0$System|0.02,0.19,0.18,0.15,0.14,0.13,0.05,0.02|#ff6384" stacked="true" max="1" step="15" />}}
{{< chart type="timeseries" title="CPU database load" stacked="true" max="1" step="15" >}}
User|0.04,0.8,0.82,0.85,0.86,0.87,0.36,0.03|#4bc0c0$System|0.02,0.19,0.18,0.15,0.14,0.13,0.05,0.02|#ff6384
{{< /chart >}}
{{< /tab >}}
{{< /tabs >}}
@@ -354,22 +384,32 @@ Now it seems interesting, Laravel performs literally about 2x slower with Postgr
| Max req/s | **220** |
| p(90) req duration | **128ms** |
{{< chart type="timeseries" title="Req/s count" datasets="Req/s|16,26,27,64,93,94,119,128,120,134,149,150,157,155,152,169,168,169,167,166,175,178,185,175,176,187,181,190,185,179,190,196,194,187,178,193,202,195,195,183,195,201,195,196,190,203,195,205,195,191,203,205,205,197,188,200,208,207,197,190,208,215,212,205,185,204,203,211,194,189,208,211,201,198,199,197,207,206,203,194,203,207,203,198,195,202,206,207,203,191,41" />}}
{{< chart type="timeseries" title="Req/s count" >}}
Req/s|16,26,27,64,93,94,119,128,120,134,149,150,157,155,152,169,168,169,167,166,175,178,185,175,176,187,181,190,185,179,190,196,194,187,178,193,202,195,195,183,195,201,195,196,190,203,195,205,195,191,203,205,205,197,188,200,208,207,197,190,208,215,212,205,185,204,203,211,194,189,208,211,201,198,199,197,207,206,203,194,203,207,203,198,195,202,206,207,203,191,41
{{< /chart >}}
{{< /tab >}}
{{< tab tabName="Req duration" >}}
{{< chart type="timeseries" title="VUs count" datasets="VUs|1,1,1,2,2,2,3,3,3,4,4,4,5,5,5,6,6,6,7,7,7,8,8,8,9,9,9,10,10,10,11,11,11,12,12,12,13,13,13,14,14,14,15,15,15,16,16,16,17,17,17,18,18,18,19,19,19,20,20,20,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21" />}}
{{< chart type="timeseries" title="VUs count" >}}
VUs|1,1,1,2,2,2,3,3,3,4,4,4,5,5,5,6,6,6,7,7,7,8,8,8,9,9,9,10,10,10,11,11,11,12,12,12,13,13,13,14,14,14,15,15,15,16,16,16,17,17,17,18,18,18,19,19,19,20,20,20,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21
{{< /chart >}}
{{< chart type="timeseries" title="Request duration in ms" datasets="Duration (ms)|44,38,37,27,21,21,22,23,24,28,27,26,30,32,32,34,36,35,40,42,40,43,43,46,50,48,49,51,54,55,56,56,56,63,67,62,62,67,66,74,71,70,75,76,78,77,82,77,85,89,84,85,88,91,96,97,92,94,103,104,99,99,97,104,110,107,102,100,105,109,105,99,104,105,107,106,100,102,103,107,104,102,103,104,106,105,103,101,103,108,102" />}}
{{< chart type="timeseries" title="Request duration in ms" >}}
Duration (ms)|44,38,37,27,21,21,22,23,24,28,27,26,30,32,32,34,36,35,40,42,40,43,43,46,50,48,49,51,54,55,56,56,56,63,67,62,62,67,66,74,71,70,75,76,78,77,82,77,85,89,84,85,88,91,96,97,92,94,103,104,99,99,97,104,110,107,102,100,105,109,105,99,104,105,107,106,100,102,103,107,104,102,103,104,106,105,103,101,103,108,102
{{< /chart >}}
{{< /tab >}}
{{< tab tabName="CPU load" >}}
{{< chart type="timeseries" title="CPU runtime load" datasets="User|0.05,0.49,0.64,0.7,0.74,0.72,0.6,0.03|#4bc0c0$System|0.02,0.1,0.12,0.14,0.14,0.14,0.12,0.02|#ff6384" stacked="true" max="1" step="15" />}}
{{< chart type="timeseries" title="CPU runtime load" stacked="true" max="1" step="15" >}}
User|0.05,0.49,0.64,0.7,0.74,0.72,0.6,0.03|#4bc0c0$System|0.02,0.1,0.12,0.14,0.14,0.14,0.12,0.02|#ff6384
{{< /chart >}}
{{< chart type="timeseries" title="CPU database load" datasets="User|0.09,0.28,0.34,0.35,0.37,0.39,0.03,0.03|#4bc0c0$System|0.13,0.36,0.41,0.44,0.46,0.47,0.02,0.02|#ff6384" stacked="true" max="1" step="15" />}}
{{< chart type="timeseries" title="CPU database load" stacked="true" max="1" step="15" >}}
User|0.09,0.28,0.34,0.35,0.37,0.39,0.03,0.03|#4bc0c0$System|0.13,0.36,0.41,0.44,0.46,0.47,0.02,0.02|#ff6384
{{< /chart >}}
{{< /tab >}}
{{< /tabs >}}
@@ -391,22 +431,32 @@ Laravel seems less limited by database performance, but still slower than MySQL.
