jackett+sonarr+radarr全自动追剧 version: "3" services: service.jackett: image: linuxserver/jackett container_name: jackett ports: - 9117:9117 environment: - TZ=Asia/Shanghai - PUID=0 - PGID=0 volumes: - /volume3/docker/autodownload/JackettConfig:/config restart: unless-stopped service.Sonarr: image: linuxserver/sonarr:latest container_name: Sonarr ports: - 8989:8989 environment: - TZ=Asia/Shanghai - PUID=0 - PGID=0 volumes: - /volume3/docker/autodownload/SonarrConfig:/config - /volume1/video/tv:/tv - /volume1/video/downloads:/downloads restart: unless-stopped service.radarr: image: linuxserver/radarr:latest container_name: radarr ports: - 7878:7878 environment: - TZ=Asia/Shanghai - PUID=0 - PGID=0 volumes: - /volume3/docker/autodownload/RadarrConfig:/config - /volume1/video/movies:/movies - /volume1/video/downloads:/downloads restart: unless-stopped

docker安装gitlab 一、直接运行docker命令docker run -d --name gitlab \ --restart always \ -p 30001:30001 \ -p 30002:30002 \ -p 30003:22 \ -v /home/$USER/dockerfile/gitlab/etc:/etc/gitlab \ -v /home/$USER/dockerfile/gitlab/logs:/var/log/gitlab \ -v /home/$USER/dockerfile/gitlab/data:/var/opt/gitlab \ gitlab/gitlab-ce:latest额外参数：--hostname 192.168.1.8 \官方文档里有加这一条 --hostname 192.168.1.8 ，实测可以不写，只需手动改配置若要运行企业版，只需把最后 gitlab/gitlab-ce:latest 改成 gitlab/gitlab-ee:latest等安装完成后运行命令获取管理员账号root密码sudo docker exec -it gitlab grep 'Password:' /etc/gitlab/initial_root_password会返回一串密码： Password: akYzRtsctNfxnvVL2EFkK7wwvYXcQOi/spm2Yn/y77Y=二、修改配置：安装完成后，新建项目后，使用git-clone的时候会发现http和ssh的地址都不正确。所以要修改访问地址配置。1、http访问地址修改80端口的修改，我们需要在 gitlab.rb 文件中搜索 external_url ：sudo vim /home/$USER/dockerfile/gitlab/etc/gitlab.rb在后续文本中搜索输入命令 ?external_url 回车?external_url## GitLab URL ##! URL on which GitLab will be reachable. ##! For more details on configuring external_url see: ##! https://docs.gitlab.com/omnibus/settings/configuration.html#configuring-the-external-url-for-gitlab ##! ##! Note: During installation/upgrades, the value of the environment variable ##! EXTERNAL_URL will be used to populate/replace this value. ##! On AWS EC2 instances, we also attempt to fetch the public hostname/IP ##! address from AWS. For more details, see: ##! https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instancedata-data-retrieval.html # external_url 'GENERATED_EXTERNAL_URL' external_url 'http://192.168.1.8:30002' ## Roles for multi-instance GitLab{callout color="#f0ad4e"}此处有30002端口，在网页端点击clone按钮的时候才会显示。前面docker运行命令的时候 30002:30002 两个端口号，后面那个端口号为镜像内部nginx自动配置的端口号，所以docker运行安装命令的时候，想要修改端口就必须前后两个端口都对应修改相同。否则clone的时候不会正确显示，也无法正确使用。{/callout}2、ssh访问地址修改在 gitlab.rb 文件中搜索 _ssh_portsudo vim /home/$USER/dockerfile/gitlab/etc/gitlab.rb在后续文本中搜索输入命令 ?