vllm/docs/source/serving/metrics.md
Harry Mellor dd6a3a02cb
[Doc] Convert docs to use colon fences (#12471)
Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
2025-01-29 11:38:29 +08:00

1.6 KiB

Production Metrics

vLLM exposes a number of metrics that can be used to monitor the health of the system. These metrics are exposed via the /metrics endpoint on the vLLM OpenAI compatible API server.

You can start the server using Python, or using Docker:

vllm serve unsloth/Llama-3.2-1B-Instruct

Then query the endpoint to get the latest metrics from the server:

$ curl http://0.0.0.0:8000/metrics

# HELP vllm:iteration_tokens_total Histogram of number of tokens per engine_step.
# TYPE vllm:iteration_tokens_total histogram
vllm:iteration_tokens_total_sum{model_name="unsloth/Llama-3.2-1B-Instruct"} 0.0
vllm:iteration_tokens_total_bucket{le="1.0",model_name="unsloth/Llama-3.2-1B-Instruct"} 3.0
vllm:iteration_tokens_total_bucket{le="8.0",model_name="unsloth/Llama-3.2-1B-Instruct"} 3.0
vllm:iteration_tokens_total_bucket{le="16.0",model_name="unsloth/Llama-3.2-1B-Instruct"} 3.0
vllm:iteration_tokens_total_bucket{le="32.0",model_name="unsloth/Llama-3.2-1B-Instruct"} 3.0
vllm:iteration_tokens_total_bucket{le="64.0",model_name="unsloth/Llama-3.2-1B-Instruct"} 3.0
vllm:iteration_tokens_total_bucket{le="128.0",model_name="unsloth/Llama-3.2-1B-Instruct"} 3.0
vllm:iteration_tokens_total_bucket{le="256.0",model_name="unsloth/Llama-3.2-1B-Instruct"} 3.0
vllm:iteration_tokens_total_bucket{le="512.0",model_name="unsloth/Llama-3.2-1B-Instruct"} 3.0
...

The following metrics are exposed:

:::{literalinclude} ../../../vllm/engine/metrics.py :end-before: end-metrics-definitions :language: python :start-after: begin-metrics-definitions :::