| Max req/s | **50** |
| p(90) req duration | **1.38s** |
{{< chart type="timeseries" title="Req/s count" datasets="Req/s|13,37,37,38,41,40,39,38,37,42,35,39,37,40,40,38,38,38,38,41,37,42,39,33,45,41,42,32,39,44,38,33,41,44,32,43,41,43,32,39,45,40,36,36,40,39,37,44,40,35,42,43,29,41,40,44,38,35,42,41,40,38,39,40,40,40,43,41,43,43,38,40,39,48,43,42,39,41,40,45,38,44,37,10" />}}
{{< chart type="timeseries" title="Req/s count" >}}
Req/s|13,37,37,38,41,40,39,38,37,42,35,39,37,40,40,38,38,38,38,41,37,42,39,33,45,41,42,32,39,44,38,33,41,44,32,43,41,43,32,39,45,40,36,36,40,39,37,44,40,35,42,43,29,41,40,44,38,35,42,41,40,38,39,40,40,40,43,41,43,43,38,40,39,48,43,42,39,41,40,45,38,44,37,10
{{< /chart >}}
{{< /tab >}}
{{< tab tabName="Req duration" >}}
{{< chart type="timeseries" title="VUs count" datasets="VUs|3,6,9,12,15,18,21,24,27,30,33,36,39,42,45,48,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,49,50,50,50,49,49,50,50,50,49,50,50,49,50,50,49,49,48,47,46,43,42,42,40,36,35,32,28,23,17,14,14,13,12,10,9,8,2" />}}
{{< chart type="timeseries" title="VUs count" >}}
VUs|3,6,9,12,15,18,21,24,27,30,33,36,39,42,45,48,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,49,50,50,50,49,49,50,50,50,49,50,50,49,50,50,49,49,48,47,46,43,42,42,40,36,35,32,28,23,17,14,14,13,12,10,9,8,2
{{< /chart >}}
{{< chart type="timeseries" title="Request duration in ms" datasets="Duration (ms)|85,107,182,244,304,380,458,555,623,664,740,817,916,994,1041,1109,1224,1272,1289,1272,1230,1243,1311,1343,1282,1227,1267,1247,1275,1273,1291,1300,1329,1261,1243,1278,1241,1307,1235,1277,1245,1269,1271,1385,1298,1220,1256,1288,1278,1258,1271,1250,1307,1353,1257,1235,1255,1254,1304,1245,1222,1262,1287,1241,1191,1122,1098,1073,1055,953,863,902,809,692,536,373,350,350,300,298,239,221,182,78" />}}
{{< chart type="timeseries" title="Request duration in ms" >}}
Duration (ms)|85,107,182,244,304,380,458,555,623,664,740,817,916,994,1041,1109,1224,1272,1289,1272,1230,1243,1311,1343,1282,1227,1267,1247,1275,1273,1291,1300,1329,1261,1243,1278,1241,1307,1235,1277,1245,1269,1271,1385,1298,1220,1256,1288,1278,1258,1271,1250,1307,1353,1257,1235,1255,1254,1304,1245,1222,1262,1287,1241,1191,1122,1098,1073,1055,953,863,902,809,692,536,373,350,350,300,298,239,221,182,78
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{{< tab tabName="CPU load" >}}
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{{< chart type="timeseries" title="CPU runtime load" stacked="true" max="1" step="15" >}}
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{{< chart type="timeseries" title="CPU database load" datasets="User|0.04,0.97,0.97,0.97,0.97,0.98,0.04,0.03|#4bc0c0$System|0.02,0.03,0.03,0.03,0.03,0.02,0.02,0.02|#ff6384" stacked="true" max="1" step="15" />}}
{{< chart type="timeseries" title="CPU database load" stacked="true" max="1" step="15" >}}
User|0.04,0.97,0.97,0.97,0.97,0.98,0.04,0.03|#4bc0c0$System|0.02,0.03,0.03,0.03,0.03,0.02,0.02,0.02|#ff6384
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{{< /tabs >}}
@@ -426,22 +476,32 @@ It's getting pretty ugly here, with a very high response time (> 1s) at full loa
| Max req/s | **410** |
| p(90) req duration | **41ms** |
{{< chart type="timeseries" title="Req/s count" datasets="Req/s|17,44,40,87,174,168,194,228,229,256,302,289,308,335,345,346,343,328,374,381,359,362,368,393,389,403,380,371,390,387,388,366,379,400,389,397,382,373,390,401,393,387,387,392,413,411,379,390,413,414,414,380,394,417,406,413,388,393,414,417,417,391,395,417,413,410,390,396,409,413,408,378,381,394,412,405,381,393,397,395,396,364,375,363,378,371,336,324,312,292,110" />}}
{{< chart type="timeseries" title="Req/s count" >}}
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{{< tab tabName="Req duration" >}}
