95 lines
2.6 KiB
Markdown
95 lines
2.6 KiB
Markdown
Docker Compose Files
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===
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Some typical docker compose examples.
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If you're not familiar with Docker, can have a look at these books (in CN):
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* [Docker Practice](https://github.com/yeasy/docker_practice)
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# Install Docker&Docker Compose
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```bash
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$ curl -sSL https://get.docker.com/ | sh
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$ sudo pip install docker-compose
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```
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# Docker-compose Usage
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See [Docker Compose Documentation](https://docs.docker.com/compose/).
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# Examples files
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## [consul-discovery](consul-discovery)
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Using consul to make a service-discoverable architecture.
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## [discuz_php_apache_mysql](discuz_php_apache_mysql)
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Discuz with apache and mysql.
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## [elk](elk)
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ELK example.
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## [elk_netflow](elk_netflow)
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Elk cluster, with netflow support.
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```sh
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docker-compose scale es=3
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```
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## [haproxy_web](haproxy_web)
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A simple haproxy and web applications cluster.
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## [hyperledger_fabric](hyperledger_fabric)
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Quickly bootup a hyperledger fabric cluster with several validator nodes, without vagrant or any manual configuration.
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Now we support from v0.6 to v1.0.x.
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See [hyperledger_fabric](hyperledger_fabric) for more details.
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## [kafka](kafka)
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Start a simple kafka service for testing.
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## [lnmp_wordpress](lnmp_wordress)
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Deploy nginx, mysql, php + wordpress.
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## [mongo_cluster](mongo_cluster)
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Start 3 mongo instance to make a replica set.
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## [mongo-elasticsearch](mongo-elasticsearch)
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Start mongo (as cluster) and elasticsearch, use a mongo-connector to sync the data from mongo to elasticsearch.
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## [mongo_webui](mongo_webui)
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Start 1 mongo instance and a mongo-express web tool to watch it.
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The mongo instance will store data into local /opt/data/mongo_home.
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The web UI will listen on local 8081 port.
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## [nginx_auth](nginx_auth)
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Use nginx as a proxy with authentication for backend application.
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## [packetbeat_elk](packetbeat_elk)
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Demo the packetbeat, elasticsearch and kibana.
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Some kibana [dashboard config](https://github.com/elastic/beats-dashboards) files are included.
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To import them, after all containers startup, go inside the kibana container, and run
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```sh
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$ cd /kibana/beats-dashboards-1.0.1 && ./load.sh http://elasticsearch:9200
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```
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## [redis](redis)
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A redis serer and a redis client (send a PING to the server).
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## [registry_mirror](registry_mirror)
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docker registry mirror, with redis as the backend cache.
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## [spark_cluster](spark_cluster)
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Spark cluster with master and worker nodes.
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```sh
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docker-compose scale worker=2
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```
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Try submitting a test pi application using the spark-submit command.
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```sh
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/urs/local/spark/bin/spark-submit --master spark://master:7077 --class org.apache.spark.examples.SparkPi /usr/local/spark/lib/spark-examples-1.4.0-hadoop2.6.0.jar 1000
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```
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