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update remarks

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Adrien Beaudouin
2023-12-28 21:19:05 +01:00
parent b06875819f
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content/posts/22-web-api-benchmarks-2024/index.md
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@ -551,7 +551,7 @@ vus_max........................: 50 min=50 max=50
{{< /tab >}}
{{< /tabs >}}
Now we have a very runtime intensive scenario, with workers as bottleneck, API is keeping up with a low response time (~100ms).
Now we have a very runtime intensive scenario, with workers as bottleneck, database not very loaded, API is keeping up with a low response time (~100ms).
#### Laravel PgSQL scenario 1
@ -703,7 +703,7 @@ vus_max........................: 50 min=50 max=50
{{< /tab >}}
{{< /tabs >}}
Laravel performs slightly better than MySQL in this scenario, and we are not limited by database, contrary with MySQL.
Laravel performs slightly better than MySQL in this scenario, and we are not limited by database this time.
#### Laravel PgSQL scenario 2
@ -1011,7 +1011,7 @@ vus_max........................: 50 min=50 max=50
{{< /tab >}}
{{< /tabs >}}
It's slightly better than Laravel in this case, with a lower response time.
It's very similar to Laravel.
#### Symfony MySQL scenario 2
@ -1167,7 +1167,7 @@ vus_max........................: 50 min=50 max=50
{{< /tab >}}
{{< /tabs >}}
Symfony is able to handle the load, still better than Laravel in the same context. Let's see if it's able to keep up with the same performance with PostgreSQL.
Similar to Laravel too, just slightly better in the same context. Let's see if it's able to keep up with the same performance with PostgreSQL.
#### Symfony PgSQL scenario 1
@ -1319,7 +1319,7 @@ vus_max........................: 50 min=50 max=50
{{< /tab >}}
{{< /tabs >}}
Symfony performs same with PostgreSQL and MySQL, and performing a little less than Laravel when using PostgreSQL.
Symfony performs same with PostgreSQL and MySQL, but we are limited by database contrary to Laravel case, and performing a little less.
#### Symfony PgSQL scenario 2
@ -1481,26 +1481,27 @@ As a side note here, uvicorn is limited to 1 CPU core, so I use 2 replicas on ea
#### FastAPI PgSQL scenario 1
Iteration creation rate = **10/s**
Iteration creation rate = **15/s**
```txt
checks.........................: 100.00% ✓ 30651 ✗ 0
data_received..................: 252 MB 4.1 MB/s
data_sent......................: 2.7 MB 44 kB/s
http_req_blocked...............: avg=45.12µs min=239ns med=907ns max=71.16ms p(90)=1.34µs p(95)=1.51µs
http_req_connecting............: avg=1.92µs min=0s med=0s max=5.95ms p(90)=0s p(95)=0s
http_req_duration..............: avg=26.35ms min=5.08ms med=20.98ms max=250.92ms p(90)=46.63ms p(95)=62.58ms
{ expected_response:true }...: avg=26.35ms min=5.08ms med=20.98ms max=250.92ms p(90)=46.63ms p(95)=62.58ms
http_req_failed................: 0.00% ✓ 0 ✗ 30651
http_req_receiving.............: avg=371.83µs min=18.19µs med=199.55µs max=38.83ms p(90)=649.07µs p(95)=1.14ms
http_req_sending...............: avg=138.43µs min=17.16µs med=98.68µs max=21.62ms p(90)=171.16µs p(95)=225.32µs
