docker-elk-ssl/README.md

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# Fig ELK stack
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[![Join the chat at https://gitter.im/deviantony/fig-elk](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/deviantony/fig-elk?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
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Run the ELK (Elasticseach, Logstash, Kibana) stack with Fig and Docker.
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It will give you the ability to quickly test your logstash filters and check how the data can be processed in Kibana.
NOTE: There is an issue with Docker 1.4.0 which prevents Fig from creating volumes. It has been fixed in Docker 1.4.1.
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Based on 3 Docker images:
* [elk-elasticsearch](https://github.com/deviantony/docker-elk-elasticsearch)
* [elk-logstash](https://github.com/deviantony/docker-elk-logstash)
* [elk-kibana](https://github.com/deviantony/docker-elk-kibana)
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## Installation and use
1. Install [Docker](http://docker.io).
2. Install [Fig](http://fig.sh).
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3. Clone this repository
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4. Update the logstash-configuration in logstash-conf/logstash.conf (test your filters here)
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5. fig up
6. nc localhost 5000 < /some/log/file.log
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7. http://localhost:8080 to see the messages show up in Kibana 3.
8. http://localhost:5601 to use Kibana 4.
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This will create 4 Docker containers with Elasticsearch, Logstash, Kibana 3 and Kibana 4 running in them and connected to each other. Four ports are exposed for access:
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* 5000: Logstash TCP input.
* 9200: Elasticsearch HTTP (With Marvel plugin accessible via [http://localhost:9200/_plugin/marvel](http://localhost:9200/_plugin/marvel))
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* 8080: Kibana 3 web interface.
* 5601: Kibana 4 web interface.