{{< chart type="timeseries" title="VUs count" datasets="VUs|1,1,1,2,2,2,3,3,3,4,4,4,5,5,5,6,6,6,7,7,7,8,8,8,9,9,8,8,8,8,9,9,9,9,9,9,10,10,9,10,10,10,11,11,11,11,11,11,12,12,12,12,12,12,13,13,12,13,13,13,14,13,13,13,12,12,12,12,12,12,11,11,11,10,10,10,10,9,9,9,8,8,7,7,6,6,6,5,4,3" />}}
{{< chart type="timeseries" title="VUs count" >}}
VUs|1,1,1,2,2,2,3,3,3,4,4,4,5,5,5,6,6,6,7,7,7,8,8,8,9,9,8,8,8,8,9,9,9,9,9,9,10,10,9,10,10,10,11,11,11,11,11,11,12,12,12,12,12,12,13,13,12,13,13,13,14,13,13,13,12,12,12,12,12,12,11,11,11,10,10,10,10,9,9,9,8,8,7,7,6,6,6,5,4,3
{{< /chart >}}
{{< chart type="timeseries" title="Request duration in ms" datasets="Duration (ms)|28,22,24,17,11,12,12,13,13,14,13,14,14,15,14,16,17,18,17,18,19,20,21,20,22,22,22,23,21,21,21,24,24,23,23,22,25,26,25,24,25,26,27,28,26,27,29,28,28,29,28,33,31,29,30,31,33,32,31,31,32,36,33,31,30,29,31,30,29,29,28,29,29,27,24,24,26,25,23,23,21,22,21,20,18,1" />}}
{{< chart type="timeseries" title="Request duration in ms" >}}
Duration (ms)|28,22,24,17,11,12,12,13,13,14,13,14,14,15,14,16,17,18,17,18,19,20,21,20,22,22,22,23,21,21,21,24,24,23,23,22,25,26,25,24,25,26,27,28,26,27,29,28,28,29,28,33,31,29,30,31,33,32,31,31,32,36,33,31,30,29,31,30,29,29,28,29,29,27,24,24,26,25,23,23,21,22,21,20,18,1
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{{< tab tabName="CPU load" >}}
{{< chart type="timeseries" title="CPU runtime load" datasets="User|0.03,0.42,0.56,0.59,0.59,0.58,0.48,0.03|#4bc0c0$System|0.02,0.24,0.32,0.31,0.36,0.34,0.27,0.02|#ff6384" stacked="true" max="1" step="15" />}}
{{< chart type="timeseries" title="CPU runtime load" stacked="true" max="1" step="15" >}}
User|0.03,0.42,0.56,0.59,0.59,0.58,0.48,0.03|#4bc0c0$System|0.02,0.24,0.32,0.31,0.36,0.34,0.27,0.02|#ff6384
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{{< chart type="timeseries" title="CPU database load" datasets="User|0.09,0.32,0.37,0.38,0.4,0.38,0.12,0.03|#4bc0c0$System|0.04,0.08,0.09,0.1,0.1,0.08,0.04,0.02|#ff6384" stacked="true" max="1" step="15" />}}
{{< chart type="timeseries" title="CPU database load" stacked="true" max="1" step="15" >}}
User|0.09,0.32,0.37,0.38,0.4,0.38,0.12,0.03|#4bc0c0$System|0.04,0.08,0.09,0.1,0.1,0.08,0.04,0.02|#ff6384
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@@ -461,22 +521,32 @@ The situation is completely different here, Symfony is able to handle the load,
| Max req/s | **120** |
| p(90) req duration | **469ms** |
{{< chart type="timeseries" title="Req/s count" datasets="Req/s|28,108,116,120,121,112,119,121,121,120,111,116,120,120,116,111,116,116,124,107,115,114,119,119,116,112,118,118,119,117,111,118,117,118,116,112,116,115,123,120,111,113,121,114,117,115,107,123,117,114,107,116,123,115,115,113,121,114,121,115,111,117,121,120,119,116,113,121,123,123,88" />}}
{{< chart type="timeseries" title="Req/s count" >}}
Req/s|28,108,116,120,121,112,119,121,121,120,111,116,120,120,116,111,116,116,124,107,115,114,119,119,116,112,118,118,119,117,111,118,117,118,116,112,116,115,123,120,111,113,121,114,117,115,107,123,117,114,107,116,123,115,115,113,121,114,121,115,111,117,121,120,119,116,113,121,123,123,88
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{{< tab tabName="Req duration" >}}
{{< chart type="timeseries" title="VUs count" datasets="VUs|3,6,9,12,12,13,14,16,17,19,19,20,22,23,24,25,27,28,29,31,33,33,35,36,38,38,39,41,43,44,46,46,48,48,50,49,47,50,50,50,49,50,49,50,50,49,50,47,49,49,49,49,48,48,50,48,50,50,50,47,48,47,44,41,37,36,32,27,23,17,5" />}}
{{< chart type="timeseries" title="VUs count" >}}
VUs|3,6,9,12,12,13,14,16,17,19,19,20,22,23,24,25,27,28,29,31,33,33,35,36,38,38,39,41,43,44,46,46,48,48,50,49,47,50,50,50,49,50,49,50,50,49,50,47,49,49,49,49,48,48,50,48,50,50,50,47,48,47,44,41,37,36,32,27,23,17,5
{{< /chart >}}
