Have you ever heard about Logstash? Suppose not, let us introduce you to the amazing software that helps collect, arrange, and produce logs and events based on filter and pipes patterns. Its primary focus is to enable centralization and analysis of logs and incidents from different outlets in a particular period of time.
The software like Logstash is inscribed on the JRuby JVM programs languages to enable you to run Logstash on different platforms. In addition to that, Logstash is capable of collecting different types of information from almost every source, including Records, Transfers, Packets, Incidents, Timestamp, Data, and much more.
The data source it uses could be E-commerce, News articles, CRM, Game Data, Web trends, Financial Data, Internet of Things, and Mobile device, and the list can go on and on.
Have a look at some of its amazing features
Following are some of the amazing Logstash features:
- Longstash is capable of collecting data from numerous sources and sending it to different destinations.
- It has the capacity to handle all types of data, including Apache logs, Windows Event Logs, Data over Network Protocols, and Data from Standard Input, etc.
- Longstash is also in charge of handling HTTP requests and response data.
- Longstash offers a plethora of filters that can help users find the data relatively more meaningful by parsing and transforming it.
- The Longstash can also be used for tackling sensors data in the Internet of things.
- Lastly, Longstash is an open-source platform, and it is available under the Apache license version 2.0
The Longstash Key Concepts
Following are the main key concepts of Logstash
- Event Object
Event Object is one of the main objects in Longstash that encompasses the data flow in the Longstash pipeline. Longstash mainly uses it to store the input data and add extra fields created during the filter stage.
Moreover, Longstash also provides an Event API to the developers to manipulate events. The event in this tutorial is referred to with various names: Log Data Event, Log Event, Log Data, Input Log Data, Output Log Data, and whatnot.
Pipeline encapsulates data flow stages in Longstash from Input to output. The input data is inserted in the Pipeline and later processed in the form of an event. Later on, the Pipeline sends the data to an output destination either in the users’ or the system’s preferable format.
So, Input is the initial stage in the Longstash pipeline. It is used to get the data in Longstash for the sake of further processing. Longstash renders different plugins to get data from various other platforms. The names of the most commonly used platforms are Syslog, Redis and Beats, and File.
Next up, we have the Filter. It is considered the middle stage of Longstash. It is the place where the real processing takes place. A developer can seek help from a pre-defined Regex Pattern by Longstash to come up with sequences for making a difference between the fields in the events and the criterion for taking input events.
Moreover, Longstash provides different plugins to assist the developers in parsing and transforming the events into a preferable structure. The most desirable filter plugins are Mutate, Drop, Clone and GeoIP, and Grok.
Output, as its name stage, as the final result, and the last stage in the Logstash pipeline. It is the spot where the output events can be formatted into the required structure of the destination systems.
Towards the final stages, the output event sends the events after complete processing to the destination with the help of plugins. The names of the most commonly used plugins are Elasticsearch, File, Graphite, Statsd, and much more.
Here, Following are a few of the advantages of Logstash,
- Logstash provides a regex pattern design for identifying and parsing different fields in different input events.
- It backs and supports a plethora of web servers and data sources for the sake of extracting logging data.
- Logstash renders multiple plugins for parsing and transforming the logging data into the required format.
- Logstash is easy-to-process because of its centralized feature, and it is capable of collecting data from several other sources.
- It has the capacity to support different databases, networks protocols, and several other services as the destination source for the sake of logging events.
- Logstash uses HTTP protocol, enabling the users to upgrade Elasticsearch versions even without the need to upgrade Logstash in lockstep.
- It is quite fast
- It can handle data in different formats, shapes, and sizes.
- The core power of Longstash is its ability to change your data in a jiffy.
- It is easy to configure and keeps configuration files in a plain text format.
- Logstash acts as an all-command line and, therefore, it can get a bit overwhelming for newbie developers.
- The documentation process lacks perfection.
- The persistent queue feature is not impressive.
- The HTTP usage adversely affects the processing of the logging data.
- Logstash is relatively complex and requires a great deal of understanding and analysis of the input logging data.
- The filter longing is not generic; therefore, the users may require to search for the appropriate sequence of patterns to avoid any error in parsing.
Keeping in view all these pros and cons, we have brought some of the amazing Logstash alternatives, so you can have the same experience that you have with Logstash.
