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target=\"_blank\">http://cn.download.nvidia.com/XFree86/Linux-x86_64/384.66/NVIDIA-Linux-x86_64-384.66.run\u003C/a>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"> \u003Ca href=\"https://developer.nvidia.com/cuda-downloads\" target=\"_blank\">NVIDIA-Linux-x86_64-384.66.run # 最新CUDA安装包\u003C/a>\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">   \u003C/font>\u003Ca href=\"https://developer.nvidia.com/compute/cuda/8.0/Prod2/local_installers/cuda_8.0.61_375.26_linux-run\" target=\"_blank\">https://developer.nvidia.com/compute/cuda/8.0/Prod2/local_installers/cuda_8.0.61_375.26_linux-run\u003C/a>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"> cuda_8.0.61_375.26_linux-run  # CUDA补丁包\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">   \u003C/font>\u003Ca href=\"https://developer.nvidia.com/compute/cuda/8.0/Prod2/patches/2/cuda_8.0.61.2_linux-run\" target=\"_blank\">https://developer.nvidia.com/compute/cuda/8.0/Prod2/patches/2/cuda_8.0.61.2_linux-run\u003C/a>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"> \u003Ca href=\"https://developer.nvidia.com/rdp/cudnn-download\" target=\"_blank\">cudnn-8.0-linux-x64-v6.0.tgz # cudnn库v6.0\u003C/a>\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">   \u003C/font>\u003Ca href=\"https://developer.nvidia.com/compute/machine-learning/cudnn/secure/v6/prod/8.0_20170307/cudnn-8.0-linux-x64-v6.0-tgz\" target=\"_blank\">https://developer.nvidia.com/compute/machine-learning/cudnn/secure/v6/prod/8.0_20170307/cudnn-8.0-linux-x64-v6.0-tgz\u003C/a>\u003Cspan> \u003C/span>\u003Cbr>\u003Cb>\u003Cfont size=\"3\">2. 安装基础环境\u003C/font>\u003C/b>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"> 检查显卡\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"># lspci | grep -i vga 04:00.0 VGA compatible controller: NVIDIA Corporation Device 1b00 (rev a1) \u003C/font>\u003Cspan>\u003C/span>\u003Cbr>\u003Cfont size=\"2\">更新系统包\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"># yum install update -y && reboot\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">检查系统版本，确保系统支持(需要Linux-64bit系统) \u003C/font>\u003Cspan>\u003C/span>\u003Cbr>\u003Cfont size=\"2\"># uname -m && cat /etc/*release x86_64 CentOS Linux release 7.4.1708 (Core)\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">安装GCC \u003C/font>\u003Cspan>\u003C/span>\u003Cbr>\u003Cfont size=\"2\"># yum install gcc gcc-c++ \u003C/font>\u003Cspan>\u003C/span>\u003Cbr>\u003Cfont size=\"2\">安装Kernel Headers Packages \u003C/font>\u003Cspan>\u003C/span>\u003Cbr>\u003Cfont size=\"2\"># yum install kernel-devel-$(uname -r) kernel-headers-$(uname -r)\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cbr>\u003Cb>\u003Cfont size=\"3\">3. 安装显卡驱动\u003C/font>\u003C/b>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"># bash NVIDIA-Linux-x86_64-384.66.run （提示错误，请执行第四步）\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cbr>\u003Cimg src=\"/uploads/layedit/20181018/02bab5476ad86f09c5c9bbf1c6e11aa3.png\" alt=\"1.png\">\u003Cspan id=\"J_att_22\">\u003Cspan id=\"td_att_22\" class=\"J_attach_img_wrap single_img\">\u003Cimg class=\"J_post_img\" src=\"http://zhl123.cn/attachment/thumb/1711/thread/6_1_af8f05f65ba4f66.png\" border=\"0\" title=\"点击查看原图\">\u003C/span>\u003C/span>\u003Cspan> \u003C/span>\u003Cbr>\u003Cb>\u003Cfont size=\"3\">4. 关闭Nouveau\u003C/font>\u003C/b>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">1)把驱动加入黑名单中: /etc/modprobe.d/nvidia-installer-disable-nouveau.conf  在后面加入：\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"> blacklist nouveau\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"> options nouveau modeset=0\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"3\">2) 使用 dracut重新建立  initramfs image file :\u003C/font>\u003Cfont size=\"2\">* 备份 the initramfs file\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">#  mv /boot/initramfs-$(uname -r).img /boot/initramfs-$(uname -r).img.bak\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">* 重新建立 the initramfs file\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"># sudo dracut -v /boot/initramfs-$(uname -r).img $(uname -r)\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">3) 重启系统至文本模式,init 3 这个可以修改/etc/inittab 文件 init 3是文本模式\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">4)检查nouveau driver确保没有被加载！