{{< chart type="timeseries" title="Request duration in ms" datasets="Duration (ms)|125,55,76,97,107,113,119,128,142,156,172,176,185,190,206,223,236,240,250,271,297,288,294,305,326,345,331,356,351,382,394,401,395,414,431,446,418,419,411,415,457,422,422,418,424,443,428,415,408,429,462,423,409,432,420,435,419,419,425,410,437,396,380,354,322,321,289,248,203,147,73" />}}
{{< chart type="timeseries" title="Request duration in ms" >}}
Duration (ms)|125,55,76,97,107,113,119,128,142,156,172,176,185,190,206,223,236,240,250,271,297,288,294,305,326,345,331,356,351,382,394,401,395,414,431,446,418,419,411,415,457,422,422,418,424,443,428,415,408,429,462,423,409,432,420,435,419,419,425,410,437,396,380,354,322,321,289,248,203,147,73
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{{< tab tabName="CPU load" >}}
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{{< chart type="timeseries" title="CPU runtime load" stacked="true" max="1" step="15" >}}
User|0.03,0.24,0.41,0.39,0.39,0.39,0.03,0.03|#4bc0c0$System|0.02,0.06,0.11,0.12,0.11,0.13,0.02,0.02|#ff6384
{{< /chart >}}
{{< chart type="timeseries" title="CPU database load" datasets="User|0.04,0.69,0.71,0.7,0.72,0.72,0.04,0.03|#4bc0c0$System|0.03,0.29,0.29,0.3,0.28,0.28,0.02,0.02|#ff6384" stacked="true" max="1" step="15" />}}
{{< chart type="timeseries" title="CPU database load" stacked="true" max="1" step="15" >}}
User|0.04,0.69,0.71,0.7,0.72,0.72,0.04,0.03|#4bc0c0$System|0.03,0.29,0.29,0.3,0.28,0.28,0.02,0.02|#ff6384
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@@ -496,22 +566,32 @@ Performance is strangely very similar with Laravel + MySQL on same scenario. Sym
| Max req/s | **250** |
| p(90) req duration | **95ms** |
{{< chart type="timeseries" title="Req/s count" datasets="Req/s|29,30,29,107,108,110,149,152,153,186,178,171,200,203,197,206,199,208,217,215,213,211,225,219,232,221,209,230,239,228,223,217,240,235,246,235,223,233,248,247,233,216,245,246,253,235,229,241,246,243,238,219,242,239,251,238,227,247,251,249,241,235,246,246,248,241,231,240,252,244,231,229,242,246,250,237,227,245,250,249,232,231,245,243,247,237,230,245,251,233" />}}
{{< chart type="timeseries" title="Req/s count" >}}
Req/s|29,30,29,107,108,110,149,152,153,186,178,171,200,203,197,206,199,208,217,215,213,211,225,219,232,221,209,230,239,228,223,217,240,235,246,235,223,233,248,247,233,216,245,246,253,235,229,241,246,243,238,219,242,239,251,238,227,247,251,249,241,235,246,246,248,241,231,240,252,244,231,229,242,246,250,237,227,245,250,249,232,231,245,243,247,237,230,245,251,233
{{< /chart >}}
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{{< tab tabName="Req duration" >}}
{{< chart type="timeseries" title="VUs count" datasets="VUs|1,1,1,2,2,2,3,3,3,4,4,4,5,5,5,6,6,6,7,7,7,8,8,8,9,9,9,10,10,10,11,11,11,12,12,12,13,13,13,14,14,14,15,15,15,16,16,16,17,17,17,18,18,18,19,19,19,20,20,20,20,20,19,19,19,18,18,18,18,18,18,18,18,18,18,18,18,18,17,17,17,17,17,17,17,17,17,17,17,16" />}}
{{< chart type="timeseries" title="VUs count" >}}
VUs|1,1,1,2,2,2,3,3,3,4,4,4,5,5,5,6,6,6,7,7,7,8,8,8,9,9,9,10,10,10,11,11,11,12,12,12,13,13,13,14,14,14,15,15,15,16,16,16,17,17,17,18,18,18,19,19,19,20,20,20,20,20,19,19,19,18,18,18,18,18,18,18,18,18,18,18,18,18,17,17,17,17,17,17,17,17,17,17,17,16
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{{< chart type="timeseries" title="Request duration in ms" datasets="Duration (ms)|34,34,34,19,18,18,20,19,19,21,22,23,25,24,25,29,30,29,32,32,33,38,35,37,39,41,43,43,42,43,49,50,46,51,48,51,57,56,53,56,60,64,62,60,60,68,70,66,68,70,72,80,75,74,76,79,83,82,79,80,82,82,81,76,76,79,77,74,72,74,77,77,75,73,72,76,78,74,72,68,73,74,69,70,68,72,72,70,67,68" />}}
{{< chart type="timeseries" title="Request duration in ms" >}}
Duration (ms)|34,34,34,19,18,18,20,19,19,21,22,23,25,24,25,29,30,29,32,32,33,38,35,37,39,41,43,43,42,43,49,50,46,51,48,51,57,56,53,56,60,64,62,60,60,68,70,66,68,70,72,80,75,74,76,79,83,82,79,80,82,82,81,76,76,79,77,74,72,74,77,77,75,73,72,76,78,74,72,68,73,74,69,70,68,72,72,70,67,68
