Once Logstash is installed first to do is to configure to specify what input and output plugins are required and how they are configured. Logstash is a powerful tool for pushing, ingesting data from the distributed system. Also, it runs can put data into other systems at the same time as Amazon web services or database such as Mongo DB and it can import more than one source at a time and output data to more that destination at the time as well. But Logstash offers flexible than webserver example, they can import data from pretty much anywhere it does not have to be local files it could be coming from other systems like Kafka or distributed file system such as S3 or HDFS. A common example is a log file being generated on a web server somewhere and Elasticsearch. Logstash is a tool used to publish real-time data as streaming into Elasticsearch it sits between the source data and the destination target to store that data in. It offers security monitoring, alerting and reporting features and it also contains advance feature in elastics stacks such as machine learning and graphics operation. Finally, another piece of the elastic stack is X-Pack. For example, a collection of weblogs coming in, that you can feed into search in the Elasticsearch overtime automatically, file beat can apply on the webserver and look for new logs file and parse them out structure them in way that Elasticsearch wants and then feed them into a cluster. Logstash and beats framework components of Elastics stack and these are ways publishing into Elasticsearch in real-time in a streaming format. Kibana which sits on top of the Elasticsearch and provide web UI for searching and data visualization. For the right sorts cases of use cases, Elasticsearch can be a very powerful tool and not just for search. Elasticsearch has built-in graph visualization tools and machine learning that makes it a competitor for things like Hadoop, spark in which can give you an answer in milliseconds instead of hours. For example, aggregating server logs and much more. However, Elasticsearch has evolved to be much more than just Lucene spread out across the cluster, it can be used for much more than full-text search now and it can handle structured data and aggregate data very quickly. Elasticsearch is one piece of the Elastics Stack system and it is used as a scalable version of Lucene open-source search framework and it just added the ability to horizontally scale Lucene.
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