_ssh_port 回车?_ssh_port### Wait for file system to be mounted ###! Docs: https://docs.gitlab.com/omnibus/settings/configuration.html#only-start-omnibus-gitlab-services-after-a-given-file-system-is-mounted # high_availability['mountpoint'] = ["/var/opt/gitlab/git-data", "/var/opt/gitlab/gitlab-rails/shared"] ### GitLab Shell settings for GitLab # gitlab_rails['gitlab_shell_ssh_port'] = 22 gitlab_rails['gitlab_ssh_host'] = '192.168.1.8' gitlab_rails['gitlab_shell_ssh_port'] = 30001 # gitlab_rails['gitlab_shell_git_timeout'] = 800 ### Extra customization # gitlab_rails['extra_google_analytics_id'] = '_your_tracking_id' # gitlab_rails['extra_google_tag_manager_id'] = '_your_tracking_id' # gitlab_rails['extra_one_trust_id'] = '_your_one_trust_id'3.生效配置：进入gitlab容器sudo docker exec -it gitlab /bin/sh重载配置和重启gitlabgitlab-ctl reconfigure && gitlab-ctl restart也可以直接重启容器。三、避坑实测直接运行官方文档带有 --hostname 192.168.1.8 的docker run命令后，使用git-clone会报错404。不带 --hostname 192.168.1.8 安装后修改配置，再重启时gitlab运行不起来。此时进行如下操作可行：隐藏内容，请前往内页查看详情

docker安装mysql 忽略大小写8.0.26docker run -d --name=db3307 -p 3307:3306 -e MYSQL_ROOT_PASSWORD=111111 mysql:8.0.26 --lower_case_table_names=15.7.35docker run -d --name=db3307 -p 3307:3306 -e MYSQL_ROOT_PASSWORD=111111 mysql:5.7.35 --lower_case_table_names=1需要挂载目录的话：docker run -p 3307:3306 --name=db3307 \ --privileged=true \ --restart unless-stopped \ -v /opt/docker/mysql/conf:/etc/mysql \ -v /opt/docker/mysql/logs:/logs \ -v /opt/docker/mysql/data:/var/lib/mysql \ -v /etc/localtime:/etc/localtime \ -e MYSQL_ROOT_PASSWORD=111111 \ -d mysql:8.0.26 \ --lower_case_table_names=1创建数据库命令CREATE DATABASE `testdb` CHARACTER SET 'utf8mb4' COLLATE 'utf8mb4_0900_ai_ci';解决问题Caused by: java.sql.SQLSyntaxErrorException: Expression #1 of SELECT list is not in GROUP BY clause and contains nonaggregated column 'cpms_v2.cpms_project.id' which is not functionally dependent on columns in GROUP BY clause; this is incompatible with sql_mode=only_full_group_bySHOW VARIABLES LIKE '%case%'; SET GLOBAL sql_mode='STRICT_TRANS_TABLES,NO_ZERO_IN_DATE,NO_ZERO_DATE,ERROR_FOR_DIVISION_BY_ZERO,NO_ENGINE_SUBSTITUTION';

Docker Desktop启动Kubernetes 启用k8s后，等待安装完成。1.查看kubectl版本：kubectl version2.配置kubernetes：可选操作：切换Kubernetes运行上下文至docker-desktop（之前版本的context为docker-for-desktop）kubectl config use-context docker-desktop3.验证Kubernetes集群状态kubectl cluster-infokubectl get nodes4.