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Docker environment for applying machine learning jobs to discover anomalies in the number of tweets on a topic

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itarano/elasticsearch-machine-learning-twitter

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elasticsearch-machine-learning-twitter

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Requeriments

Docker or Docker for Windows, docker-compose is used to environment deploy.

Deploy

Windows:

Start: bin/start-up.bat

Stop: bin/stop-remove.bat

Linux:

Start: bin/start-up.sh

Stop: bin/stop-remove.sh

You can easily deploy without using bin scripts doing docker-compose up, 'up' command create containers, network and start all the services. To stop and remove all containers and network, you can do docker-compose down.

Also you can uncomment the docker-compose lines 'volumes' for elasticsearch service in docker-compose.yml file and persist the information you generate in kibana (i.e. machine learning jobs). To deploy the environment in the future is unnecessary up filebeat (ingest dataset job), so you can do docker-compose up kibana which automatically deploy elasticsearch too.

Software environment

Elasticsearch: 6.7.0

Kibana: 6.7.0

Filebeat: 6.7.0

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Docker environment for applying machine learning jobs to discover anomalies in the number of tweets on a topic

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