\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"># lsmod | grep nouveau\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">\u003Cbr>\u003C/font>\u003Cspan>\u003C/span>\u003Cbr>\u003Cfont size=\"3\"># bash NVIDIA-Linux-x86_64-384.66.run\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cspan>Accept \u003C/span>\u003Cbr>\u003Cimg src=\"/uploads/layedit/20181018/416642f44f9d5af07ed87ab63fc81c64.png\" alt=\"2.png\">\u003Cbr>\u003Cbr>\u003Cspan>Building kernerl modules 安装 \u003C/span>\u003Cbr>\u003Cimg src=\"/uploads/layedit/20181018/6192e22a31f8a34f6de6a50a947d24ca.png\" alt=\"3.png\">\u003Cbr>\u003Cbr>\u003Cp>\u003Cspan>32bit兼容包选择, 这里要注意选择 No,不然后面就会出错\u003C/span>\u003C/p>\u003Cp>\u003Cspan>\u003Cimg src=\"/uploads/layedit/20181018/91ab7e35766e7656bc88944e2001332f.png\" alt=\"4.png\">\u003Cbr>\u003C/span>\u003C/p>\u003Cbr>\u003Cfont size=\"3\">\u003Cb>5. 安装CUDA\u003C/b>\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">1）开始安装\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"># bash cuda_8.0.61_375.26_linux-run\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"># accept\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">-------------------------------------------------------------\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"> Do you accept the previously read EULA?\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">accept/decline/quit: accept\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"># no\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 375.26?\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">(y)es/(n)o/(q)uit: n\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">-------------------------------------------------------------\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"># 后面的就都选yes或者default\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">Do you want to install the OpenGL libraries?\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">(y)es/(n)o/(q)uit [ default is yes ]: \u003C/font>\u003Cspan>\u003C/span>\u003Cbr>\u003Cfont size=\"2\">Do you want to run nvidia-xconfig?\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">This will update the system X configuration file so that the NVIDIA X driver\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">is used. The pre-existing X configuration file will be backed up.\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">This option should not be used on systems that require a custom\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">X configuration, such as systems with multiple GPU vendors.\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">(y)es/(n)o/(q)uit [ default is no ]: y\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">Install the CUDA 8.0 Toolkit?\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">(y)es/(n)o/(q)uit: y\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cbr>\u003Cfont size=\"2\">Enter Toolkit Location\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">[ default is /usr/local/cuda-8.0 ]: \u003C/font>\u003Cspan>\u003C/span>\u003Cbr>\u003Cbr>\u003Cfont size=\"2\">Do you want to install a symbolic link at /usr/local/cuda?\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">(y)es/(n)o/(q)uit: y\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cbr>\u003Cfont size=\"2\">Install the CUDA 8.0 Samples?\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">(y)es/(n)o/(q)uit: y\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cbr>\u003Cfont size=\"2\">Enter CUDA Samples Location\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">[ default is /root ]: \u003C/font>\u003Cspan>\u003C/span>\u003Cbr>\u003Cbr>\u003Cfont size=\"2\">Installing the NVIDIA display driver...\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">The driver installation has failed due to an unknown error. Please consult the driver installation log located at /var/log/nvidia-installer.log.