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Elasticsearch 9 and the Elastic Stack: In Depth and Hands On (Udemy.com)

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

4.4
6,758 reviews

Created by: Sundog Education by Frank Kane

Last updated July 2026

Our take

Based on the ratings of 6,758 students, a sample of their written reviews and the syllabus, as the course stood in July 2026. No course pays to be reviewed.

Frank Kane's Sundog Education course is a tour of the whole Elastic Stack rather than a search-only class. About 14 hours across 118 lectures cover installing a cluster, mappings, full-text and structured search, aggregations, Kibana, Logstash and Filebeat, then operations and cloud hosting. The largest section, over four hours, is about getting data in, including integrations with Spark, Kafka and relational databases. It suits working developers or ops people who want to run Elasticsearch, not just query it. The requirements ask for some REST, JSON and Linux familiarity, and that matters, because most lessons happen in a terminal.

Students rate it 4.4 from about 6,800 reviews, and nearly nine in ten give four or five stars. The praise is consistent: short lectures, public datasets you can follow along with, a handy deployment cheat sheet, and Kane connecting theory to hands-on work. Complaints cluster in two places. Setup trips people up, and two one-star reviews say Q&A questions went unanswered, one after a failed install. Two ask for a Docker path and one for a single git repo holding all the commands. One two-star review felt the course leans on installation and typing commands over concepts, and spends too long on integrations with outside tools.

The course was refreshed in July 2026, so the material is current, though one 2021 review complained of old slides. It sits beside the Complete Guide to Elasticsearch and the Elasticsearch Masterclass, and what sets it apart is the ingestion and operations coverage: Logstash, Beats, monitoring, scaling, rolling restarts and cloud hosting. There are no quizzes or coding exercises, so the practice is whatever you do in the VM. Recommended for anyone who needs the whole stack running, less so for someone who only wants sharper queries.

Best forDevelopers or ops people who need to run and feed an Elasticsearch cluster, not just write queries against one.
Skip it ifYou only want to write better search queries, or you need a Docker-based setup and responsive Q&A support.

Pros

  • Short lectures with public datasets, so every step can be followed along in the VM
  • Covers ingestion at scale: Logstash, Filebeat, Spark, Kafka and relational database imports
  • Over two and a half hours on operations: monitoring, scaling, rolling restarts and cloud hosting
  • Refreshed July 2026, rated 4.4 with nearly nine in ten reviews at four or five stars

Cons

  • Installation is where students get stuck, and a few say their Q&A questions went unanswered
  • No Docker setup path and no single repo of commands; one review called the resources scattered
  • No quizzes or coding exercises, and one reviewer found the long integrations section a drag
Gave me the high level overview I needed as a complete beginner while providing enough detail and hands-on activities to get me comfortable.
David Rarig, a student

Labeled all levels, but it assumes REST, JSON and basic Linux comfort; true beginners should expect some terminal friction.

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What you will 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

Course content

10 sections · 118 lectures · 14 hours of video 4 articles

  1. 1Installing and Understanding Elasticsearch 4 free previews11 lectures · 1 hour
  2. 2Mapping and Indexing Data 2 free previews18 lectures · 1.9 hours
  3. 3Searching with Elasticsearch 2 free previews16 lectures · 1.5 hours
  4. 4Importing Data into your Index - Big or Small 2 free previews26 lectures · 4.1 hours
  5. 5Aggregation 1 free preview8 lectures · 45 min
  6. 6Using Kibana 1 free preview8 lectures · 57 min
  7. 7Analyzing Log Data with the Elastic Stack 2 free previews8 lectures · 48 min
  8. 8Elasticsearch Operations 1 free preview16 lectures · 2.7 hours
  9. 9Elasticsearch in the Cloud 1 free preview5 lectures · 28 min
  10. 10You Made It!2 lectures · 6 min

Who it is for

The instructor says it suits

  • Any technologist tasked with fast, scalable searching and analysis of big data sets.

