[sglang,vllm] feat: use prometheus and grafana to show rollout message
What does this PR do?
We provide an additional training monitoring capability, leveraging Prometheus and Grafana to display rollout information during training. The figures below show the performance of Qwen235B on the AIME2024 dataset with a response length of 20k, where the emergence of a long-tail problem is clearly observable.
The following figure presents the fully asynchronous training of the Qwen235B model. Here, resource idleness is distinctly noticeable, indicating that rollout resources can be reduced.
Through the above two examples, we also illustrate the necessity of system observability.
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