\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cbr>\u003Cfont size=\"2\">===========\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">= Summary =\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">===========\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cbr>\u003Cfont size=\"2\">Driver:   Not Selected\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">Toolkit:  Installed in /usr/local/cuda-8.0\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">Samples:  Installed in /root, but missing recommended libraries\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cbr>\u003Cfont size=\"2\">Please make sure that\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">-   PATH includes /usr/local/cuda-8.0/bin\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">-   LD_LIBRARY_PATH includes /usr/local/cuda-8.0/lib64, or, add /usr/local/cuda-8.0/lib64 to /etc/ld.so.conf and run ldconfig as root\u003C/font>\u003Cspan>\u003C/span>\u003Cbr>\u003Cbr>\u003Cfont size=\"2\">To uninstall the CUDA Toolkit, run the uninstall script in /usr/local/cuda-8.0/bin\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cbr>\u003Cfont size=\"2\">Please see CUDA_Installation_Guide_Linux.pdf in /usr/local/cuda-8.0/doc/pdf for detailed information on setting up CUDA.\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cbr>\u003Cfont size=\"2\">***WARNING: Incomplete installation! This installation did not install the CUDA Driver. A driver of version at least 361.00 is required for CUDA 8.0 functionality to work.\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">To install the driver using this installer, run the following command, replacing <CudaInstaller> with the name of this run file:\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">   sudo <CudaInstaller>.run -silent -driver\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cbr>\u003Cfont size=\"2\">Logfile is /tmp/cuda_install_192.log\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cbr>\u003Cfont size=\"2\">2）安装CUDA补丁\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"># bash cuda_8.0.61.2_linux-run\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"># accept\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">\u003Cbr>3）验证安装结果\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">添加环境变量\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">在 ~/.bashrc的最后面添加下面两行\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">export PATH=/usr/local/cuda-8.0/bin:$PATH\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64:/usr/local/cuda-8.0/extras/CUPTI/lib64:$LD_LIBRARY_PATH\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">使生效\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"># source ~/.bashrc\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">查看版本信息\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"># nvcc -V\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">nvcc: NVIDIA (R) Cuda compiler driver\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">Copyright (c) 2005-2016 NVIDIA Corporation\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">Built on Tue_Jan_10_13:22:03_CST_2017\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">Cuda compilation tools, release 8.0, V8.0.61\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"># nvidia-smi\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">Tue Nov 28 03:05:40 2017       \u003C/font>\u003Cspan>\u003C/span>\u003Cbr>\u003Cfont size=\"2\">+-----------------------------------------------------------------------------+\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">| NVIDIA-SMI 384.66                 Driver Version: 384.66                    |\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">|-------------------------------+----------------------+----------------------+\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">|===============================+======================+======================|\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">|   0  Tesla P40           Off  | 00000000:85:00.0 Off |                    0 |\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">| N/A   37C    P0    50W / 250W |      0MiB / 22912MiB |      0%      Default |\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">+-------------------------------+----------------------+----------------------+\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">                                                                              \u003C/font>\u003Cspan>\u003C/span>\u003Cbr>\u003Cfont