配置Kubernetes控制台（1）部署Kubernetes dashboardkubectl apply -f https://raw.githubusercontent.com/kubernetes/dashboard/v1.10.1/src/deploy/recommended/kubernetes-dashboard.yaml或者kubectl apply -f https://raw.githubusercontent.com/kubernetes/dashboard/v2.0.0-rc5/aio/deploy/recommended.yaml或者kubectl create -f kubernetes-dashboard.yaml（2）检查kubernetes-dashboard应用状态kubectl get pod -n kubernetes-dashboard开启API Server访问代理kubectl proxy（3）通过URL访问kubernetes dashboardhttp://localhost:8001/api/v1/namespaces/kube-system/services/https:kubernetes-dashboard:/proxy/或http://localhost:8001/api/v1/namespaces/kubernetes-dashboard/services/https:kubernetes-dashboard:/proxy/（4）生成令牌Token（需用Windows PowerShell打开，CMD无法执行）$TOKEN=((kubectl -n kube-system describe secret default | Select-String "token:") -split " +")[1]kubectl config set-credentials docker-for-desktop --token="${TOKEN}"echo $TOKEN

CentOS中离线安装ffmpeg 1.下载安装包 ffmpeg-4.1.tar.xz 2.解压安装包：tar -xvJf ffmpeg-4.1.tar.xz3.编译安装： /programFiles/soft/ffmpeg 为自己指定的安装目录./configure --enable-shared --prefix=/programFiles/soft/ffmpeg提示错误：nasm/yasm not found or too old. Use --disable-x86asm for a crippled build. If you think configure made a mistake, make sure you are using the latest version from Git. If the latest version fails, report the problem to the ffmpeg-user@ffmpeg.org mailing list or IRC #ffmpeg on irc.freenode.net. Include the log file "ffbuild/config.log" produced by configure as this will help solve the problem.安装gcc编译器centos 执行yum install gccubuntu 执行apt install gcc安装yasm编译器：centos 执行yum install -y yasmubuntu 执行apt install -y yasm离线安装yasm：{card-describe title="安装步骤"}离线包： yasm-1.3.0.tar.gzwget http://www.tortall.net/projects/yasm/releases/yasm-1.3.0.tar.gztar zxvf yasm-1.3.0.tar.gzcd yasm-1.3.0./configuremake && make install{/card-describe}4.编译（编译时间比较长）和安装：make && make install5.遇到问题 -bash: make: command not found 的解决办法 一般出现这个提示，是因为安装系统的时候使用的是最小化mini安装，系统没有安装make、vim等常用命令，直接yum安装下即可。yum -y install gcc automake autoconf libtool make安装g++:yum install gcc gcc-c++6.修改文件/etc/ld.so.confvim /etc/ld.so.confinclude ld.so.conf.d/*.conf将安装目录的lib包路径 /{make install的目录}/ffmpeg/lib 加入最后/programFiles/soft/ffmpeg/lib/使修改生效：ldconfig7.查看版本/programFiles/soft/ffmpeg/bin/ffmpeg -version8.配置环境变量vim /etc/profile在最后PATH添加环境变量（ /programFiles/soft/ffmpeg/bin 为安装目录）：#set ffmpeg environment PATH=$PATH:/programFiles/soft/ffmpeg/bin export PATH或者这么写：#set ffmpeg env export FFMPEG_HOME=/usr/bin/ffmpeg export PATH=$PATH:${FFMPEG_HOME}/bin使配置生效：source /etc/profile 9.查看环境变量是否配置成功ffmpeg -version参考资料：https://www.cnblogs.com/wpjamer/p/ffmpeg.htmlhttps://www.cnblogs.com/wintercloud/p/11162962.html转码时候遇到问题 Unknown encoder 'libx264'即，缺少libx264解码库，需要安装该库：git clone http://git.videolan.org/git/x264.git && cd x264./configure --enable-static --enable-sharedmake && make installFFMPEG使用NVIDIA的GPU硬件转码（使用N卡加速解码）下载ffmpeg源码sudo apt-get install build-essential yasm cmake libtool libc6 libc6-dev unzip wget