For business inquiries : (+1) 438 601-1155
For special requests : (+1) 438 601-1155
For business inquiries : (+1) 438 601-1155
For special requests : (+1) 438 601-1155
The Elasticsearch, Logstash, and Kibana (ELK) training provides comprehensive instruction on indexing, searching, and visualizing data using the ELK stack. ELK enables the creation of powerful log querying platforms, primarily for textual log content. Logstash ingests logs and stores them in Elasticsearch for indexing, while Kibana facilitates searching and visualizing the results. This course equips participants with the skills to effectively utilize ELK for various data analysis tasks.
Module 1: Introduction and Installation of Elasticsearch, Logstash, and Kibana
Overview and history of Elasticsearch, Logstash, and Kibana.
Installation prerequisites and considerations, including cloud-based deployment.
Implementation and setup of Elasticsearch, Logstash, and Kibana.
Configuration specifics for Elasticsearch.
Key principles of Elasticsearch administration.
Application development using Elasticsearch.
Impact of Elasticsearch on existing architectures and applications.
Roles and functionalities of Logstash and Kibana.
Case study: Architectural overview of a high-volume query and indexing Elasticsearch server setup.
Module 2: Understanding Elasticsearch Operations
Introduction to Apache Lucene.
Architecture and fundamental concepts of Elasticsearch.
JSON data exchange format via Service Container.
REST API usage.
Query scoring and relevance.
Data storage and basic search operations.
Hands-on exercises: Storing data in Elasticsearch and performing simple search queries.
Module 3: Advanced Elasticsearch Functionality
Document and data indexing.
Document and data searching.
Document and data analysis.
Result set calculation.
Result filtering and sorting.
Query suggestions.
Result highlighting.
Hands-on exercises: Manipulating data indexing, implementing queries, filtering, and result sorting.
Module 4: Indexing, Searching, and Visualizing Data and Documents
Strategies for contextualizing data with Elasticsearch and Kibana.
Improving data indexing methodologies.
Enhancing search query efficiency.
Geographical relevance in search queries.
Percolation concepts and applications.
