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Refactor Prometheus and Add Request Level Metrics (#2316)

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Robert Shaw
2024-01-31 14:58:07 -08:00
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commit 93b38bea5d
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examples/production_monitoring/README.md Normal file
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# vLLM + Prometheus/Grafana
This is a simple example that shows you how to connect vLLM metric logging to the Prometheus/Grafana stack. For this example, we launch Prometheus and Grafana via Docker. You can checkout other methods through [Prometheus](https://prometheus.io/) and [Grafana](https://grafana.com/) websites.
Install:
- [`docker`](https://docs.docker.com/engine/install/)
- [`docker compose`](https://docs.docker.com/compose/install/linux/#install-using-the-repository)
### Launch
Prometheus metric logging is enabled by default in the OpenAI-compatible server. Launch via the entrypoint:
```bash
python3 -m vllm.entrypoints.openai.api_server \
--model mistralai/Mistral-7B-v0.1 \
--max-model-len 2048 \
--disable-log-requests
```
Launch Prometheus and Grafana servers with `docker compose`:
```bash
docker compose up
```
Submit some sample requests to the server:
```bash
wget https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/resolve/main/ShareGPT_V3_unfiltered_cleaned_split.json
python3 ../../benchmarks/benchmark_serving.py \
--model mistralai/Mistral-7B-v0.1 \
--tokenizer mistralai/Mistral-7B-v0.1 \
--endpoint /v1/completions \
--dataset ShareGPT_V3_unfiltered_cleaned_split.json \
--request-rate 3.0
```
Navigating to [`http://localhost:8000/metrics`](http://localhost:8000/metrics) will show the raw Prometheus metrics being exposed by vLLM.
### Grafana Dashboard
Navigate to [`http://localhost:3000`](http://localhost:3000). Log in with the default username (`admin`) and password (`admin`).
#### Add Prometheus Data Source
Navigate to [`http://localhost:3000/connections/datasources/new`](http://localhost:3000/connections/datasources/new) and select Prometheus.
On Prometheus configuration page, we need to add the `Prometheus Server URL` in `Connection`. For this setup, Grafana and Prometheus are running in separate containers, but Docker creates DNS name for each containers. You can just use `http://prometheus:9090`.
Click `Save & Test`. You should get a green check saying "Successfully queried the Prometheus API.".
#### Import Dashboard
Navigate to [`http://localhost:3000/dashboard/import`](http://localhost:3000/dashboard/import), upload `grafana.json`, and select the `prometheus` datasource. You should see a screen that looks like the following:
![Grafana Dashboard Image](https://i.imgur.com/R2vH9VW.png)

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examples/production_monitoring/docker-compose.yaml Normal file
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# docker-compose.yaml
version: "3"
services:
prometheus:
image: prom/prometheus:latest
extra_hosts:
- "host.docker.internal:host-gateway" # allow a direct connection from container to the local machine
ports:
- "9090:9090" # the default port used by Prometheus
volumes:
- ${PWD}/prometheus.yaml:/etc/prometheus/prometheus.yml # mount Prometheus config file
grafana:
image: grafana/grafana:latest
depends_on:
- prometheus
ports:
- "3000:3000" # the default port used by Grafana

