代码改变世界

Docker Stack 笔记

  AndrewCja  阅读(348)  评论(0编辑  收藏  举报

Docker Compose (Docker Stack)

 

image

Specify the image to start the container from. Can either be a repository/tag or a partial image ID.
If the image does not exist, Compose attempts to pull it, unless you have also specified build, in which case it builds it using the specified options and tags it with the specified tag.

 

deploy

(resource limits) This only takes effect when deploying to a swarm with docker stack deploy, and is ignored by docker-compose up and docker-compose run.

 

depends_on

Express dependency between services. depends_on does not wait for db and redis to be “ready” before starting web - only until they have been started. If you need to wait for a service to be ready, see Controlling startup order (wait-for-it.sh) for more on this problem and strategies for solving it.

 

networks

Networks to join, referencing entries under the top-level networks key.

 

ports

(Port mapping) Either specify both ports (HOST:CONTAINER), or just the container port (an ephemeral host port is chosen).

 

environment

Environment variables with only a key are resolved to their values on the machine Compose is running on, which can be helpful for secret or host-specific values.
environment:
- SHOW=true
- SESSION_SECRET

 

volumes

bind mount, named volume
When you use a bind mount, a file or directory on the host machine is mounted into a container. The file or directory is referenced by its absolute path on the host machine. By contrast, when you use a volume, a new directory is created within Docker's storage directory on the host machine, and Docker manages that directory's contents. Volumes have several advantages over bind mounts.
The source of the mount. For bind mounts, this is the path to the file or directory on the Docker daemon host. May be specified as source or src.
The destination takes as its value the path where the file or directory is mounted in the container. May be specified as destination, dst, or target.

 

logging

The default driver json-file, has options to limit the amount of logs stored. To do this, use a key-value pair for maximum storage size and maximum number of files:
options:
max-size: "200k"
max-file: "10"
The example shown above would store log files until they reach a max-size of 200kB, and then rotate them. As logs grow beyond the max limits, older log files are removed to allow storage of new logs.

 

 

docker-stack.yml

复制代码
# docker stack deploy -c docker-stack.yml
version:
"3.5" x-logging: &graylog-logging driver: gelf options: gelf-address: "udp://graylog-svc:12201" x-default-logging: &default-logging driver: json-file x-deploy: &default-limits resources: limits: memory: 256M x-environment: &rcs-config-server-url RCS_CONFIG_SERVER_URL=http://config-server:19050/config services: redis: image: "redis:latest" # logging: *graylog-logging deploy: *default-limits networks: - outside ports: - "6379:6379" volumes: - /u/docker/redis/config:/usr/local/etc/redis

traffic-mgr: image: "dck0.prime/prime-rcs-traffic-manager:${RCS_TRAFFIC_VERSION:-0.0.1-SNAPSHOT}" # logging: *graylog-logging deploy: *default-limits depends_on: - config-server networks: - outside ports: - "19090:19090" - "16001:16001" environment: - *rcs-config-server-url - RCS_CONFIG_CLIENT_PROFILE=qa - LOGBACK_LOGSTASH_URL=10.102.129.23:5044 - APM_AGENT_ACTIVE=true - JPDA_ADDRESS=16001 - JPDA_TRANSPORT=dt_socket volumes: - /u/docker/nginx/html/logs/rcs:/rcs/logs path-plan: image: "dck0.prime/prime-rcs-path-plan:${RCS_PATH_PLAN_VERSION:-0.0.1-SNAPSHOT}" # logging: *graylog-logging deploy: *default-limits networks: - outside ports: - "18020:80" environment: - RCS_MISSION_SERVER=http://mission-mgr:19030 volumes: - /u/docker/nginx/html/logs/rcs:/RcsPathPlan/logs networks: outside: external: true name: qa-subnet
复制代码

 

编辑推荐:
· 如何编写易于单元测试的代码
· 10年+ .NET Coder 心语,封装的思维:从隐藏、稳定开始理解其本质意义
· .NET Core 中如何实现缓存的预热?
· 从 HTTP 原因短语缺失研究 HTTP/2 和 HTTP/3 的设计差异
· AI与.NET技术实操系列:向量存储与相似性搜索在 .NET 中的实现
阅读排行:
· 周边上新:园子的第一款马克杯温暖上架
· Open-Sora 2.0 重磅开源!
· 分享 3 个 .NET 开源的文件压缩处理库,助力快速实现文件压缩解压功能!
· Ollama——大语言模型本地部署的极速利器
· DeepSeek如何颠覆传统软件测试?测试工程师会被淘汰吗?
点击右上角即可分享
微信分享提示