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Check your elasticsearch listen in /etc/elasticsearch/elasticsearch.yml Check if elasticsearch is up :) (ps -ef |grep elasticsearch) If not restart it. And check if you don't firewall your 9200 port . because kibana need to connect to elasticsearch . All kibana job is done with request on elasticsearch database on port 9200 .


You always have some kind of overhead when you store your logs in ES because ES will store each single line from your logs as document (in json) with added information. Count your log lines and compare it with the count of docs in your index to find out if there is maybe a loop or a duplication of data. Show us your elasticsearch.yml for more information ...


It is enough to rename the folder holding the data. The folder created by default for a standalone server is called elasticsearch, renaming it to the cluster name (mycluster in the context of the question) makes the previous data available.


I did something similar using Nginx running in front of ES. It is possible to setup "authorization" in Nginx based on the keywords in the URL. Refer to the use case defined in this document: http://www.elasticsearch.org/blog/playing-http-tricks-nginx/


If someone will be interested about how I resolve an issue with logs... After some investigation, I found that you can actually set the amount of logs to store in logging.yml which is by default lie in /etc/elasticsearch, by adding: maxBackupIndex: x line like this: file: type: dailyRollingFile file: ${path.logs}/${cluster.name}.log datePattern: ...


The ES logs contain information about your running application i.e. errors. If you don't see any problems within your logs you can safely delete old logs by hand or by logrotate. To reduce the size of your indexes you have to remove some docs from them because the indexes are the place where ES stores the data. Do not use logrotate for indexes or strange ...


Elasticsearch is a search and index kind of database, build and optimized for searching and analytics, not for caching. For a caching server you would use Memcached. But these days there are other alternatives such as Redis (Key-Value database) which is much faster and supports more complex solutions. Carl Zulauf did a great job describing the differences ...

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