docker.io/milvusdb/milvus:v2.6.4-20251021-9b9a303a-gpu-arm64 linux/arm64

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/milvusdb/milvus:v2.6.4-20251021-9b9a303a-gpu-arm64-linuxarm64
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/milvusdb/milvus:v2.6.4-20251021-9b9a303a-gpu-arm64-linuxarm64  docker.io/milvusdb/milvus:v2.6.4-20251021-9b9a303a-gpu-arm64

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/milvusdb/milvus:v2.6.4-20251021-9b9a303a-gpu-arm64-linuxarm64
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/milvusdb/milvus:v2.6.4-20251021-9b9a303a-gpu-arm64-linuxarm64  docker.io/milvusdb/milvus:v2.6.4-20251021-9b9a303a-gpu-arm64

Shell快速替换命令

sed -i 's#milvusdb/milvus:v2.6.4-20251021-9b9a303a-gpu-arm64#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/milvusdb/milvus:v2.6.4-20251021-9b9a303a-gpu-arm64-linuxarm64#' deployment.yaml

Ansible快速分发-Docker

#ansible k8s -m shell -a 'docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/milvusdb/milvus:v2.6.4-20251021-9b9a303a-gpu-arm64-linuxarm64 && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/milvusdb/milvus:v2.6.4-20251021-9b9a303a-gpu-arm64-linuxarm64  docker.io/milvusdb/milvus:v2.6.4-20251021-9b9a303a-gpu-arm64'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/milvusdb/milvus:v2.6.4-20251021-9b9a303a-gpu-arm64-linuxarm64 && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/milvusdb/milvus:v2.6.4-20251021-9b9a303a-gpu-arm64-linuxarm64  docker.io/milvusdb/milvus:v2.6.4-20251021-9b9a303a-gpu-arm64'

镜像构建历史

# 0001-01-01 08:00:00  3.11GB 复制新文件或目录到容器中
COPY --chown=root:root --chmod=774 ./lib/ /milvus/lib/
                        
# 0001-01-01 08:00:00  116.97KB 复制新文件或目录到容器中
COPY --chown=root:root --chmod=774 ./configs/ /milvus/configs/
                        
# 0001-01-01 08:00:00  263.83MB 复制新文件或目录到容器中
COPY --chown=root:root --chmod=774 ./bin/milvus /milvus/bin/milvus
                        
# 0001-01-01 08:00:00  0.00B 执行命令并创建新的镜像层
RUN mkdir -p /milvus/bin
                        
# 0001-01-01 08:00:00  23.90KB 执行命令并创建新的镜像层
RUN curl -L -o /tini https://github.com/krallin/tini/releases/download/v0.19.0/tini-$TARGETARCH &&     chmod +x /tini
                        
# 0001-01-01 08:00:00  71.47MB 执行命令并创建新的镜像层
RUN apt-get update &&     apt-get install -y --no-install-recommends ca-certificates &&     sed -i 's/http:/https:/g' /etc/apt/sources.list &&     apt-get update &&     apt-get install -y --no-install-recommends curl libaio-dev libgomp1 libopenblas-dev &&     apt-get remove --purge -y &&     rm -rf /var/lib/apt/lists/*
                        
# 2023-11-10 14:47:29  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2023-11-10 14:47:29  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2023-11-10 14:47:29  2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
                        
# 2023-11-10 14:47:28  3.06KB 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
                        
# 2023-11-10 14:47:28  258.02KB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=arm64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_PACKAGE_NAME} ${NV_LIBNCCL_PACKAGE_NAME} # buildkit
                        
# 2023-11-10 14:47:27  2.03GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=arm64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     cuda-libraries-11-8=${NV_CUDA_LIB_VERSION}     ${NV_LIBNPP_PACKAGE}     cuda-nvtx-11-8=${NV_NVTX_VERSION}     libcusparse-11-8=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 14:47:27  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 14:47:27  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 14:47:27  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.15.5-1+cuda11.8
                        
# 2023-11-10 14:47:27  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.15.5-1
                        
# 2023-11-10 14:47:27  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.15.5-1
                        
# 2023-11-10 14:47:27  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2023-11-10 14:47:27  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-11-8=11.11.3.6-1
                        