size=\"2\">+-----------------------------------------------------------------------------+\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">| Processes:                                                       GPU Memory |\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">|  GPU       PID  Type  Process name                               Usage      |\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">|=============================================================================|\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">|  No running processes found                                                 |\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\">+-----------------------------------------------------------------------------+\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cbr>\u003Cfont size=\"3\">\u003Cb>6. 安装 cuDNN 库\u003C/b>\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"># tar -xvzf cudnn-8.0-linux-x64-v6.0.tgz\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"># cp -P cuda/include/cudnn.h /usr/local/cuda-8.0/include\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"># cp -P cuda/lib64/libcudnn* /usr/local/cuda-8.0/lib64\u003C/font>\u003Cspan> \u003C/span>\u003Cbr>\u003Cfont size=\"2\"># chmod a+r /usr/local/cuda-8.0/include/cudnn.h /usr/local/cuda-8.0/lib64/libcudnn*\u003C/font>\u003C/p>","**系统环境：CentOS Linux release 7.4.1708  显卡型号：****nVidia Tesla P40 GPU**\n\n**\n1. 准备工作**\n\n \n\n 准备安装包\n\n \n\n [cuda_8.0.61_375.26_linux-run # 最新显卡驱动](http://www.nvidia.cn/Download/index.aspx?lang=cn) \n\n   \n[http://cn.download.nvidia.com/XFree86/Linux-x86_64/384.66/NVIDIA-Linux-x86_64-384.66.run](http://cn.download.nvidia.com/XFree86/Linux-x86_64/384.66/NVIDIA-Linux-x86_64-384.66.run)\n \n\n [NVIDIA-Linux-x86_64-384.66.run # 最新CUDA安装包](https://developer.nvidia.com/cuda-downloads)\n\n \n\n   \n[https://developer.nvidia.com/compute/cuda/8.0/Prod2/local_installers/cuda_8.0.61_375.26_linux-run](https://developer.nvidia.com/compute/cuda/8.0/Prod2/local_installers/cuda_8.0.61_375.26_linux-run)\n \n\n cuda_8.0.61_375.26_linux-run  # CUDA补丁包\n\n \n\n   \n[https://developer.nvidia.com/compute/cuda/8.0/Prod2/patches/2/cuda_8.0.61.2_linux-run](https://developer.nvidia.com/compute/cuda/8.0/Prod2/patches/2/cuda_8.0.61.2_linux-run)\n \n\n [cudnn-8.0-linux-x64-v6.0.tgz # cudnn库v6.0](https://developer.nvidia.com/rdp/cudnn-download)\n\n \n\n   \n[https://developer.nvidia.com/compute/machine-learning/cudnn/secure/v6/prod/8.0_20170307/cudnn-8.0-linux-x64-v6.0-tgz](https://developer.nvidia.com/compute/machine-learning/cudnn/secure/v6/prod/8.0_20170307/cudnn-8.0-linux-x64-v6.0-tgz)\n \n\n**\n2. 安装基础环境\n**\n \n\n 检查显卡\n\n \n\n# lspci | grep -i vga 04:00.0 VGA compatible controller: NVIDIA Corporation Device 1b00 (rev a1) \n\n更新系统包\n\n \n\n# yum install update -y && reboot\n\n \n\n检查系统版本，确保系统支持(需要Linux-64bit系统) \n\n# uname -m && cat /etc/*release x86_64 CentOS Linux release 7.4.1708 (Core)\n\n \n\n安装GCC \n\n# yum install gcc gcc-c++ \n\n安装Kernel Headers Packages \n\n# yum install kernel-devel-$(uname -r) kernel-headers-$(uname -r)\n\n \n\n**\n3. 安装显卡驱动\n**\n \n\n# bash NVIDIA-Linux-x86_64-384.66.run （提示错误，请执行第四步）\n\n \n\n![1.png](/uploads/layedit/20181018/02bab5476ad86f09c5c9bbf1c6e11aa3.png)\n\n![](http://zhl123.cn/attachment/thumb/1711/thread/6_1_af8f05f65ba4f66.png)\n\n \n\n**\n4. 关闭Nouveau\n**\n \n\n1)把驱动加入黑名单中: /etc/modprobe.d/nvidia-installer-disable-nouveau.conf  在后面加入：\n\n \n\n blacklist nouveau\n\n \n\n options nouveau modeset=0\n\n \n\n2) 使用 dracut重新建立  initramfs image file :\n\n* 备份 the initramfs file\n\n \n\n#  mv /boot/initramfs-$(uname -r).img /boot/initramfs-$(uname -r).img.bak\n\n \n\n* 重新建立 the initramfs file\n\n \n\n# sudo dracut -v /boot/initramfs-$(uname -r).img $(uname -r)\n\n \n\n3) 重启系统至文本模式,init 3 这个可以修改/etc/inittab 文件 init 3是文本模式\n\n \n\n4)检查nouveau driver确保没有被加载！\n\n \n\n# lsmod | grep nouveau\n\n \n\n# bash NVIDIA-Linux-x86_64-384.66.run\n\n \n\nAccept \n\n![2.png](/uploads/layedit/20181018/416642f44f9d5af07ed87ab63fc81c64.png)\n\nBuilding kernerl modules 安装 \n\n![3.png](/uploads/layedit/20181018/6192e22a31f8a34f6de6a50a947d24ca.png)\n\n32bit兼容包选择, 这里要注意选择 No,不然后面就会出错\n\n![4.png](/uploads/layedit/20181018/91ab7e35766e7656bc88944e2001332f.png)\n\n**5. 