http_req_tls_handshaking.......: avg=40.7µs min=0s med=0s max=47.82ms p(90)=0s p(95)=0s
http_req_waiting...............: avg=25.84ms min=1.21ms med=20.49ms max=250.26ms p(90)=45.93ms p(95)=61.85ms
http_reqs......................: 30651 503.353918/s
iteration_duration.............: avg=1.37s min=809.38ms med=1.36s max=1.99s p(90)=1.62s p(95)=1.7s
iterations.....................: 601 9.869685/s
vus............................: 14 min=10 max=17
vus_max........................: 50 min=50 max=50
checks.........................: 100.00% ✓ 33048 ✗ 0
data_received..................: 272 MB 4.3 MB/s
data_sent......................: 2.9 MB 46 kB/s
dropped_iterations.............: 253 4.042284/s
http_req_blocked...............: avg=44.03µs min=197ns med=873ns max=51.66ms p(90)=1.31µs p(95)=1.48µs
http_req_connecting............: avg=1.59µs min=0s med=0s max=3.33ms p(90)=0s p(95)=0s
http_req_duration..............: avg=87.55ms min=5.74ms med=79.16ms max=449.45ms p(90)=160.7ms p(95)=187.45ms
{ expected_response:true }...: avg=87.55ms min=5.74ms med=79.16ms max=449.45ms p(90)=160.7ms p(95)=187.45ms
http_req_failed................: 0.00% ✓ 0 ✗ 33048
http_req_receiving.............: avg=809.01µs min=18.38µs med=273.27µs max=53.15ms p(90)=1.95ms p(95)=3.12ms
http_req_sending...............: avg=156.85µs min=23.21µs med=95.41µs max=45.6ms p(90)=181.16µs p(95)=248.5µs
http_req_tls_handshaking.......: avg=40.32µs min=0s med=0s max=44.77ms p(90)=0s p(95)=0s
http_req_waiting...............: avg=86.59ms min=0s med=78.14ms max=448.54ms p(90)=159.53ms p(95)=186.05ms
http_reqs......................: 33048 528.02138/s
iteration_duration.............: avg=4.49s min=1.14s med=4.65s max=6.25s p(90)=5.17s p(95)=5.3s
iterations.....................: 648 10.35336/s
vus............................: 22 min=15 max=50
vus_max........................: 50 min=50 max=50
```
{{< tabs >}}
@ -1511,13 +1512,13 @@ vus_max........................: 50 min=50 max=50
{
label: 'Req/s',
data: [
145, 483, 466, 539, 474, 513, 506, 490, 544,
491, 527, 502, 465, 528, 521, 508, 505, 460,
508, 494, 508, 499, 511, 547, 505, 525, 487,
522, 488, 532, 522, 461, 523, 507, 528, 540,
474, 497, 525, 504, 550, 496, 528, 519, 541,
521, 484, 502, 494, 540, 522, 491, 515, 478,
557, 493, 529, 502, 467, 527, 480, 41
270, 514, 530, 535, 552, 541, 524, 493, 545,
555, 560, 539, 519, 545, 540, 531, 525, 514,
547, 540, 537, 533, 485, 511, 534, 525, 508,
500, 550, 527, 538, 516, 500, 542, 532, 530,
504, 508, 540, 538, 553, 537, 497, 560, 517,
578, 559, 487, 551, 546, 538, 531, 517, 518,
578, 559, 521, 516, 556, 567, 517, 517, 351
]
}
]
@ -1532,11 +1533,12 @@ vus_max........................: 50 min=50 max=50
{
label: 'VUs',
data: [
10, 11, 11, 11, 12, 13, 14, 14, 11, 12, 11, 13,
14, 13, 13, 14, 13, 13, 16, 17, 15, 17, 16, 15,
15, 13, 15, 15, 15, 14, 14, 15, 16, 15, 15, 13,
15, 15, 15, 14, 12, 14, 13, 13, 13, 13, 12, 13,
13, 13, 11, 12, 13, 13, 13, 13, 11, 12, 14, 14
15, 23, 31, 41, 46, 50, 50, 50, 48, 49, 50, 48,
48, 45, 49, 50, 49, 48, 50, 49, 50, 49, 49, 50,
50, 50, 50, 48, 50, 47, 49, 48, 48, 49, 49, 50,
48, 48, 50, 49, 49, 50, 48, 48, 49, 48, 45, 50,
48, 49, 49, 48, 47, 50, 49, 50, 48, 47, 50, 48,
39, 22
]
}
]
