The following points explain the various advantages of Logstash. Some of the most commonly used plugins are – Elasticsearch, File, Graphite, Statsd, etc. Lastly, it sends the output event after complete processing to the destination by using plugins. This is the last stage in the Logstash pipeline, where the output events can be formatted into the structure required by the destination systems. Some of the most commonly used filter plugins are – Grok, Mutate, Drop, Clone and Geoip. Logstash offers various plugins to help the developer to parse and transform the events into a desirable structure. A developer can use pre-defined Regex Patterns by Logstash to create sequences for differentiating between the fields in the events and criteria for accepted input events. This is the middle stage of Logstash, where the actual processing of events take place. Some of the most commonly used plugins are – File, Syslog, Redis and Beats. Logstash offers various plugins to get data from different platforms. This is the first stage in the Logstash pipeline, which is used to get the data in Logstash for further processing. Then sends to an output destination in the user or end system’s desirable format. The input data is entered in the pipeline and is processed in the form of an event. It comprises of data flow stages in Logstash from input to output. In this tutorial, this event is referred with various names like Logging Data Event, Log Event, Log Data, Input Log Data, Output Log Data, etc. Logstash offers an Event API to developers to manipulate events. Logstash uses this object to store the input data and add extra fields created during the filter stage. It is the main object in Logstash, which encapsulates the data flow in the Logstash pipeline. The key concepts of Logstash are as follows − Event Object
Logstash is open source and available under the Apache license version 2.0. Logstash can also be used for handling sensors data in internet of things. Logstash provides a variety of filters, which helps the user to find more meaning in the data by parsing and transforming it. Logstash can also handle http requests and response data.
Logstash can handle all types of logging data like Apache Logs, Windows Event Logs, Data over Network Protocols, Data from Standard Input and many more. Logstash can collect data from different sources and send to multiple destinations. The general features of Logstash are as follows − The data source can be Social data, E-commerce, News articles, CRM, Game data, Web trends, Financial data, Internet of Things, Mobile devices, etc. It collects different types of data like Logs, Packets, Events, Transactions, Timestamp Data, etc., from almost every type of source. Logstash is written on JRuby programming language that runs on the JVM, hence you can run Logstash on different platforms. It helps in centralizing and making real time analysis of logs and events from different sources. Logstash is a tool based on the filter/pipes patterns for gathering, processing and generating the logs or events.