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Refactor Prometheus and Add Request Level Metrics (vllm-project#2316)
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robertgshaw2-neuralmagic authored and jimpang committed Feb 20, 2024
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54 changes: 54 additions & 0 deletions examples/production_monitoring/README.md
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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)
19 changes: 19 additions & 0 deletions examples/production_monitoring/docker-compose.yaml
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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
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