{{< /chart >}}
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{{< tab tabName="CPU load" >}}
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{{< chart type="timeseries" title="CPU runtime load" stacked="true" max="1" step="15" >}}
User|0.12,0.55,0.67,0.71,0.73,0.73,0.29,0.03,0.03|#4bc0c0$System|0.05,0.17,0.2,0.21,0.22,0.2,0.09,0.01,0.02|#ff6384
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{{< chart type="timeseries" title="CPU database load" datasets="User|0.15,0.28,0.32,0.32,0.33,0.32,0.03,0.03,0.03|#4bc0c0$System|0.2,0.37,0.4,0.43,0.43,0.43,0.02,0.02,0.02|#ff6384" stacked="true" max="1" step="15" />}}
{{< chart type="timeseries" title="CPU database load" stacked="true" max="1" step="15" >}}
User|0.15,0.28,0.32,0.32,0.33,0.32,0.03,0.03,0.03|#4bc0c0$System|0.2,0.37,0.4,0.43,0.43,0.43,0.02,0.02,0.02|#ff6384
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@@ -535,22 +615,32 @@ As a side note here, uvicorn is limited to 1 CPU core, so I use 2 replicas on ea
| Max req/s | **550** |
| p(90) req duration | **49ms** |
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{{< chart type="timeseries" title="Req/s count" >}}
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{{< tab tabName="Req duration" >}}
{{< chart type="timeseries" title="VUs count" datasets="VUs|7,8,9,11,11,11,11,12,12,12,11,12,11,12,12,12,13,14,15,15,14,13,15,14,12,13,12,13,15,12,14,15,16,16,16,16,16,18,17,17,16,16,15,18,14,16,15,15,17,16,16,16,17,16,16,15,15,16,16,17" />}}
{{< chart type="timeseries" title="VUs count" >}}
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{{< chart type="timeseries" title="Request duration in ms" datasets="Duration (ms)|25,14,15,18,21,22,21,21,22,24,23,22,23,23,25,24,24,27,26,29,28,27,27,27,27,25,28,24,27,27,25,27,28,30,33,33,32,31,31,34,33,32,29,31,33,30,33,31,31,32,31,29,30,31,31,31,31,30,32,34,32,22" />}}
{{< chart type="timeseries" title="Request duration in ms" >}}
Duration (ms)|25,14,15,18,21,22,21,21,22,24,23,22,23,23,25,24,24,27,26,29,28,27,27,27,27,25,28,24,27,27,25,27,28,30,33,33,32,31,31,34,33,32,29,31,33,30,33,31,31,32,31,29,30,31,31,31,31,30,32,34,32,22
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{{< /tab >}}
{{< tab tabName="CPU load" >}}
{{< chart type="timeseries" title="CPU runtime load" datasets="User|0.03,0.02,0.63,0.66,0.64,0.64,0.03|#4bc0c0$System|0.01,0.01,0.13,0.13,0.15,0.14,0.02|#ff6384" stacked="true" max="1" step="15" />}}
{{< chart type="timeseries" title="CPU runtime load" stacked="true" max="1" step="15" >}}
User|0.03,0.02,0.63,0.66,0.64,0.64,0.03|#4bc0c0$System|0.01,0.01,0.13,0.13,0.15,0.14,0.02|#ff6384
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{{< chart type="timeseries" title="CPU database load" datasets="User|0.03,0.03,0.39,0.37,0.38,0.38,0.03|#4bc0c0$System|0.02,0.02,0.13,0.13,0.16,0.15,0.02|#ff6384" stacked="true" max="1" step="15" />}}
{{< chart type="timeseries" title="CPU database load" stacked="true" max="1" step="15" >}}
User|0.03,0.03,0.39,0.37,0.38,0.38,0.03|#4bc0c0$System|0.02,0.02,0.13,0.13,0.16,0.15,0.02|#ff6384
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@@ -570,22 +660,32 @@ Now we are talking, FastAPI outperforms above PHP frameworks, and database isn't
| Max req/s | **870** |
| p(90) req duration | **113ms** |
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{{< chart type="timeseries" title="Req/s count" >}}
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{{< chart type="timeseries" title="VUs count" >}}
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{{< chart type="timeseries" title="Request duration in ms" datasets="Duration (ms)|13,11,7,8,11,14,16,19,20,25,24,25,30,29,35,39,38,42,45,49,51,53,52,58,63,60,58,63,58,60,66,56,60,57,65,60,63,60,66,61,66,60,64,59,64,60,61,61,59,61,61,64,60,57,61,64,63,59,59,63,61,64,63,57,63,63,63,58,56,59,56,56,55,55,57,57,57,59,52,59,56,51,52,53,53,53,53,51,50,50,46" />}}
