Elasticsearch is a search engine and NoSQL database. It’s designed for storing, retrieving, and managing semi-structured data. In the context of ELK, it’s used for storing log data in a scalable, distributed manner, making it possible to perform complex search and analysis on large volumes of data.
Logstash is a log processing tool that can be used to collect, process and store logs. It can be used to extract data from various sources, transform the data, and send it to a target like Elasticsearch. Logstash is used to collect log data from various sources, transform it, and send it to Elasticsearch for indexing and analysis.
Kibana is a data visualization tool that provides a web-based interface for searching, exploring, and visualizing data stored in Elasticsearch. It provides an easy-to-use interface for analyzing log data, creating visualizations and dashboards, and detecting patterns and trends. Kibana is used to interact with the log data stored in Elasticsearch and provide insights into the data through visualizations and dashboards.
Features/Benefits of ELK
Centralized log management
ELK provides a centralized repository for log data, making it easy to manage and search logs from multiple sources.
ELK enables real-time analysis of log data, making it possible to quickly detect and respond to issues.
Kibana provides a wide range of customizable visualizations that can be used to represent log data in a variety of ways.
ELK is a cost-effective solution for log analysis, especially compared to proprietary tools.
ELK can be used to analyze log data from a wide range of sources, including application logs, system logs, network logs, and security logs.
Kibana provides a user-friendly interface for searching, exploring, and visualizing log data, making it accessible to users with varying levels of technical expertise.