@ -1547,12 +1549,12 @@ vus_max........................: 50 min=50 max=50
{
label: 'Duration (ms)',
data: [
17, 18, 22, 20, 22, 23, 24, 26, 24, 24, 23, 24,
27, 26, 25, 24, 26, 29, 28, 29, 32, 31, 32, 30,
29, 28, 29, 29, 31, 29, 28, 32, 30, 29, 30, 27,
30, 31, 30, 29, 27, 28, 27, 25, 25, 24, 25, 24,
25, 25, 23, 25, 24, 28, 24, 24, 23, 23, 28, 26,
22, 10
20, 33, 45, 65, 74, 88, 93, 96, 90, 89, 90, 92,
94, 91, 89, 91, 91, 95, 90, 93, 92, 93, 101, 93,
90, 94, 96, 101, 87, 92, 89, 96, 98, 91, 91, 93,
94, 97, 92, 90, 88, 91, 95, 91, 93, 86, 88, 94,
89, 91, 90, 92, 93, 92, 87, 86, 94, 90, 91, 86,
86, 63, 36
]
}
]
@ -1566,11 +1568,11 @@ vus_max........................: 50 min=50 max=50
{
label: 'User',
data: [
0.03, 0.03, 0.45, 0.64,
0.63, 0.63, 0.64, 0.65,
0.65, 0.64, 0.67, 0.64,
0.65, 0.65, 0.24, 0.03,
0.02, 0.02, 0.02
0.03, 0.02, 0.52, 0.71,
0.74, 0.73, 0.71, 0.69,
0.71, 0.73, 0.73, 0.75,
0.71, 0.74, 0.5, 0.04,
0.03, 0.03, 0.02
],
borderColor: '#4bc0c0',
backgroundColor: '#4bc0c0',
@ -1579,10 +1581,10 @@ vus_max........................: 50 min=50 max=50
{
label: 'System',
data: [
0.01, 0.02, 0.09, 0.13,
0.13, 0.14, 0.15, 0.14,
0.13, 0.15, 0.13, 0.14,
0.13, 0.13, 0.07, 0.02,
0.01, 0.01, 0.12, 0.15,
0.15, 0.15, 0.15, 0.17,
0.16, 0.15, 0.15, 0.15,
0.15, 0.15, 0.11, 0.02,
0.01, 0.01, 0.01
],
borderColor: '#ff6384',
@ -1597,11 +1599,11 @@ vus_max........................: 50 min=50 max=50
{
label: 'User',
data: [
0.03, 0.25, 0.38, 0.36,
0.38, 0.38, 0.37, 0.37,
0.37, 0.37, 0.36, 0.37,
0.36, 0.19, 0.03, 0.03,
0.03, 0.03, 0.04
0.03, 0.3, 0.46, 0.47,
0.47, 0.48, 0.47, 0.48,
0.49, 0.49, 0.49, 0.46,
0.49, 0.35, 0.03, 0.03,
0.03, 0.03, 0.03
],
borderColor: '#4bc0c0',
backgroundColor: '#4bc0c0',
@ -1610,11 +1612,11 @@ vus_max........................: 50 min=50 max=50
{
label: 'System',
data: [
0.01, 0.09, 0.12, 0.14,
0.14, 0.15, 0.15, 0.15,
0.15, 0.15, 0.14, 0.12,
0.13, 0.06, 0.02, 0.02,
0.02, 0.02, 0.01
0.01, 0.11, 0.25, 0.25,
0.3, 0.27, 0.27, 0.25,
0.29, 0.28, 0.28, 0.26,
0.29, 0.19, 0.02, 0.02,
0.02, 0.01, 0.01
],
borderColor: '#ff6384',
backgroundColor: '#ff6384',
@ -1936,7 +1938,7 @@ vus_max........................: 50 min=50 max=50
{{< /tab >}}
{{< /tabs >}}
It's slightly better than FastAPI, let's keep up on scenario 2.
It's slightly better than FastAPI, and database is strangely sleeping far more than with FastAPI, let's keep up on scenario 2.
#### NestJS PgSQL scenario 2
@ -2750,13 +2752,13 @@ Here are the final req/s results for each framework. I choose to take MySQL resu
borderColor: '#0f766e',
backgroundColor: '#0f766e',
data: [
145, 483, 466, 539, 474, 513, 506, 490, 544,
491, 527, 502, 465, 528, 521, 508, 505, 460,
508, 494, 508, 499, 511, 547, 505, 525, 487,
522, 488, 532, 522, 461, 523, 507, 528, 540,
474, 497, 525, 504, 550, 496, 528, 519, 541,
521, 484, 502, 494, 540, 522, 491, 515, 478,
557, 493, 529, 502, 467, 527, 480, 41
270, 514, 530, 535, 552, 541, 524, 493, 545,
555, 560, 539, 519, 545, 540, 531, 525, 514,
547, 540, 537, 533, 485, 511, 534, 525, 508,
500, 550, 527, 538, 516, 500, 542, 532, 530,
504, 508, 540, 538, 553, 537, 497, 560, 517,
578, 559, 487, 551, 546, 538, 531, 517, 518,
578, 559, 521, 516, 556, 567, 517, 517, 351
]
},
{