Introduction to information retrieval
Data indexing: concepts, forms
Presentation of the Elastic suite: products, contexts of use
Discovery of the ElasticSearch search engine
Connectors and transformation tools of Logstash
Kibana for analysis and visualization
Suite distributions

Workshop: Architecture and installation of the ELK stack

ElasticSearch: origin, detail of the search engine, technologies / functionalities
Fundamental concepts: Index, Document, Cluster, Node, Replica
Presentation of available APIs (REST): Indexing, search
Indexing: management of indexes, documents and mapping, metadata
Types of fields
Analyzers
Use of filters
Search with the engine: types, filters, relevance score, faceted search
Aggregation, Bucket, Measure
Geo-location management: points, precision, shapes
Performance measurement
Data modeling

Workshop: index creation and modifications – manipulation of the API’s searches – use of analyzers

Input data management: plugins, supported formats
Output data management
filters
DSL Logstash

Workshop: Logstash configuration and data management

Kibana: features, architecture, available plugins
Searches
Visualization Templates
Custom Visualisations

Workshop: use of predefined visualisations – creation of personalized visualisations and formatting

The ELK suite in a high availability (HA) environment
Setting up an Elasticsearch cluster
Management of several Logstash instances: architecture, message queue,
Kibana filebeat for the   Elasticsearch distribution
Tuning and monitoring requests

Workshop: implementation of an HA architecture with the Elastic suite

Optimization of the deployment of the suite
Management of hardware and network resources
Monitoring tools (technical metrics)
Backup and restore

Workshop: use of a monitoring and load testing tool – implementation of a backup and restore strategy