Logstash Alternatives and Best Similar Software 2021
Following are some of the amazing alternatives to Logstash.
Next up, on the list of options like Logstash is Stackify. The main focus of Stackify is to render developers with the best resources required for boosting troubleshoot and tracking the produced application as well as servers. Stackify builds conventional IT running tools for network and gadget managers.
With Stackify, the developers spend a significant amount of time dealing with IT operations for repairing apps. However, Stackify does not offer many tools to support the software successfully.
Graylog is yet another best alternative to Logstash. It is mainly known as a log processing structure that is in charge of keeping, indexing, and amazing from numerous sources, which includes structured and disorganized information. With technological advancements, systems are mainly located on various makers adopting a microservice architecture with other microservices. This often results in consuming a great deal of time for visiting various gadgets per time from each microservice. So, Graylog is the perfect solution to avert this situation and save time. It provides immense convenience to users by setting up the logs of different microservices all in a single area.
3. Apache Kafka
Kafka tops the list of the best Logstash alternatives. It was initially established and opened by Linkedin in the year 2011, and it acts as a dispersed community occasion streaming application that has the capacity to manage trillions of occasions on a daily basis. It was initially constructed as a message line; however, now, it has proliferated from a message to line to a wholesome occasion streaming network. Apache Kafka’s preliminary designers are in charge of designing Confluent and provide Kafka with Confluent Framework for easy delivery. Moreover, Kafka’s Confluent Interface has the potential to extend the broadcast experience of operators as well as designers in the development having some social and commercial background.
Next on the list of best Logstash alternatives is Splunk. It is mainly responsible for managing and offering insights into computer data and other various broad information types. Different programs, including CPUs running a web server, IOT computer system, and mobile app logs, produce these data from Splunk. The information produced from Splunk does not need to be supplied to end customers, as it does not retain any industrial worth. However, this alternative has a relatively more powerful mentality, control, and output optimization of the device. Splunk is even powerful enough to read disorganized, badly structured understanding. It can also make the scan, tag, report, and control panels on this information after reading the poorly structured data.
Based on Apache Lucene, Elasticsearch N.V. and published in the year 2010, Elasticsearch is one of the most flexible and easy-to-use open-source Logstash alternatives. Its analysis engine is distributed for all types of data, including textual, numerical, geopolitical, structure, and unstructured data. This alternative is one of the Elastic Stack’s known elements, a collection of open-source tools offered for services like data intake, enhancement, storage, analysis, and finally for the view. And this is all possible because of the plain, REST APIs, dispersed styles, scalability, and speed. In fact, there has been some crazy latest addition to Elastic Stack, as it has been now equipped with a reasonable amount of lightweight transportation agents known as Beats. Its main work is to deliver data to Elasticsearch, usually referred to as the ELKStack.
Next on the list of best Logstash alternatives is Filebeat. This alternative is known for its simplicity and the convenience it offers to the users. Filebeat mainly assists by simply supplying a teeny tiny method to move and centralize records and data. The main reason behind this motif is to disable SSH when users have more than one server, virtual makers, and logging containers. In addition to that, Filebeat offers many other advantages too. For example, it conveniently produces enormous amounts of files and back encryption, and it can also conveniently tackle backpressure. Filebeat is without a doubt a logging agent; its main work is to produce and send the log files to Logstash for further processing. The log files can also be used for elastic search for indexing on the computer.
Apache Flume is one of the most convenient Logstash alternatives. It is basically a mechanism, a service, a toll, or a data intake mainly to gather and bring a significant quantity of streaming information from different sources to a single piece of information like log files and occasions. Moreover, it is a tool with fantastic dependability, circulation, and setup. Mostly, it is developed to copy streaming information to HDFS from various web services.
Kafka is yet another name on the list of apps similar to Logstash. It has been received in Scala & Java and is known as a distributed stream queuing structure. The app is mainly open-source. This Apache Kafka is mainly used in consecutive order in the line for posting and subscribing messages. There is no doubt about its high performance, confidentiality, reliability, and duplication function. In addition to that, the app is clearly scalable, fast, and has a spectacular publishing customer messaging system. All these features make it one of the best Logstash alternatives.
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All these alternatives to Logstash, mentioned above, are the best. All have got superb features. They are reliable, trustworthy, and scalable. At the end, however, the choice depends on the users, their usability, and preferences.