镜像概览

完整引用
docker.io/tensorflow/serving
Registry
docker.io
命名空间
tensorflow
仓库
serving
已缓存 Tag 数
438
最近同步
07/06/2026, 12:34 AM

简介

TensorFlow Serving 模型推理服务镜像,SavedModel gRPC/REST 部署,ML 生产环境模型 serving 标准方案。

详细介绍

tensorflow/serving 运行 TensorFlow Serving 高性能模型推理服务,加载 SavedModel 并通过 gRPC/REST API 提供 batch 预测。定位为 ML 模型 serving 后端,需挂载 models volume 存放 SavedModel;K8s Deployment GPU/CPU 推理服务。

快速启动

docker run -d --name tf-serving \
  -p 8500:8500 -p 8501:8501 \
  -v /data/models:/models \
  -e MODEL_NAME=my_model \
  docker.io/tensorflow/serving:latest

推荐实践

docker run -d --name tf-serving \
  --gpus all --restart unless-stopped \
  -p 8500:8500 -p 8501:8501 \
  -v /data/models:/models \
  -e MODEL_NAME=my_model \
  docker.io/tensorflow/serving:2.15.0

核心参数说明

  • -p 8500:8500 — gRPC 推理 API
  • -p 8501:8501 — REST 推理 API
  • -v .../models:... — SavedModel 目录
  • -e MODEL_NAME — 模型名称

Kubernetes

apiVersion: apps/v1
kind: Deployment
metadata:
  name: tf-serving
spec:
  replicas: 2
  selector:
    matchLabels:
      app: tf-serving
  template:
    metadata:
      labels:
        app: tf-serving
    spec:
      containers:
        - name: serving
          image: docker.io/tensorflow/serving:2.15.0
          ports:
            - containerPort: 8500
            - containerPort: 8501
          env:
            - name: MODEL_NAME
              value: my_model
          volumeMounts:
            - name: models
              mountPath: /models
      volumes:
        - name: models
          persistentVolumeClaim:
            claimName: tf-models
---
apiVersion: v1
kind: Service
metadata:
  name: tf-serving
spec:
  selector:
    app: tf-serving
  ports:
    - port: 8500
      targetPort: 8500
    - port: 8501
      targetPort: 8501

GPU 节点可选;HPA 按 QPS 扩缩。

最新 Tag(20 条)

查看全部 438 个 Tag →
Tag架构推送时间大小Digest同步期望操作
docker.io/tensorflow/serving
:nightly
linux/amd64
2026/06/29 13:48204.7 MBsha256:2f9b5e9ae50a
docker.io/tensorflow/serving
:nightly-devel
linux/amd64
2026/06/29 13:467.0 GBsha256:4408b76e6bc9
docker.io/tensorflow/serving
:nightly-gpu
linux/amd64
2026/06/09 18:564.5 GBsha256:7d9d39dfd35f
docker.io/tensorflow/serving
:nightly-devel-gpu
linux/amd64
2026/06/09 18:4521.5 GBsha256:c9b98f420cbe
docker.io/tensorflow/serving
:latest-gpu
linux/amd64
2026/06/05 05:454.5 GBsha256:67153005c5c5
docker.io/tensorflow/serving
:2.20.0-gpu
linux/amd64
2026/06/05 05:454.5 GBsha256:67153005c5c5
docker.io/tensorflow/serving
:latest-devel-gpu
linux/amd64
2026/06/05 05:3321.5 GBsha256:cff2de144956
docker.io/tensorflow/serving
:2.20.0-devel-gpu
linux/amd64
2026/06/05 05:3321.5 GBsha256:cff2de144956
docker.io/tensorflow/serving
:latest
linux/amd64
2026/06/04 17:44184.5 MBsha256:8a208c232297
docker.io/tensorflow/serving
:2.20.0
linux/amd64
2026/06/04 17:44184.5 MBsha256:8a208c232297
docker.io/tensorflow/serving
:latest-devel
linux/amd64
2026/06/04 17:436.7 GBsha256:579aa9607bff
docker.io/tensorflow/serving
:2.20.0-devel
linux/amd64
2026/06/04 17:436.7 GBsha256:579aa9607bff
docker.io/tensorflow/serving
:2.19.1-gpu
linux/amd64
2026/04/15 21:053.6 GBsha256:124ad2887536
docker.io/tensorflow/serving
:2.19.1-devel-gpu
linux/amd64
2026/04/15 20:5517.0 GBsha256:76c4753e173a
docker.io/tensorflow/serving
:2.19.1
linux/amd64
2026/04/15 16:12168.4 MBsha256:99bc0c3e306c
docker.io/tensorflow/serving
:2.19.1-devel
linux/amd64
2026/04/15 16:113.3 GBsha256:4a5a73836cb2
docker.io/tensorflow/serving
:2.19.0-gpu
linux/amd64
2025/05/06 11:303.6 GBsha256:d32afbfadf8c
docker.io/tensorflow/serving
:2.19.0-devel-gpu
linux/amd64
2025/05/06 11:2017.1 GBsha256:388b8d48628e
docker.io/tensorflow/serving
:2.19.0
linux/amd64
2025/05/06 07:02168.4 MBsha256:289a8ca157c7
docker.io/tensorflow/serving
:2.19.0-devel
linux/amd64
2025/05/06 07:013.3 GBsha256:0e73a32222ef