Linux Enterprise-docker cluster compose and high-availability Docker swarm

One. Docker Compose

Docker Compose divides the managed containers into three tiers, engineering (project), Services (service), and Containers (CONTAIENR). All files (docker-compose.yml, extends files, or environment variable files, etc.) in the directory under which Docker Compose runs are part of a project, and the current directory name is the same if no specific project name is specified. A project can contain multiple services, each of which defines the image, parameters, and dependencies that the container runs. One service can include multiple container instances, and Docker Compose does not solve the problem of load balancing, so other tools are needed to realize service discovery and load balancing.
Docker Compose is a tool for creating and running multi-container applications. Using Compose first requires writing
The Compose file describes multiple container services and the associations between them, and then launches all the containers by command based on the configuration.
Dockerfile can define a container, and a Compose template file (YAML format) can define an application that contains multiple interrelated containers. The Compose project was written in Python, based on the Docker API we will learn in the following experiment.

Two. Docker Compose configuration test

Configuring the Environment redhat7.2

1. Put docker-compose-linux-x86_64 files under/bin, and do soft links and executable permissions to facilitate the invocation of commands

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2. Test import Haproxy and nginx image, do load balancing

3. Write the Compose configuration file under TMP

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4. Creating Backend Services

Web1 for HTTPD,WEB2 and WEB3, respectively, to create a default access directory

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5. Set up the configuration installation httpd service and boot httpd service files in the Web1 httpd service

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6. Build Haroxy.cfg Load Balancer profile in Haproxy

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7. Executing the docker-compose up command in the compose directory will consolidate output from all containers

docker-compose Complete structure

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8. Configuration Complete for load balancing

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9. Health Check , close web3, Access normal , restart Web3, service OK

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Three. High availability of load balancer for Docker swarm

Swarm is a relatively simple set of tools that Docker launched in early December 2014 to manage the Docker set
Group, it turns a group of Docker hosts into a single, virtual host. Swarm using the standard Docker API
Interface as its front-end access entry, in other words, various forms of Docker client (Docker client in Go, Docker_py,docker, etc.) can communicate directly with Swarm. Swarm almost all in the Go language to complete development. Swarm Deamon is just a scheduler (Scheduler) plus router (router), Swarm itself does not run the container, it just accepts requests sent by the Docker client, dispatches the appropriate node to run the container, which means that even Swarm For some reason, the nodes in the cluster will also run as usual, and when Swarm resumes running, it collects the rebuilt cluster information.

1. Configuring the Environment

redhat7.2,7.2 comes with swarm tools

Server1 Master

Server2 from

Server3 from

2. Installation

Server1,server2,server3 installing Docker and starting the service

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3. Create a cluster

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Copy the Docker swarm join to 172.25.29.1:2377 and copy them into the shell of Server2 and Server3, respectively.

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View node status on Server1 after completion, cluster configuration complete

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4.Docker Swarm load balancing High availability experiment

Server1,server2,server3 Import Nginx Image

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5. Import flask frame Mirror, Server1,server2,server3

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Due to load balancing, host names need to be displayed on Nginx Web pages to differentiate load balancing on different backend

A Python-written statement that displays the hostname, importing the flask and OS

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6.server1 single-machine run read Python file, see if you can see the host name

Open the flask image and put the demo.py script under root

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Commit Save

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Test whether the Python script that writes the host name is displayed as normal

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can display container name, test normal, can encapsulate commit

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7. Export the mirrored Python:demo image with the demo.py script added to the test to Demo.tar

Close the container and export

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8.server2 and Server3 Import flask and demo images respectively

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9. Create a cluster named Flask and start 3 backend service nodes to read the demo.py script under Python

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10. Browser Test after launch

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3 Back-end service polling

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11. Turn back-end services into 8 nodes

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Display polling

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Four. Docker swarm Visual Web monitoring interface

1. Import Visualizer image

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2. Create

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View Container

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3. Browser input address, view monitoring interface

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4. Timed Updates

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Update-parallelism 2 per update 2

Update-delay 10s updated 1 times every 10 seconds

Nginx Update Nginx Image every time

To update a cluster named flask

Graphic Change Image:nginx

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Linux Enterprise-docker cluster compose and high-availability Docker swarm