ElasticSearch 6.1 with Beats, Logstash and Kibana.

Explore the basics of Elasticsearch, including documents, IDs, and indexing, and learn how primary and replica sources enable scalable, durable, distributed search with horizontal scaling.

Learn to install Elasticsearch 6.1 on Ubuntu in a virtual machine, set up a cluster, and configure basics with Beats, Logstash, and Kibana.

Learn how to create an Elasticsearch cluster, configure master and data nodes, manage discovery, and create an index.

Learn Kibana basics and installation to visualize data from an Elasticsearch cluster, explore indices and documents, and leverage geo maps, time-series visuals, monitoring, security with X-Pack, and API data export.

Explore Logstash introduction: learn how it ingests data from multiple sources via input plugins and Kafka, processes it in a pipeline, and forwards events to Elasticsearch for analysis with Beats.

Install and run Logstash, set up a basic input-output pipeline, and push logs to Elasticsearch via a template-backed index. Inspect simple files, parsed events, and ip-based location for alerts.

Beats introduces a lightweight data shipper that collects log lines and forwards them to Elasticsearch or Logstash, enabling monitoring and visualization in Kibana, with a small memory footprint.

Deep dive into filebeat, explaining how harvester and prospector read log content, manage open and closed files, and use the registry to resume and reprocess log lines.

Design Kibana visualizations for log data collected with beats and indexed in Elasticsearch. Learn to explore indices, display log records, and build visualizations across time.

Explore ELK 6 new features and how the updated Beats integrate with the Elasticsearch 6.1 suite, highlighting improvements and new capabilities introduced in this release.