931
examples/production_monitoring/grafana.json Normal file
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{
"__inputs": [
{
"name": "DS_PROMETHEUS",
"label": "prometheus",
"description": "",
"type": "datasource",
"pluginId": "prometheus",
"pluginName": "Prometheus"
}
],
"__elements": {},
"__requires": [
{
"type": "grafana",
"id": "grafana",
"name": "Grafana",
"version": "10.2.3"
},
{
"type": "datasource",
"id": "prometheus",
"name": "Prometheus",
"version": "1.0.0"
},
{
"type": "panel",
"id": "timeseries",
"name": "Time series",
"version": ""
}
],
"annotations": {
"list": [
{
"builtIn": 1,
"datasource": {
"type": "grafana",
"uid": "-- Grafana --"
},
"enable": true,
"hide": true,
"iconColor": "rgba(0, 211, 255, 1)",
"name": "Annotations & Alerts",
"type": "dashboard"
}
]
},
"description": "Monitoring vLLM Inference Server",
"editable": true,
"fiscalYearStartMonth": 0,
"graphTooltip": 0,
"id": null,
"links": [],
"liveNow": false,
"panels": [
{
"datasource": {
"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
"description": "End to end request latency measured in seconds.",
"fieldConfig": {
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"barAlignment": 0,
"drawStyle": "line",
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"gradientMode": "none",
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"viz": false
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"insertNulls": false,
"lineInterpolation": "linear",
"lineWidth": 1,
"pointSize": 5,
"scaleDistribution": {
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},
"showPoints": "auto",
"spanNulls": false,
"stacking": {
"group": "A",
"mode": "none"
},
"thresholdsStyle": {
"mode": "off"
}
},
"mappings": [],
"thresholds": {
"mode": "absolute",
"steps": [
{
"color": "green",
"value": null
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{
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"value": 80
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]
},
"unit": "s"
},
"overrides": []
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"gridPos": {
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"w": 12,
"x": 0,
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"id": 9,
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},
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"fullMetaSearch": false,
"includeNullMetadata": false,
"instant": false,
"legendFormat": "P99",
"range": true,
"refId": "A",
"useBackend": false
},
{
"datasource": {
"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
"disableTextWrap": false,
"editorMode": "builder",
"expr": "histogram_quantile(0.95, sum by(le) (rate(vllm:e2e_request_latency_seconds_bucket[$__rate_interval])))",
"fullMetaSearch": false,
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{
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"expr": "histogram_quantile(0.9, sum by(le) (rate(vllm:e2e_request_latency_seconds_bucket[$__rate_interval])))",
"fullMetaSearch": false,
"hide": false,
"includeNullMetadata": false,
"instant": false,
"legendFormat": "P90",
"range": true,
"refId": "C",
"useBackend": false
},
{
"datasource": {
"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
"disableTextWrap": false,
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"expr": "histogram_quantile(0.5, sum by(le) (rate(vllm:e2e_request_latency_seconds_bucket[$__rate_interval])))",
"fullMetaSearch": false,
"hide": false,
"includeNullMetadata": false,
"instant": false,
"legendFormat": "P50",
"range": true,
"refId": "D",
"useBackend": false
},
{
"datasource": {
"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
"editorMode": "code",
"expr": "rate(vllm:e2e_request_latency_seconds_sum[$__rate_interval])\n/\nrate(vllm:e2e_request_latency_seconds_count[$__rate_interval])",
"hide": false,
"instant": false,
"legendFormat": "Average",
"range": true,
"refId": "E"
}
],
"title": "E2E Request Latency",
"type": "timeseries"
},
{
"datasource": {
"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
"description": "Number of tokens processed per second",
"fieldConfig": {
"defaults": {
"color": {
"mode": "palette-classic"
},
"custom": {
"axisBorderShow": false,
"axisCenteredZero": false,
"axisColorMode": "text",
"axisLabel": "",
"axisPlacement": "auto",
"barAlignment": 0,
"drawStyle": "line",
"fillOpacity": 0,
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"hideFrom": {
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{
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"targets": [
{
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"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
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"expr": "rate(vllm:prompt_tokens_total[$__rate_interval])",
"fullMetaSearch": false,
"includeNullMetadata": false,
"instant": false,
"legendFormat": "Prompt Tokens/Sec",
"range": true,
"refId": "A",
"useBackend": false
},
{
"datasource": {
"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
"disableTextWrap": false,
"editorMode": "builder",
"expr": "rate(vllm:generation_tokens_total[$__rate_interval])",
"fullMetaSearch": false,
"hide": false,
"includeNullMetadata": false,
"instant": false,
"legendFormat": "Generation Tokens/Sec",