安装CUDA**\n\n \n\n1）开始安装\n\n \n\n# bash cuda_8.0.61_375.26_linux-run\n\n \n\n# accept\n\n \n\n-------------------------------------------------------------\n\n \n\n Do you accept the previously read EULA?\n\n \n\naccept/decline/quit: accept\n\n \n\n# no\n\n \n\nInstall NVIDIA Accelerated Graphics Driver for Linux-x86_64 375.26?\n\n \n\n(y)es/(n)o/(q)uit: n\n\n \n\n-------------------------------------------------------------\n\n \n\n# 后面的就都选yes或者default\n\n \n\nDo you want to install the OpenGL libraries?\n\n \n\n(y)es/(n)o/(q)uit [ default is yes ]: \n\nDo you want to run nvidia-xconfig?\n\n \n\nThis will update the system X configuration file so that the NVIDIA X driver\n\n \n\nis used. The pre-existing X configuration file will be backed up.\n\n \n\nThis option should not be used on systems that require a custom\n\n \n\nX configuration, such as systems with multiple GPU vendors.\n\n \n\n(y)es/(n)o/(q)uit [ default is no ]: y\n\n \n\nInstall the CUDA 8.0 Toolkit?\n\n \n\n(y)es/(n)o/(q)uit: y\n\n \n\nEnter Toolkit Location\n\n \n\n[ default is /usr/local/cuda-8.0 ]: \n\nDo you want to install a symbolic link at /usr/local/cuda?\n\n \n\n(y)es/(n)o/(q)uit: y\n\n \n\nInstall the CUDA 8.0 Samples?\n\n \n\n(y)es/(n)o/(q)uit: y\n\n \n\nEnter CUDA Samples Location\n\n \n\n[ default is /root ]: \n\nInstalling the NVIDIA display driver...\n\n \n\nThe driver installation has failed due to an unknown error. Please consult the driver installation log located at /var/log/nvidia-installer.log.\n\n \n\n===========\n\n \n\n= Summary =\n\n \n\n===========\n\n \n\nDriver:   Not Selected\n\n \n\nToolkit:  Installed in /usr/local/cuda-8.0\n\n \n\nSamples:  Installed in /root, but missing recommended libraries\n\n \n\nPlease make sure that\n\n \n\n-   PATH includes /usr/local/cuda-8.0/bin\n\n \n\n-   LD_LIBRARY_PATH includes /usr/local/cuda-8.0/lib64, or, add /usr/local/cuda-8.0/lib64 to /etc/ld.so.conf and run ldconfig as root\n\nTo uninstall the CUDA Toolkit, run the uninstall script in /usr/local/cuda-8.0/bin\n\n \n\nPlease see CUDA_Installation_Guide_Linux.pdf in /usr/local/cuda-8.0/doc/pdf for detailed information on setting up CUDA.\n\n \n\n***WARNING: Incomplete installation! This installation did not install the CUDA Driver. A driver of version at least 361.00 is required for CUDA 8.0 functionality to work.\n\n \n\nTo install the driver using this installer, run the following command, replacing  with the name of this run file:\n\n \n\n   sudo .run -silent -driver\n\n \n\nLogfile is /tmp/cuda_install_192.log\n\n \n\n2）安装CUDA补丁\n\n \n\n# bash cuda_8.0.61.2_linux-run\n\n \n\n# accept\n\n \n\n3）验证安装结果\n\n \n\n添加环境变量\n\n \n\n在 ~/.bashrc的最后面添加下面两行\n\n \n\nexport PATH=/usr/local/cuda-8.0/bin:$PATH\n\n \n\nexport LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64:/usr/local/cuda-8.0/extras/CUPTI/lib64:$LD_LIBRARY_PATH\n\n \n\n使生效\n\n \n\n# source ~/.bashrc\n\n \n\n查看版本信息\n\n \n\n# nvcc -V\n\n \n\nnvcc: NVIDIA (R) Cuda compiler driver\n\n \n\nCopyright (c) 2005-2016 NVIDIA Corporation\n\n \n\nBuilt on Tue_Jan_10_13:22:03_CST_2017\n\n \n\nCuda compilation tools, release 8.0, V8.0.61\n\n \n\n# nvidia-smi\n\n \n\nTue Nov 28 03:05:40 2017       \n\n+-----------------------------------------------------------------------------+\n\n \n\n| NVIDIA-SMI 384.66                 Driver Version: 384.66                    |\n\n \n\n|-------------------------------+----------------------+----------------------+\n\n \n\n| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n\n \n\n| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n\n \n\n|===============================+======================+======================|\n\n \n\n|   0  Tesla P40           Off  | 00000000:85:00.0 Off |                    0 |\n\n \n\n| N/A   37C    P0    50W / 250W |      0MiB / 22912MiB |      0%      Default |\n\n \n\n+-------------------------------+----------------------+----------------------+\n\n \n\n                                                                              \n\n+-----------------------------------------------------------------------------+\n\n \n\n| Processes:                                                       GPU Memory |\n\n \n\n|  GPU       PID  Type  Process name                               Usage      |\n\n \n\n|=============================================================================|\n\n \n\n|  No running processes found                                                 |\n\n \n\n+-----------------------------------------------------------------------------+\n\n \n\n**6. 