leideng/QCFuse/srt/mem_cache/storage/hf3fs/docs - Storage Bucket

Using HF3FS as L3 Global KV Cache

This document provides step-by-step instructions for setting up a k8s + 3FS + SGLang runtime environment from scratch, describing how to utilize deepseek-hf3fs as the L3 KV cache for SGLang. The process consists of five main steps:

Step 1: Install deepseek-3fs via 3fs-Operator

Refer to the 3fs-operator documentation to deploy 3FS components in your Kubernetes environment using the Operator with one-click deployment.

Step 2: Launch SGLang Pod

Start your SGLang Pod while specifying 3FS-related labels in the YAML configuration. Follow the fuse-client-creation guide.

Step 3: Configure Usrbio Client in SGLang Pod

The Usrbio client is required for accessing 3FS. Install it in your SGLang Pod using either method below:

Alternative 1 (Recommend): Build from source (refer to setup_usrbio_client.md)

Alternative 2: Run pip3 install hf3fs-py-usrbio (Follow https://pypi.org/project/hf3fs-py-usrbio/#files)

Step 4: Deploy Model Serving

Single Node Deployment

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/lib/python3.12/dist-packages
python3 -m sglang.launch_server \
    --model-path /path/to/models/Qwen3-32B/ \
    --host 0.0.0.0 --port 10000 \
    --page-size 64 \
    --enable-hierarchical-cache \
    --hicache-ratio 2 --hicache-size 0 \
    --hicache-write-policy write_through \
    --hicache-storage-backend hf3fs

Multi-Node Deployment (Shared KV Cache)

Follow the deploy_sglang_3fs_multinode.md guide to deploy SGLang with 3FS across multiple nodes for shared KV caching.