{{< chart type="timeseries" title="Request duration in ms" >}}
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{{< chart type="timeseries" title="CPU runtime load" stacked="true" max="1" step="15" >}}
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{{< chart type="timeseries" title="CPU database load" stacked="true" max="1" step="15" >}}
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@@ -607,22 +707,32 @@ FastAPI performs around twice better PHP main frameworks in every situation. I'm
| Max req/s | **700** |
| p(90) req duration | **Xms** |
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{{< chart type="timeseries" title="Req/s count" >}}
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{{< chart type="timeseries" title="VUs count" >}}
VUs|15,22,28,37,43,49,50,50,50,46,50,50,49,46,47,50,50,49,49,49,49,49,49,48,49,49,50,50,47,49,50,46,48,50,48,49,48,50,49,50,48,49,49,48,49,48,50,47,47,46,48,49,48,46,47,48,50,50,48,43,27
{{< /chart >}}
{{< chart type="timeseries" title="Request duration in ms" datasets="Duration (ms)|14,25,36,48,62,75,86,73,83,76,78,79,88,93,82,78,86,83,85,81,74,84,79,77,76,82,79,70,78,83,84,82,72,74,86,74,68,64,84,83,84,78,82,74,71,85,77,83,81,78,73,78,83,78,81,79,73,81,89,89,66,45,24" />}}
{{< chart type="timeseries" title="Request duration in ms" >}}
Duration (ms)|14,25,36,48,62,75,86,73,83,76,78,79,88,93,82,78,86,83,85,81,74,84,79,77,76,82,79,70,78,83,84,82,72,74,86,74,68,64,84,83,84,78,82,74,71,85,77,83,81,78,73,78,83,78,81,79,73,81,89,89,66,45,24
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{{< chart type="timeseries" title="CPU runtime load" stacked="true" max="1" step="15" >}}
User|0.06,0.05,0.42,0.43,0.44,0.42,0.04|#4bc0c0$System|0.02,0.08,0.56,0.53,0.51,0.55,0.02|#ff6384
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{{< chart type="timeseries" title="CPU database load" stacked="true" max="1" step="15" >}}
User|0.03,0.2,0.22,0.24,0.22,0.1,0.03|#4bc0c0$System|0.02,0.15,0.17,0.17,0.18,0.07,0.02|#ff6384
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@@ -642,22 +752,32 @@ It's even better than FastAPI, let's keep up on scenario 2.
| Max req/s | **1400** |
| p(90) req duration | **53ms** |
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{{< chart type="timeseries" title="Req/s count" >}}
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{{< tab tabName="Req duration" >}}
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{{< chart type="timeseries" title="VUs count" >}}
VUs|3,6,9,12,15,18,21,24,27,30,33,36,39,42,45,48,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,49,50,50,49,50,50,50,50,50,50,49,49,50,50,50,50,49,49,49,50,49,46,44,43,40,40,36,32,29,24,18,18,18,18,18,18,18,18,18,18,17,15,12,9,4
{{< /chart >}}
{{< chart type="timeseries" title="Request duration in ms" datasets="Duration (ms)|20,8,8,12,13,14,16,19,22,23,25,26,28,33,35,35,39,38,40,40,37,36,36,37,36,37,36,35,40,39,37,37,36,39,37,35,36,37,40,37,38,34,36,41,39,36,34,37,40,36,38,37,37,40,39,36,37,35,38,39,36,34,32,35,35,30,29,25,26,23,20,15,14,17,16,15,15,15,16,16,15,14,12,12,10,7,5" />}}
{{< chart type="timeseries" title="Request duration in ms" >}}
Duration (ms)|20,8,8,12,13,14,16,19,22,23,25,26,28,33,35,35,39,38,40,40,37,36,36,37,36,37,36,35,40,39,37,37,36,39,37,35,36,37,40,37,38,34,36,41,39,36,34,37,40,36,38,37,37,40,39,36,37,35,38,39,36,34,32,35,35,30,29,25,26,23,20,15,14,17,16,15,15,15,16,16,15,14,12,12,10,7,5
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{{< chart type="timeseries" title="CPU runtime load" stacked="true" max="1" step="15" >}}
User|0.03,0.43,0.47,0.45,0.45,0.45,0.35,0.02|#4bc0c0$System|0.02,0.54,0.52,0.52,0.52,0.52,0.57,0.02|#ff6384