安装 cuDNN 库**\n\n \n\n# tar -xvzf cudnn-8.0-linux-x64-v6.0.tgz\n\n \n\n# cp -P cuda/include/cudnn.h /usr/local/cuda-8.0/include\n\n \n\n# cp -P cuda/lib64/libcudnn* /usr/local/cuda-8.0/lib64\n\n \n\n# chmod a+r /usr/local/cuda-8.0/include/cudnn.h /usr/local/cuda-8.0/lib64/libcudnn*","/article/19",5276,"2018-10-18 16:29:17","2018-10-18 16:34:06",[155,156,157],{"id":39,"name":81,"url":82},{"id":44,"name":23,"url":59},{"id":46,"name":145,"url":150},{"create_time":6,"description":6,"id":44,"image_url":6,"index_template":52,"is_cover":53,"is_menu":53,"keywords":6,"list_template":54,"model_code":55,"model_id":56,"model_name":57,"name":23,"parent_id":39,"seo_description":6,"seo_keywords":6,"seo_title":6,"show_template":58,"sort":53,"subtitle":6,"update_time":6,"url":59},{"title":160,"url":161},"增强 nginx 的 SSL 安全性配置示例 ","/article/20",{"title":163,"url":164},"Centos7 双网卡绑定（bond0） 操作指南 ","/article/18",[166,167,168,169],{"create_time":6,"description":6,"id":44,"image_url":6,"index_template":52,"is_cover":53,"is_menu":53,"keywords":6,"list_template":54,"model_code":55,"model_id":56,"model_name":57,"name":23,"parent_id":39,"seo_description":6,"seo_keywords":6,"seo_title":6,"show_template":58,"sort":53,"subtitle":6,"update_time":6,"url":59},{"create_time":6,"description":6,"id":45,"image_url":6,"index_template":52,"is_cover":53,"is_menu":53,"keywords":6,"list_template":54,"model_code":55,"model_id":56,"model_name":57,"name":61,"parent_id":39,"seo_description":6,"seo_keywords":6,"seo_title":6,"show_template":58,"sort":56,"subtitle":6,"update_time":6,"url":62},{"create_time":6,"description":6,"id":46,"image_url":6,"index_template":52,"is_cover":53,"is_menu":53,"keywords":6,"list_template":54,"model_code":55,"model_id":56,"model_name":57,"name":64,"parent_id":39,"seo_description":6,"seo_keywords":6,"seo_title":6,"show_template":58,"sort":65,"subtitle":6,"update_time":6,"url":66},{"create_time":6,"description":6,"id":47,"image_url":6,"index_template":52,"is_cover":53,"is_menu":53,"keywords":6,"list_template":54,"model_code":55,"model_id":56,"model_name":57,"name":68,"parent_id":39,"seo_description":6,"seo_keywords":6,"seo_title":6,"show_template":58,"sort":69,"subtitle":6,"update_time":6,"url":70},{"description":147,"keywords":146,"title":145},[172,181,190,199,208,217,226,235,244,252],{"id":173,"category_id":44,"title":174,"keywords":175,"description":176,"image_url":6,"url":177,"hits":178,"is_recommend":73,"is_top":73,"create_time":179,"update_time":180},101,"开启 HTTPS 并获得 ssllabs 满分的过程","开启,获得,满分,过程","准备工作确保你要申请证书的域名都解析到了这台服务器上，且能直接通过域名访问。使用官网推荐的CertBot获取证书。在CertBot官网选择一下环境(比如我选Nginx on Ubuntu 17.04)就可以看到入门教程了。安装CertBot12345apt-get updateapt-get install software-properties-commonadd-apt-repository ppa:certbot/certbotapt-get updateapt-get","/article/101",18546,"2019-11-26 16:12:11","2019-11-26 16:23:16",{"id":182,"category_id":44,"title":183,"keywords":184,"description":185,"image_url":6,"url":186,"hits":187,"is_recommend":73,"is_top":73,"create_time":188,"update_time":189},113,"在CentOS 7中添加命令自动补全功能","命令自动补全,centos","在CentOS 7中，默认情况下并不会安装命令补全包，需要手动安装才能使用命令补全功能。以下是在CentOS 7中安装命令补全包的方法：1. bash-completion：这是一个针对Bash shell的命令补全软件包，可以提供对系统命令、用户自定义命令和文件路径的自动补全功能。可以通过以下命令安装：```sudo yum install bash-completion```安装完成后，需要在/etc/profile配置文件中添加以下内容：```if [ -f /etc/bash_compl","/article/113",14948,"2023-05-16 10:54:01","2023-05-16 10:57:28",{"id":191,"category_id":44,"title":192,"keywords":193,"description":194,"image_url":6,"url":195,"hits":196,"is_recommend":53,"is_top":73,"create_time":197,"update_time":198},94,"Centos7 安装 openvas ","openvas,开放式漏洞评估系统，installing openvas centos-7","一、描述OpenVAS，即开放式漏洞评估系统，是一个用于评估目标漏洞的杰出框架。功能十分强大，最重要的是，它是“开源”的——就是免费的意思啦～它与著名的Nessus“本是同根生”，在Nessus商业化之后仍然坚持开源，号称“当前最好用的开源漏洞扫描工具”。最新版的Kali Linux(kali 3.0)不再自带OpenVAS了，所以我们要自己部署OpenVAS漏洞检测系统。其核心部件是一个服务器，包括一套网络漏洞测试程序，可以检测远程系统和应用程序中的安全问题。但是它的最常用用途是检测目标网络或","/article/94",14690,"2019-01-14 17:43:42","2019-01-14 18:16:36",{"id":200,"category_id":44,"title":201,"keywords":202,"description":203,"image_url":6,"url":204,"hits":205,"is_recommend":73,"is_top":73,"create_time":206,"update_time":207},99,"Centos7 利用iptables防止nmap工具防端口扫描","iptables","一、Nmap介绍       Nmap（NetworkMapper）是一款开放源代码的网络探测和安全审核工具。