Store, search, and analyze your data with ease using ElasticSearch 5.0
About This Video
Get the basics of ElasticSearch concepts, APIs and best use cases
Create large-scale ElasticSearch clusters and build analytics using aggregation
Implement Elastic Search 5.0 in the logstash Apache web log analysis.
This course is a step-by-step guide to using Elasticsearch in combination with the rest of the ELK stack (now called Elastic Stack) to ship, parse, store, and analyze logs.
You’ll start this course by getting an understanding of what ElasticSearch is, what it’s used for, and why it’s important. Then, you’ll be introduced to the new features in ElasticSearch 5.0. We’ll go through each of the fundamental concepts of ElasticSearch such as queries, indices, and aggregation.
You’ll find out how to add more power to your searches using filters, ranges, and more. You’ll also see how ElasticSearch can be used with the other components of the Elastic Stack such as LogStash, Kibana, and Beats. Finally, we’ll take a walk through getting ElasticSearch up and running on the popular logstash Apache web log analysis.
Aside from learning how to add more power to your searches with filters, ranges, and more, you'll also see how ElasticSearch can be used with the other components of the Elastic Stack such as LogStash, Kibana and Beats. Finally, we’ll build, test and run our first Logstash pipeline to analyze Apache web logs. This step combines all the understanding of ElasticSearch, Logstash, Kibana and the lightweight data shipper FileBeat that we acquired from previous sections.
By the end of this course, you will have a firm understanding of all the fundamentals of ElasticSearch 5.0, along with knowledge of practical real world usage.