ELK Stack (Elasticsearch, Logstash, Kibana)

Description

This course provides an introduction to using the ELK stack (Elasticsearch, Logstash, Kibana) for reading, normalizing, processing, indexing, and visualizing data and time series. The core components of the Elastic suite will be presented through a practical approach with exercises, exploring their applications and examining real-world use cases that illustrate their configuration and functionalities.

Elasticsearch, the main product of the suite, is a professional search engine capable of effectively handling Big Data in any application or website. It is currently the most widely used search engine in the world. Elasticsearch natively supports clustering and distributed architectures, providing full-text search functionality with a RESTful interface, independent of the programming language used, utilizing JSON for data representation and HTTP as the communication protocol. Elasticsearch can be used to search any type of document and provides a scalable near-real-time search system with multi-tenancy support.

Kibana is the tool in the suite that allows users to navigate and visualize data contained in Elasticsearch indices. Leveraging Elasticsearch’s data search and aggregation capabilities, Kibana makes it easy and intuitive to create graphs and dashboards for Big Data analysis.

Logstash is the component of the stack responsible for retrieving, filtering, normalizing, and sending data from heterogeneous sources to Elasticsearch. Its plugin architecture allows it to work with different data sources with minimal effort.