Analyzing data is a critical element to running a successful business. Whether that data comes from a structured or unstructured source, it is crucial to understanding how the business is performing and what steps might be taken to improve that performance. The ELK stack is perfect for this. The ELK stack is the combination of these three important tools (all open source) to provide your business with accurate, real-time data analytics and in-depth analysis: ElasticSearch, Logstash and Kibana. Today we will be discussing the role of each of these tools and how they can be used together to create a clear picture for business owners, investors and analysts.
What Is ElasticSearch?
The easiest way to explain ElasticSearch is to describe it as a specialized search engine focused exclusively on real-time analysis of data that is being transferred. Built on top of Apache Lucene, ElasticSearch uses a RESTful architecture offering full-text search functionality. It is also document-oriented, enabling users to store data as JSON. These factors make ElasticSearch a very simple, flexible but powerful tool.
What Is Logstash?
Just as the name indicates, Logstash is used to collect, parse and store different logs. It can also be used for managing events. Logstash is important to the ELK stack because it handles shipping and indexing these logs and events, which makes them available in ElasticSearch.
What Is Kibana?
Kibana is the user-facing element to ELK stack. It provides end users with a clean interface for viewing, searching a visualizing data for any and all logs. It presents all of the data managed in ElasticSearch and Logstash inside a very customizable interface, which includes a histogram as well as numerous other panels designed to assist in real-time analysis and search. No matter what the user is looking for, the combination of these 3 open source tools enables him/her to monitor real-time updates about very specific subjects or queries.
How the ELK Stack Tools Work Together
To better understand how the three tools that comprise ELK stack work together, begin by thinking of Logstash as a sort of pipe liner, if you will. Logstach reads input from one or many sources and then output that data wrapped in a JSON message. From there, a broker, like Redis, will cache the message until another Logstash agent picks up the data in its final format and sends it to a finalized output – ElasticSearch. Within ElasticSearch, the data is indexed and then stored later in a searchable database.
From there, end users are able to login to Kibana to access the ElasticSearch functionality which enables them to visualize and search through all the logs that have been transferred through the database. The entire system is completely scalable, as there are many different “shippers” running on many different “hosts” to monitor the log files and ship the messages to their appropriate brokers.
Using each of these 3 tools together is one of the most efficient and effective methods of data collection and organization available. The data is easy to manage and sift through, even in real-time. If you’re a business owner, consultant, or anyone else looking to gain important insights about a business, deploying the ELK stack is the best move you can make.