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Elasticsearch Engineer 1

ElasticSearch is one of the leading search platforms. With LogStash, added for log collection, and Kibana for the dashboard, it becomes ELK, a popular log collection and analysis tool. New features...

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$3,800 USD
Course Code CUSTOM-ELK-X-PACK
Duration 4 days
Available Formats Classroom

  • ElasticSearch is one of the leading search platforms. With LogStash, added for log collection, and Kibana for the dashboard, it becomes ELK, a popular log collection and analysis tool. New features include security, monitoring, and machine learning. All together, these components provide a platform for industrial search applications, and all of them are covered in this course.
  • This course is intended for data engineers and data scientists, architects, developers, and administrators who are want to build versatile search solutions. It gives them practical level of experience, achieved through a combination of 50% lecture and 50% lab work.
  • The course will give you the knowledge that will prepare you for the Elastic Certified Engineer Exam.

Skills Gained

After completing the course, the participants will be able to do the following tasks using Elastic

  • Data Management
  • Searching Data
  • Developing Search Applications
  • Data Processing
  • Cluster Management

Who Can Benefit

Data Engineers, Data Scientists, Architects, Developers, Administrators

Prerequisites

  • Be able to navigate Linux command line
  • (resources to up-skill attendees on basic Linux will be provided in advance of the training for participants who may be unfamiliar with open source operating systems).
  • Basic knowledge of command line Linux editors (vi or nano)

Course Details

Lab Environment:

  • Working environment will be provided for students. Students would only need an SSH client and a browser.
  • Zero Install: There is no need to install software on students’ machines.

Elasticsearch

  • Elasticsearch functionality
  • Indexing, updating, and deleting data
  • Searching your data
  • Analyzing your data
  • Searching with relevancy
  • Exploring your data with aggregations
  • Types of aggregations
  • Metric and bucket aggregations
  • Common aggregations
  • Relations among documents
  • Scaling out
  • Improving performance
  • Shards and high availability
  • Shard and high performance
  • Cluster administration

Kibana

  • Data Visualization
  • The Kibana Dashboard
  • Designing for Scale
  • Use cases

Integrations

  • What’s in Integrations?
  • X-Pack now integrated into Elasticsearch
  • Beats
  • Elastic agent
  • Web crawler

Security threat detection and response

  • Introduction to security
  • Security in Elastic

Machine Learning

  • Machine learning in Elastic
  • Generative AI on Elastic