"range": true,
"refId": "B",
"useBackend": false
}
],
"title": "Token Throughput",
"type": "timeseries"
},
{
"datasource": {
"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
"description": "Inter token latency in seconds.",
"fieldConfig": {
"defaults": {
"color": {
"mode": "palette-classic"
},
"custom": {
"axisBorderShow": false,
"axisCenteredZero": false,
"axisColorMode": "text",
"axisLabel": "",
"axisPlacement": "auto",
"barAlignment": 0,
"drawStyle": "line",
"fillOpacity": 0,
"gradientMode": "none",
"hideFrom": {
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"tooltip": false,
"viz": false
},
"insertNulls": false,
"lineInterpolation": "linear",
"lineWidth": 1,
"pointSize": 5,
"scaleDistribution": {
"type": "linear"
},
"showPoints": "auto",
"spanNulls": false,
"stacking": {
"group": "A",
"mode": "none"
},
"thresholdsStyle": {
"mode": "off"
}
},
"mappings": [],
"thresholds": {
"mode": "absolute",
"steps": [
{
"color": "green",
"value": null
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{
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"value": 80
}
]
},
"unit": "s"
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}
},
"targets": [
{
"datasource": {
"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
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{
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"refId": "E"
}
],
"title": "Time Per Output Token Latency",
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"uid": "${DS_PROMETHEUS}"
},
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{
"datasource": {
"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
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"fullMetaSearch": false,
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"refId": "A",
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},
{
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"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
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"legendFormat": "Num Swapped",
"range": true,
"refId": "B",
"useBackend": false
},
{
"datasource": {
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},
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"refId": "C",
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},
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"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
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{
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"uid": "${DS_PROMETHEUS}"
},
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"expr": "histogram_quantile(0.5, sum by(le) (rate(vllm:time_to_first_token_seconds_bucket[$__rate_interval])))",
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"legendFormat": "P50",
"range": true,
"refId": "D",
"useBackend": false
},
{
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"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
"editorMode": "code",
"expr": "rate(vllm:time_to_first_token_seconds_sum[$__rate_interval])\n/\nrate(vllm:time_to_first_token_seconds_count[$__rate_interval])",
"hide": false,
"instant": false,
"legendFormat": "Average",
"range": true,
"refId": "E"
}
],
"title": "Time To First Token Latency",
"type": "timeseries"
},
{
"datasource": {
"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
"description": "Percentage of used cache blocks by vLLM.",
"fieldConfig": {
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"lineWidth": 1,
"pointSize": 5,
"scaleDistribution": {
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},
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"stacking": {
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"mode": "none"
},
"thresholdsStyle": {
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}
},
"mappings": [],
"thresholds": {
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"steps": [
{
"color": "green",
"value": null
},
{
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"value": 80
}
]
},
"unit": "percentunit"
},
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"y": 16
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}
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"targets": [
{
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},
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"expr": "vllm:gpu_cache_usage_perc",
"instant": false,
"legendFormat": "GPU Cache Usage",
"range": true,
"refId": "A"
},
{
"datasource": {
"type": "prometheus",
"uid": "${DS_PROMETHEUS}"
},
"editorMode": "code",
"expr": "vllm:cpu_cache_usage_perc",
"hide": false,
"instant": false,
"legendFormat": "CPU Cache Usage",
"range": true,
"refId": "B"
}
],
"title": "Cache Utilization",
"type": "timeseries"
}
],
"refresh": "",
"schemaVersion": 39,
"tags": [],
"templating": {
"list": []
},
"time": {
"from": "now-5m",
"to": "now"
},
"timepicker": {},
"timezone": "",
"title": "vLLM",
"uid": "b281712d-8bff-41ef-9f3f-71ad43c05e9b",
"version": 2,
"weekStart": ""
}

10
examples/production_monitoring/prometheus.yaml Normal file
View File

@@ -0,0 +1,10 @@
# prometheus.yaml
global:
scrape_interval: 5s
evaluation_interval: 30s
scrape_configs:
- job_name: vllm
static_configs:
- targets:
- 'host.docker.internal:8000'