What you need before you start

  • You need access to a Windows, Mac, or Ubuntu PC with 20GB of free disk space
  • You should have some familiarity with web services and REST
  • Some familiarity with Linux will be helpful
  • Exposure to JSON-formatted data will help

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Quality Score

Content Quality
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Video Quality
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Qualified Instructor
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Overall Score : 88 / 100

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Course Description

New for 2021! Elasticsearch 7 is a powerful tool not only for powering search on big websites, but also for analyzing big data sets in a matter of milliseconds! It's an increasingly popular technology, and a valuable skill to have in today's job market. This comprehensive course covers it all, from installation to operations, with over 90 lectures including 8 hours of video.
We'll cover setting up search indices on an Elasticsearch 7 cluster (if you need Elasticsearch 5 or 6 - we have other courses on that), and querying 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 7 - including index lifecycle management, the deprecation of types and type mappings, and a hands-on activity with Elasticsearch SQL. We've also added much more depth on managing security with the Elastic Stack, and how backpressure works with Beats.
We cover, in depth, the often-overlooked problem of importing data into an Elasticsearch index. Whether it's via raw RESTful queries, scripts using Elasticsearch API's, or integration with other "big data" systems like Spark and Kafka - you'll see many ways to get Elasticsearch started from large, existing data sets at scale. We'll also stream data into Elasticsearch using Logstash and Filebeat - commonly referred to as the "ELK Stack" (Elasticsearch / Logstash / Kibana) or the "Elastic Stack".
Elasticsearch isn't just for search anymore - it has powerful aggregation capabilities for structured data. We'll bucket and analyze data using Elasticsearch, and visualize it using the Elastic Stack's web UI, Kibana.
You'll learn how to manage operations on your Elastic Stack, using X-Pack to monitor your cluster's health, and how to perform operational tasks like scaling up your cluster, and doing rolling restarts. We'll also spin up Elasticsearch clusters in the cloud using Amazon Elasticsearch Service and the Elastic Cloud.
Elasticsearch is positioning itself to be a much faster alternative to Hadoop, Spark, and Flink for many common data analysis requirements. It's an important tool to understand, and it's easy to use! Dive in with me and I'll show you what it's all about.Who this course is for:
  • Any technologist who wants to add Elasticsearch to their toolchest for searching and analyzing big data sets.
Read More All Levels All Levels product length iconTime: 14.3h

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Instructor Details

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Sundog Education's mission is to make highly valuable career skills in big data, data science, and machine learning accessible to everyone in the world. Our consortium of expert instructors shares our knowledge in these emerging fields with you, at prices anyone can afford.
Sundog Education is led by Frank Kane and owned by Frank's company, Sundog Software LLC. Frank spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. Frank holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology, and teaching others about big data analysis.
Due to our volume of students we are unable to respond to private messages; please post your questions within the Q&A of your course. Thanks for understanding.Frank spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. Frank holds 17 issued patents in the fields of distributed computing, data mining

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Reviews

4.4

6,758 ratings on Udemy

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By Ma Wen

Lack of overviews and general explanation on the API to help people understanding elasticsearch. Too many details.

By Kees van der Burg

Excellent course. Very practical and informative.

By Glen Saldanha

The logstash CSV file wasn't explained in depth. What does grok mean?

By Kariato Davey

I'm not in DEVOPS, rather a data guy, so the ability to query and create indexes was what i needed. This course worked, it was practical and allowed me to pivot in ElasticSearch_DSL(not covered) after prototyping a few queries in CURL. Loved that the first thing the class did was to install ElasdticSearch so I could practice.

By Guilherme Londres

Great intro course! Provide's what you need to follow in the subject.

By Cody James Reed

Frank helped solidify the core foundation and principles that make up Elasticsearch and the "Elastic-Stack." This course satisfies any initial questions that you may have about Elasticsearch and its implementation. If you're interested in AWS and Elasticsearch, I'd also highly recommend Frank and Stephane Maarek's AWS Certified Big Data https://www.udemy.com/share/100Y5kBUoadllQQn4=/

By Lorenço Gonzaga

Great course!! Learning to run Elastic in the cloud.

By 이주한

It was good lecture, but I have expected deeper explanation. It’s kind of superficial

By Rajarshi Roy

Fantastic.. Execution steps are clearly mentioned.

By Marcus Vinícius

This is not my first course from Frank Kane and what I can say is that he always deliver it! One more time a great course!

By J Scott Stanlick

The instructor is clearly knowledgeable, however, I think too much time is spent typing Curl and JSON statements. I believe using something like POSTman would have been a little less clumsy

By Kevin Burrowes

I get the curl shows the low-level hacker approach. But you should really be doing most of these commands in Kibana and not on the command line.

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Elasticsearch 9 and the Elastic Stack: In Depth and Hands On
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  • Video Duration: icon 14.3h
  • Price: $89.99
  • Provider: icon Udemy
  • Updated: icon July 2026
  • Level: All Levels All Levels
  • Language: icon English
  • Certificate: icon Yes
  • Lectures:118 in 10 sections
  • Students:53,700
  • Subtitles:12 languages
  • Udemy badge:Bestseller
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