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{{< chart type="timeseries" title="CPU database load" datasets="User|0.08,0.37,0.39,0.37,0.38,0.34,0.17,0.04|#4bc0c0$System|0.01,0.27,0.31,0.32,0.31,0.28,0.11,0.02|#ff6384" stacked="true" max="1" step="15" />}}
{{< chart type="timeseries" title="CPU database load" stacked="true" max="1" step="15" >}}
User|0.08,0.37,0.39,0.37,0.38,0.34,0.17,0.04|#4bc0c0$System|0.01,0.27,0.31,0.32,0.31,0.28,0.11,0.02|#ff6384
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@@ -679,22 +799,32 @@ What can I say, NestJS is the clear winner so far. The native even loop system m
| Max req/s | **500** |
| p(90) req duration | **161ms** |
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{{< chart type="timeseries" title="Req/s count" >}}
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{{< chart type="timeseries" title="VUs count" >}}
VUs|10,13,16,16,19,23,24,26,24,28,31,31,32,34,35,37,38,39,41,41,44,48,47,48,50,45,48,46,47,46,48,48,48,47,49,49,50,48,47,50,49,46,47,48,49,45,46,49,47,48,50,46,48,48,48,48,48,48,47,48,39,24
{{< /chart >}}
{{< chart type="timeseries" title="Request duration in ms" datasets="Duration (ms)|21,22,28,31,36,43,48,50,51,54,61,62,63,66,67,74,78,77,87,87,89,97,95,96,104,107,93,97,93,92,101,101,95,98,102,107,101,99,103,99,108,105,100,106,98,109,94,97,101,100,106,105,95,97,100,103,101,99,98,99,105,93,58,24" />}}
{{< chart type="timeseries" title="Request duration in ms" >}}
Duration (ms)|21,22,28,31,36,43,48,50,51,54,61,62,63,66,67,74,78,77,87,87,89,97,95,96,104,107,93,97,93,92,101,101,95,98,102,107,101,99,103,99,108,105,100,106,98,109,94,97,101,100,106,105,95,97,100,103,101,99,98,99,105,93,58,24
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{{< chart type="timeseries" title="CPU runtime load" stacked="true" max="1" step="15" >}}
User|0.03,0.06,0.18,0.2,0.18,0.19,0.03|#4bc0c0$System|0.02,0.06,0.24,0.25,0.25,0.25,0.02|#ff6384
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{{< chart type="timeseries" title="CPU database load" datasets="User|0.03,0.41,0.42,0.44,0.45,0.15,0.03|#4bc0c0$System|0.02,0.49,0.51,0.51,0.5,0.19,0.02|#ff6384" stacked="true" max="1" step="15" />}}
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@@ -714,22 +844,32 @@ Database is the bottleneck again, java runtime is clearly sleeping here, while p
| Max req/s | **2600** |
| p(90) req duration | **38ms** |
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{{< chart type="timeseries" title="Req/s count" >}}
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{{< chart type="timeseries" title="CPU database load" stacked="true" max="1" step="15" >}}
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@@ -751,22 +891,32 @@ Java is maybe not the best DX experience for me, but it's a beast in terms of ra
| Max req/s | **980** |
| p(90) req duration | **87ms** |
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{{< chart type="timeseries" title="Req/s count" >}}
Req/s|18,742,920,880,882,977,984,976,947,927,962,967,979,955,911,954,965,1005,957,918,904,986,973,974,892,969,973,988,917,900,973,975,972,953,928,963,997,975,971,884,954,977,950,965,923,942,976,968,972,885,959,960,974,948,890,952,973,986,953,914,973,947,102
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{{< chart type="timeseries" title="VUs count" datasets="VUs|13,20,24,28,34,36,37,38,43,43,47,50,47,48,49,49,46,48,48,47,48,47,47,45,50,48,44,49,49,48,47,48,44,47,48,47,46,48,48,48,45,46,45,47,48,47,47,49,49,45,49,46,46,43,50,42,44,44,50,48,20" />}}
{{< chart type="timeseries" title="VUs count" >}}
VUs|13,20,24,28,34,36,37,38,43,43,47,50,47,48,49,49,46,48,48,47,48,47,47,45,50,48,44,49,49,48,47,48,44,47,48,47,46,48,48,48,45,46,45,47,48,47,47,49,49,45,49,46,46,43,50,42,44,44,50,48,20
