镜像概览

完整引用
docker.io/anyscale/ray
Registry
docker.io
命名空间
anyscale
仓库
ray
已缓存 Tag 数
9244
最近同步
07/06/2026, 09:25 AM

简介

Anyscale Ray 分布式计算镜像,运行 Ray head/worker 支撑 Python 并行与 LLM 推理集群,需 GPU 节点可选。

详细介绍

anyscale/ray 提供 Ray runtime,可 scale ML training、hyperparameter tuning 与 Ray Serve 推理。典型用于 LLM 批推理或 RL 训练集群,定位为分布式计算框架,需 head/worker 拓扑与 GCS;K8s 使用 KubeRay Operator 或 RayCluster CR。

快速启动

docker run -d --name ray-head \
  -p 8265:8265 -p 10001:10001 \
  docker.io/anyscale/ray:latest \
  ray start --head --dashboard-host=0.0.0.0

推荐实践

docker run -d --name ray-head \
  --restart unless-stopped \
  -p 8265:8265 \
  --gpus all \
  docker.io/anyscale/ray:2.9.0-py310 \
  ray start --head --dashboard-host=0.0.0.0 --num-gpus=1

核心参数说明

  • -p 8265:8265 — Ray Dashboard
  • ray start --head — Head 节点模式
  • --gpus all — GPU worker(可选)
  • 固定 tag — Ray 与 Python 版本 pin

Kubernetes

apiVersion: ray.io/v1
kind: RayCluster
metadata:
  name: ray-cluster
spec:
  headGroupSpec:
    rayStartParams:
      dashboard-host: 0.0.0.0
    template:
      spec:
        containers:
          - name: ray-head
            image: docker.io/anyscale/ray:2.9.0-py310
            ports:
              - containerPort: 8265
  workerGroupSpecs:
    - replicas: 2
      template:
        spec:
          containers:
            - name: ray-worker
              image: docker.io/anyscale/ray:2.9.0-py310
---
apiVersion: v1
kind: Service
metadata:
  name: ray-dashboard
spec:
  selector:
    ray.io/node-type: head
  ports:
    - port: 8265
      targetPort: 8265

推荐 KubeRay;GPU 节点 taint/toleration 调度。

最新 Tag(20 条)

查看全部 9244 个 Tag →
Tag架构推送时间大小Digest同步期望操作
docker.io/anyscale/ray
:nightly-py311-cu130
linux/amd64linux/arm64
2026/06/30 19:217.0 GBsha256:e335ba406069
docker.io/anyscale/ray
:nightly-py310-cu130
linux/amd64linux/arm64
2026/06/30 19:206.9 GBsha256:54d562ecd83c
docker.io/anyscale/ray
:nightly-cu130
linux/amd64linux/arm64
2026/06/30 19:206.9 GBsha256:54d562ecd83c
docker.io/anyscale/ray
:nightly-py313-cu130
linux/amd64linux/arm64
2026/06/30 19:207.0 GBsha256:71196b1583b1
docker.io/anyscale/ray
:nightly-py312-cu130
linux/amd64linux/arm64
2026/06/30 19:206.9 GBsha256:415bff5e0fa1
docker.io/anyscale/ray
:nightly-py311-cu117
linux/amd64linux/arm64
2026/06/30 19:175.2 GBsha256:08a570b4fa2a
docker.io/anyscale/ray
:nightly-py312-cu118
linux/amd64linux/arm64
2026/06/30 19:176.2 GBsha256:7e81a7f4532b
docker.io/anyscale/ray
:nightly-py310-cu117
linux/amd64linux/arm64
2026/06/30 19:175.2 GBsha256:07ffcf82d83c
docker.io/anyscale/ray
:nightly-py310-cu118
linux/amd64linux/arm64
2026/06/30 19:176.2 GBsha256:29c0ddc4ab9e
docker.io/anyscale/ray
:nightly-cu117
linux/amd64linux/arm64
2026/06/30 19:175.2 GBsha256:07ffcf82d83c
docker.io/anyscale/ray
:nightly-cu118
linux/amd64linux/arm64
2026/06/30 19:176.2 GBsha256:29c0ddc4ab9e
docker.io/anyscale/ray
:nightly-py311-cu118
linux/amd64linux/arm64
2026/06/30 19:176.2 GBsha256:ed2f7b102665
docker.io/anyscale/ray
:nightly-py312-cu117
linux/amd64linux/arm64
2026/06/30 19:175.2 GBsha256:ab2b5da3d996
docker.io/anyscale/ray
:nightly-py310-cu121
linux/amd64linux/arm64
2026/06/30 19:176.3 GBsha256:44abd808150d
docker.io/anyscale/ray
:nightly-cu121
linux/amd64linux/arm64
2026/06/30 19:176.3 GBsha256:44abd808150d
docker.io/anyscale/ray
:nightly-py311-cu121
linux/amd64linux/arm64
2026/06/30 19:176.3 GBsha256:c78cc6bcfea5
docker.io/anyscale/ray
:nightly-py313-cu121
linux/amd64linux/arm64
2026/06/30 19:176.3 GBsha256:a22a355615d3
docker.io/anyscale/ray
:nightly-py313-cu118
linux/amd64linux/arm64
2026/06/30 19:166.3 GBsha256:fb129ce4a7d0
docker.io/anyscale/ray
:nightly-py313-cu123
linux/amd64linux/arm64
2026/06/30 19:165.6 GBsha256:ae6b15add5de
docker.io/anyscale/ray
:nightly-py311-cu124
linux/amd64linux/arm64
2026/06/30 19:165.8 GBsha256:88b50daf961b