libnuma1 libnuma-dev正常编译配置（防止报错，根据提示加上--disable-x86asm）./configure --prefix=/usr/local/ffmpeg --enable-shared --enable-yasm --enable-libx264 --enable-gpl --enable-pthreads --extra-cflags=-I/usr/local/x264/include --extra-ldflags=-L/usr/local/x264/lib --disable-x86asmN卡加速编译配置./configure --enable-nonfree -–enable-cuda-sdk –enable-libnpp --extra-cflags=-I/usr/local/cuda/include --extra-ldflags=-L/usr/local/cuda/lib64编译和安装make && make install同分辨率转码, gpu加速转码，ddr在线模式ffmpeg -y -vsync 0 -hwaccel cuvid -c:v h264_cuvid -i input.mp4 -c:a copy -c:v h264_nvenc -b:v 5M output.mp4变分辨率转码：ffmpeg -y -vsync 0 -hwaccel cuvid –resize 1280x720 -c:v h264_cuvid -i input.mp4 -c:a copy -c:v h264_nvenc -b:v 5M output.mp4corp转码 (-crop (top)x(bottom)x(left)x(right))ffmpeg -y -vsync 0 -hwaccel cuvid –crop 16x16x32x32 -c:v h264_cuvid -i input.mp4 -c:a copy -c:v h264_nvenc -b:v 5M output.mp4scale_cuda filter 转码ffmpeg -y -vsync 0 -hwaccel cuvid -c:v h264_cuvid -i input.mp4 -vf scale_cuda=1280:720 -c:a copy -c:v h264_nvenc -b:v 5M output.mp4scale_npp filter 转码ffmpeg -y -vsync 0 -hwaccel cuvid -c:v h264_cuvid -i input.mp4 -vf scale_npp=1280:720 -c:a copy -c:v h264_nvenc -b:v 5M output.mp41:N 转码ffmpeg -y -vsync 0 -hwaccel cuvid -c:v h264_cuvid -i input.mp4 -vf scale_npp=1920:1080 -c:a copy -c:v h264_nvenc -b:v 5M output1.mp4 -vf scale_npp=1280:720 -c:a copy -c:v h264_nvenc -b:v 8M output2.mp4yuv编码, 1:N 编码ffmpeg -y -vsync 0 -pix_fmt yuv420p -s 1920x1080 -i input.yuv -filter_complex "[0:v]hwupload_cuda,split=4[o1][o2][o3][o4]" -map "[o1]" -c:v h264_nvenc -b:v 8M output1.mp4 -map "[o2]" -c:v h264_nvenc -b:v 10M output2.mp4 -map "[o3]" -c:v h264_nvenc -b:v 12M output3.mp4 -map "[o4]" -c:v h264_nvenc -b:v 14M output4.mp4转码, 1:N 编码ffmpeg -y -hwaccel cuvid –c:v h264_cuvid -i input1.mp4 -hwaccel cuvid –c:v h264_cuvid -i input2.mp4 -map 0:0 -vf scale_npp=640:480 –c:v h264_nvenc -b:v 1M output11.mp4 -map 0:0 -vf scale_npp=320:240 –c:v h264_nvenc -b:v 500k output12.mp4 -map 1:0 -vf scale_npp=1280:720 –c:v h264_nvenc -b:v 3M output21.mp4 -map 1:0 -vf scale_npp=640:480 –c:v h264_nvenc -b:v 2M output22.mp4软解码，gpu resize，gpu编码ffmpeg -y -init_hw_device cuda=foo:bar -filter_hw_device foo -i input1.mp4 -i input2.mp4 -map 0:0 -vf hwupload,scale_npp=640:480 –c:v h264_nvenc -b:v 1M output11.mp4 -map 0:0 -vf hwupload,scale_npp=320:240 –c:v h264_nvenc -b:v 500k output12.mp4 -map 1:0 -vf hwupload,scale_npp=1280:720 –c:v h264_nvenc -b:v 2M output21.mp4 -map 1:0 -vf hwupload,scale_npp=640:480 –c:v h264_nvenc -b:v 1M output22.mp4更多配置通过ffmpeg查看NVIDIA编码器和解码器属性配置更多参考：https://developer.nvidia.com/ffmpegh264_nvenc 编码器配置参考Using_FFmpeg_with_NVIDIA_GPU_Hardware_Acceleration_v01.4.pdf