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{{< chart type="timeseries" title="Request duration in ms" datasets="Duration (ms)|12,14,18,26,30,33,34,37,39,44,45,48,48,48,52,50,49,45,49,52,52,48,50,45,53,50,49,46,50,55,50,47,48,49,50,49,46,47,49,53,51,47,47,48,50,51,49,48,49,53,49,49,48,48,50,51,44,43,47,51,50,33,9" />}}
{{< chart type="timeseries" title="Request duration in ms" >}}
Duration (ms)|12,14,18,26,30,33,34,37,39,44,45,48,48,48,52,50,49,45,49,52,52,48,50,45,53,50,49,46,50,55,50,47,48,49,50,49,46,47,49,53,51,47,47,48,50,51,49,48,49,53,49,49,48,48,50,51,44,43,47,51,50,33,9
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{{< chart type="timeseries" title="CPU runtime load" stacked="true" max="1" step="15" >}}
User|0.03,0.03,0.43,0.46,0.46,0.46,0.11|#4bc0c0$System|0.01,0.01,0.18,0.2,0.21,0.2,0.05|#ff6384
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{{< chart type="timeseries" title="CPU database load" stacked="true" max="1" step="15" >}}
User|0.03,0.04,0.78,0.76,0.76,0.76,0.03|#4bc0c0$System|0.02,0.02,0.21,0.24,0.23,0.22,0.02|#ff6384
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@@ -786,20 +936,28 @@ ASP.NET Core is the final winner of 1st scenario. EF Core is incredibly efficien
| Max req/s | **2500** |
| p(90) req duration | **38ms** |
{{< chart type="timeseries" title="Req/s count" datasets="Req/s|205,1130,1622,1790,2011,2135,2024,2093,2463,2465,2428,2385,2144,2460,2503,2551,2337,2200,2404,2379,2452,2322,2252,2462,2449,2469,2306,2230,2488,2554,2466,2253,2180,2426,2445,2502,2349,2196,2476,2343,2538,2341,2166,2499,2412,2452,2259,2137,2439,2474,2461,2302,2113,2479,2374,2421,2369,2221,2462,2409,2332,2382,2216,2394,2478,2341,1644,1934,2134,2266,2070,1598,1417,1505,1518,710" />}}
{{< chart type="timeseries" title="Req/s count" >}}
Req/s|205,1130,1622,1790,2011,2135,2024,2093,2463,2465,2428,2385,2144,2460,2503,2551,2337,2200,2404,2379,2452,2322,2252,2462,2449,2469,2306,2230,2488,2554,2466,2253,2180,2426,2445,2502,2349,2196,2476,2343,2538,2341,2166,2499,2412,2452,2259,2137,2439,2474,2461,2302,2113,2479,2374,2421,2369,2221,2462,2409,2332,2382,2216,2394,2478,2341,1644,1934,2134,2266,2070,1598,1417,1505,1518,710
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{{< chart type="timeseries" title="VUs count" datasets="VUs|5,10,15,21,25,30,35,40,45,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,49,49,50,50,50,50,48,49,50,50,49,50,48,50,47,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,49,50,50,48,49,47,46,44,42,39,37,34,31,21,13,8,8,8,4" />}}
{{< chart type="timeseries" title="VUs count" >}}
VUs|5,10,15,21,25,30,35,40,45,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,49,49,50,50,50,50,48,49,50,50,49,50,48,50,47,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,49,50,50,48,49,47,46,44,42,39,37,34,31,21,13,8,8,8,4
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{{< chart type="timeseries" title="Request duration in ms" datasets="Duration (ms)|6,5,7,9,10,12,15,17,17,18,20,21,23,20,20,19,21,23,21,21,20,21,22,20,20,20,21,22,20,19,20,22,23,20,20,20,21,22,20,21,19,21,23,20,21,20,22,23,21,20,20,22,23,20,21,21,21,22,20,21,21,20,21,19,18,18,24,19,16,13,10,8,5,5,5,4" />}}
{{< chart type="timeseries" title="Request duration in ms" >}}
Duration (ms)|6,5,7,9,10,12,15,17,17,18,20,21,23,20,20,19,21,23,21,21,20,21,22,20,20,20,21,22,20,19,20,22,23,20,20,20,21,22,20,21,19,21,23,20,21,20,22,23,21,20,20,22,23,20,21,21,21,22,20,21,21,20,21,19,18,18,24,19,16,13,10,8,5,5,5,4
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{{< chart type="timeseries" title="CPU runtime load" stacked="true" max="1" step="15" >}}
User|0.03,0.6,0.6,0.61,0.64,0.47,0.02|#4bc0c0$System|0.01,0.3,0.29,0.3,0.29,0.29,0.02|#ff6384
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{{< chart type="timeseries" title="CPU database load" stacked="true" max="1" step="15" >}}
User|0.2,0.55,0.54,0.53,0.53,0.15,0.03|#4bc0c0$System|0.14,0.34,0.34,0.34,0.34,0.09,0.02|#ff6384