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Elasticsearch 8 and the Elastic Stack: In Depth and Hands On

Elasticsearch 8 and the Elastic Stack: In Depth and Hands On

Complete Elastic search tutorial – search, analyze, and visualize big data with Elasticsearch, Kibana, Logstash, & Beats

Elasticsearch and the Elastic Stack are important tools for managing massive data. You need to know the problems it solves and how it works to design the best systems, and be the most valuable engineer you can be.

Elasticsearch 8 is a powerful tool for analyzing big data sets in a matter of milliseconds! It’s increasingly popular technology for powering search and analytics on big websites, and a valuable skill to have in today’s job market. This course covers it all, from installation to operations. Learn how to use Elasticsearch 8 and implement it in your work within the next few days.

We’ve teamed up with Coralogix to co-produce the most comprehensive Elastic Stack course we’ve seen— with over 100 lectures including 15 hours of video.

We’ll show you how to set up search indices on an Elasticsearch 8 cluster (if you need Elasticsearch 6 or 7 – we have other courses on that), and query that data in many different ways. Fuzzy searches, partial matches, search-as-you-type, pagination, sorting – you name it. And it’s not just theory, every lesson has hands-on examples where you’ll practice each skill using a virtual machine running Elasticsearch on your own PC.

We’ll explore what’s new in Elasticsearch 8 and illustrate all the new syntax requirements of Elasticsearch commands, now that things deprecated through the Elasticsearch 7 have been removed. Almost every hands-on activity has been re-recorded to ensure compatibility with Elasticsearch 8.

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What you’ll learn

  • Install and configure Elasticsearch 7 on a cluster
  • Create search indices and mappings
  • Search full-text and structured data in several different ways
  • Import data into Elasticsearch using various techniques
  • Integrate Elasticsearch with other systems, such as Spark, Kafka, relational databases, S3, and more
  • Aggregate structured data using buckets and metrics
  • Use Logstash and the “ELK stack” to import streaming log data into Elasticsearch
  • Use Filebeats and the Elastic Stack to import streaming data at scale
  • Analyze and visualize data in Elasticsearch using Kibana
  • Manage operations on production Elasticsearch clusters
  • Use cloud-based solutions including Amazon’s Elasticsearch Service and Elastic Cloud

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