# 2023-11-10 14:47:27  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=11.11.3.6-1
                        
# 2023-11-10 14:47:27  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-8
                        
# 2023-11-10 14:47:27  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=11.7.5.86-1
                        
# 2023-11-10 14:47:27  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-11-8=11.8.0.86-1
                        
# 2023-11-10 14:47:27  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=11.8.0.86-1
                        
# 2023-11-10 14:47:27  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=11.8.86-1
                        
# 2023-11-10 14:47:27  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.8.0-1
                        
# 2023-11-10 14:40:03  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2023-11-10 14:40:03  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2023-11-10 14:40:03  17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2023-11-10 14:40:03  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2023-11-10 14:40:03  0.00B 设置环境变量 PATH
ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2023-11-10 14:40:03  46.00B 执行命令并创建新的镜像层
RUN |1 TARGETARCH=arm64 /bin/sh -c echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf     && echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf # buildkit
                        
# 2023-11-10 14:40:03  1.43MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=arm64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     cuda-cudart-11-8=${NV_CUDA_CUDART_VERSION}     ${NV_CUDA_COMPAT_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 14:39:20  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=11.8.0
                        
# 2023-11-10 14:39:20  10.21MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=arm64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     gnupg2 curl ca-certificates &&     curl -fsSLO https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/${NVARCH}/cuda-keyring_1.0-1_all.deb &&     dpkg -i cuda-keyring_1.0-1_all.deb &&     apt-get purge --autoremove -y curl     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-11-10 14:39:20  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2023-11-10 14:39:20  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2023-11-10 14:39:20  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=11.8.89-1
                        
# 2023-11-10 14:39:20  0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA
ENV NVIDIA_REQUIRE_CUDA=cuda>=11.8
                        
# 2023-11-10 14:39:20  0.00B 设置环境变量 NVARCH
ENV NVARCH=sbsa
                        
# 2023-10-05 15:32:22  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2023-10-05 15:32:22  69.19MB 
/bin/sh -c #(nop) ADD file:f8594e26831508c318e42c8dfd9942041031087b8de1bf3fec11fd75b8b30fd4 in / 
                        
# 2023-10-05 15:32:21  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=22.04
                        
# 2023-10-05 15:32:21  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2023-10-05 15:32:21  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2023-10-05 15:32:20  0.00B 
/bin/sh -c #(nop)  ARG RELEASE
                        
                    

镜像信息

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    "RepoTags": [
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    "Created": "2025-10-21T03:56:55.947501582Z",
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    "DockerVersion": "",
    "Author": "",
    "Config": {
        "Hostname": "",
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        "AttachStdin": false,
        "AttachStdout": false,
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        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
            "PATH=/milvus/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin",
            "NVARCH=sbsa",
            "NVIDIA_REQUIRE_CUDA=cuda\u003e=11.8",
            "NV_CUDA_CUDART_VERSION=11.8.89-1",
            "CUDA_VERSION=11.8.0",
            "LD_LIBRARY_PATH=/milvus/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/lib",
            "NVIDIA_VISIBLE_DEVICES=all",
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            "NV_NVTX_VERSION=11.8.86-1",
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            "NV_LIBNPP_PACKAGE=libnpp-11-8=11.8.0.86-1",
            "NV_LIBCUSPARSE_VERSION=11.7.5.86-1",
            "NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-8",
            "NV_LIBCUBLAS_VERSION=11.11.3.6-1",
            "NV_LIBCUBLAS_PACKAGE=libcublas-11-8=11.11.3.6-1",
            "NV_LIBNCCL_PACKAGE_NAME=libnccl2",
            "NV_LIBNCCL_PACKAGE_VERSION=2.15.5-1",
            "NCCL_VERSION=2.15.5-1",
            "NV_LIBNCCL_PACKAGE=libnccl2=2.15.5-1+cuda11.8",
            "NVIDIA_PRODUCT_NAME=CUDA",
            "LD_PRELOAD=/milvus/lib/libjemalloc.so",
            "MALLOC_CONF=background_thread:true"
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        "Cmd": null,
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        "WorkingDir": "/milvus",
        "Entrypoint": [
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        "Labels": {
            "maintainer": "NVIDIA CORPORATION \u003ccudatools@nvidia.com\u003e",
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