它用于快速扫描一个网络和一台主机开放的端口，还能使用TCP/IP协议栈特征探测远程主机的操作系统类型。nmap支持很多扫描技术，例如：UDP、TCPconnect()、TCPSYN(半开扫描)、ftp代理(bounce攻击)、反向标志、ICMP、FIN、ACK扫描、圣诞树(XmasTree)、SYN扫描和null扫描。Nmap最初是用于Unix系统","/article/99",14415,"2019-07-09 21:27:00","2019-07-09 21:57:53",{"id":209,"category_id":46,"title":210,"keywords":211,"description":212,"image_url":6,"url":213,"hits":214,"is_recommend":73,"is_top":73,"create_time":215,"update_time":216},61,"Docker 推荐的启动方式","推荐,启动,方式","# cat DockerfileFROM openjdk:8-alpineWORKDIR /ADD ./target/*.jar app.jarEXPOSE 9999COPY docker-entrypoint.sh /RUN chmod +x /docker-entrypoint.shENTRYPOINT [“/docker-entrypoint.sh”]CMD [“java”,”-server”,”-Duser.timezone=GMT+08″,”-jar”,”/app.jar”]# cat","/article/61",14347,"2018-10-22 13:55:47","2018-10-22 13:56:10",{"id":218,"category_id":44,"title":219,"keywords":220,"description":221,"image_url":6,"url":222,"hits":223,"is_recommend":73,"is_top":73,"create_time":224,"update_time":225},107,"Acme.sh 给 SSL 证书自动续期失败的解决方法","HTTP/1.1 200 OK,Server: Bayou Tech Web Srv 1.0,Content-Encoding: none,Content-Length: 5,Content-Type","一、Acme.sh 自动续期失败的症状问题描述如下，续期的时候，提示如下错误：root@dc:~# \"/data/acme.sh\"/acme.sh --cron --home \"/data/acme.sh\" > /dev/null[Sun Nov 10 23:52:17 CST 2020] Error, can not get domain token entry example.com[Sun Nov 10 23:52:17 CST 2020] Please check log file","/article/107",12618,"2021-09-03 10:44:18","2021-09-03 10:46:23",{"id":227,"category_id":44,"title":228,"keywords":229,"description":230,"image_url":6,"url":231,"hits":232,"is_recommend":53,"is_top":73,"create_time":233,"update_time":234},93,"ELK+Filebeat+Kafka+ZooKeeper 构建海量日志分析平台","Filebeat,Kafka","一、说明1.Filebeat是一个日志文件托运工具，在你的服务器上安装客户端后，filebeat会监控日志目录或者指定的日志文件，追踪读取这些文件（追踪文件的变化，不停的读）2.Kafka是一种高吞吐量的分布式发布订阅消息系统，它可以处理消费者规模的网站中的所有动作流数据3.Logstash是一根具备实时数据传输能力的管道，负责将数据信息从管道的输入端传输到管道的输出端；与此同时这根管道还可以让你根据自己的需求在中间加上滤网，Logstash提供里很多功能强大的滤网以满足你的各种应用场景4.El","/article/93",12190,"2018-12-24 16:40:08","2018-12-26 11:53:38",{"id":236,"category_id":46,"title":237,"keywords":238,"description":239,"image_url":6,"url":240,"hits":241,"is_recommend":53,"is_top":73,"create_time":242,"update_time":243},81,"kubernetes 1.12.1 高可用安装之部署Dashboard","安装Dashboard","创建Dashboard需要CoreDNS部署成功之后再安装Dashboard。[root@master01 ~]# wget https://zhl123.com/download/k8s/Dashboard.tgz[root@master01 ~]# tar xf Dashboard.tgz[root@master01 ~]# kubectl create -f Dashboard/[root@master01 Dashboard]# kubectl get svc -n kube-syste","/article/81",12037,"2018-10-26 09:54:41","2018-10-26 16:59:19",{"id":245,"category_id":44,"title":246,"keywords":6,"description":247,"image_url":6,"url":248,"hits":249,"is_recommend":73,"is_top":73,"create_time":250,"update_time":251},100,"用 Nginx 给 Cookie 增加 Secure 和 HttpOnly","在 nginx 的 location 中配置12# 只支持 proxy 模式下设置，SameSite 不需要可删除，如果想更安全可以把 SameSite 设置为 Strictproxy_cookie_path / \"/; httponly; secure; SameSite=Lax\";示例1234567891011121314151617181920212223242526server {    listen 443 ssl http2;    server_name www.zhl123.cn","/article/100",11848,"2019-11-26 16:10:57","2019-11-26 16:23:45",{"id":253,"category_id":44,"title":254,"keywords":255,"description":256,"image_url":6,"url":257,"hits":258,"is_recommend":73,"is_top":73,"create_time":259,"update_time":260},41,"Tomcat 安全配置与性能优化","tomcat，性能优化","1. JVM 1.1. 使用 Server JRE 替代JDK。 服务器上不要安装JDK，请使用 Server JRE. 服务器上根本不需要编译器，代码应该在Release服务器上完成编译打包工作。 理由：一旦服务器被控制，可以防止在其服务器上编译其他恶意代码并植入到你的程序中。 1.2. JAVA_OPTS export JAVA_OPTS=\"-server -Xms512m -Xmx4096m  -XX:PermSize=64M -","/article/41",11623,"2016-09-01 17:06:36","2018-10-18 17:06:58",[262,270,278,286,294,302,310,318,327,336],{"id":263,"category_id":40,"title":264,"keywords":6,"description":265,"image_url":6,"url":266,"hits":267,"is_recommend":73,"is_top":73,"create_time":268,"update_time":269},123,"Agent Skill 精选集：最值得收藏的 Agent Skills Top 10","如果你正在用 Claude Code 或 Codex，一定对 Agent Skills 不陌生。通过安装 Agent Skills，你可以让这些 AI 助手变得更强——不用每次都解释你的需求，它们直接就知道该怎么做。最近有人在 GitHub 上做了一个采样调查，统计了哪些 Skills 的质量最佳和最受欢迎。我整理了这份 Top 10 榜单，加上使用场景和适合人群，帮你快速找到最有用的那几个。Top 10 最受欢迎的 Agent Skills1. Skil","/article/123",270,"2026-01-19 18:49:12","2026-01-19 18:52:01",{"id":271,"category_id":44,"title":272,"keywords":6,"description":273,"image_url":6,"url":274,"hits":275,"is_recommend":73,"is_top":73,"create_time":276,"update_time":277},122,"Nginx性能调优18条黄金法则：支撑10万并发的配置模板","一、概述1.1 背景介绍说实话，Nginx调优这事儿我踩过无数坑。记得2019年双11，我们电商平台流量暴涨，Nginx直接扛不住了，QPS从平时的2万飙升到8万，响应时间从50ms飙到了2秒，最后还是靠临时加机器扛过去的。那次事故之后，我花了大半年时间专门研究Nginx的性能极限，总结出了这20条黄金法则。Nginx作为目前最流行的Web服务器和反向代理，官方数据显示单机可以轻松处理10万+的并发连接。但实际生产环境中，很多同学拿到默认配置就直接上了，结果发现连1万并发都扛不住。问题不在Ngi","/article/122",337,"2026-01-12 11:11:50","2026-01-12 11:12:28",{"id":279,"category_id":46,"title":280,"keywords":6,"description":281,"image_url":6,"url":282,"hits":283,"is_recommend":73,"is_top":73,"create_time":284,"update_time":285},121,"Docker 镜像优化与安全扫描：将镜像体积压缩 70%","1. 适用场景 & 前置条件项目要求适用场景容器化应用镜像体积过大（> 500MB），构建时间长（> 10分钟），存在安全漏洞（CVE高危）OSRHEL/CentOS 7.9+ 或 Ubuntu 20.04+内核Linux Kernel 3.10+软件版本Docker 20.10+ 或 Podman 3.0+，Trivy 0.40+（安全扫描工具）资源规格2C4G（最小）/ 4C8G（推荐），磁盘 50GB+（存储镜像与缓存）网络可访问 Docker Hub/阿里云镜像仓库（","/article/121",309,"2026-01-06 11:54:35","2026-01-06 12:01:59",{"id":287,"category_id":44,"title":288,"keywords":6,"description":289,"image_url":6,"url":290,"hits":291,"is_recommend":73,"is_top":73,"create_time":292,"update_time":293},120,"用 Prometheus Recording Rules 把告警噪声砍掉 70%(二)","五、故障排查和监控5.1 故障排查◆ 5.1.1 日志查看# 查看 Prometheus 日志中的规则评估错误journalctl -u prometheus | grep -i \"rule\" | tail -50# 查看规则评估耗时curl -s http://localhost:9090/api/v1/rules | jq '.data.groups[].rules[] | select(.health != \"ok\")'# Kubernet","/article/120",282,"2026-01-06 11:53:50","2026-01-06 11:54:33",{"id":295,"category_id":44,"title":296,"keywords":6,"description":297,"image_url":6,"url":298,"hits":299,"is_recommend":73,"is_top":73,"create_time":300,"update_time":301},119,"用 Prometheus Recording Rules 把告警噪声砍掉 70%(一)","一、概述1.1 背景介绍在大规模微服务架构下，Prometheus 告警系统往往会陷入一个尴尬的境地：告警太多，运维团队开始选择性忽略；告警太少，真正的故障又可能漏掉。我在某电商平台负责监控体系建设时，团队每天要处理超过 2000 条告警，其中 70% 以上是重复的、关联的或者短暂抖动产生的噪声。Recording Rules 是 Prometheus 提供的预计算机制，可以将复杂的查询表达式预先计算并存储为新的时间序列。通过合理设计 Recording Rules，我们不仅能显著降低 Prom","/article/119",301,"2026-01-06 11:51:58","2026-01-06 11:53:45",{"id":303,"category_id":44,"title":304,"keywords":6,"description":305,"image_url":6,"url":306,"hits":307,"is_recommend":73,"is_top":73,"create_time":308,"update_time":309},118,"GitOps 落地实践：ArgoCD + Kustomize 实现声明式基础设施管理(二)","四、最佳实践和注意事项4.1 最佳实践4.1.1 性能优化优化点一：减少 Git 轮询频率# argocd-cm ConfigMapapiVersion: v1kind: ConfigMapmetadata:  name: argocd-cm  namespace: argocddata:  timeout.reconciliation: 300s  # 默认 180","/article/118",305,"2026-01-06 11:49:00","2026-01-06 11:49:34",{"id":311,"category_id":44,"title":312,"keywords":6,"description":313,"image_url":6,"url":314,"hits":315,"is_recommend":73,"is_top":73,"create_time":316,"update_time":317},117,"GitOps 落地实践：ArgoCD + Kustomize 实现声明式基础设施管理(一)","一、概述1.1 背景介绍GitOps 作为云原生时代的运维范式，将 Git 作为基础设施和应用配置的单一事实来源，通过声明式配置和自动化同步机制，实现了配置管理的版本控制、审计追溯和快速回滚。ArgoCD 作为 CNCF 毕业项目，提供了完整的 GitOps 工作流，支持多集群管理、RBAC 权限控制、SSO 集成等企业级特性。结合 Kustomize 的配置管理能力，能够优雅地解决多环境配置差异、敏感信息管理、配置复用等问题。在传统的 CI/CD 流程中，往往由 CI 工具直接执行 kubec","/article/117",310,"2026-01-06 11:45:03","2026-01-06 11:48:56",{"id":319,"category_id":40,"title":320,"keywords":321,"description":322,"image_url":6,"url":323,"hits":324,"is_recommend":73,"is_top":73,"create_time":325,"update_time":326},116,"运维部门年度2025工作总结与2026工作规划应该如何写？","运维部门年度2025工作总结,2026工作规划","2025年，运维部在公司“数字化转型深化”战略引领下，以“稳定为基、效率为纲、安全为盾、创新为翼”为核心导向，全面支撑核心业务系统运行、推动技术架构迭代、强化团队能力建设。 全年实现核心业务系统可用性99.985%，较2024年提升0.02个百分点；故障平均恢复时间（MTTR）从42分钟压缩至29分钟，下降31%；云资源成本同比降低16.8%，自动化运维覆盖率从65%提升至83%，未发生重大生产安全事故，圆满完成年度目标。现将全年工作及2026年规划汇报如下：2025年核心工作成果（数","/article/116",297,"2026-01-06 11:20:58","2026-01-06 11:44:04",{"id":328,"category_id":40,"title":329,"keywords":330,"description":331,"image_url":6,"url":332,"hits":333,"is_recommend":73,"is_top":73,"create_time":334,"update_time":335},115,"Kubernetes 100个常用命令","100 个 Kubectl 命令","这篇文章是关于使用 Kubectl 进行 Kubernetes 诊断的指南。列出了 100 个 Kubectl 命令，这些命令对于诊断 Kubernetes 集群中的问题非常有用。这些问题包括但不限于：• 集群信息• Pod 诊断• 服务诊断• 部署诊断• 网络诊断• 持久卷和持久卷声明诊断• 资源使用情况• 安全和授权• 节点故障排除• 其他诊断命令：文章还提到了许多其他命令，如资源扩展和自动扩","/article/115",3642,"2023-11-02 14:09:30","2023-11-02 14:10:05",{"id":182,"category_id":44,"title":183,"keywords":184,"description":185,"image_url":6,"url":186,"hits":187,"is_recommend":73,"is_top":73,"create_time":188,"update_time":189},1784716029539]