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

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Sundog Education by Frank Kane,Frank Kane,Sundog Education Team,Coralogix Ltd.

15:11:48

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1 - Installing and Understanding Elasticsearch

1 - Udemy Getting the Most From This Course.mp4

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2 - 14737304.mp4

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3 - Installing Elasticsearch Step by Step.mp4

20:48

4 - Elasticsearch Overview.mp4

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5 - 14728396.mp4

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6 - Elasticsearch Basics Logical Concepts.mp4

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7 - 14728406.mp4

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8 - 14728692.mp4

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9 - Whats New in Elasticsearch.mp4

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10 - 14728708.mp4

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11 - 14728744.mp4

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2 - Mapping and Indexing Data

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14 - Connecting to your Cluster.mp4

09:04

15 - Note alternate download location for the MovieLens data set.html

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17 - 14728774.mp4

08:32

18 - A note on entering CURL commands.html

19 - Import a Single Movie via JSON REST.mp4

10:10

20 - Insert Many Movies at Once with the Bulk API.mp4

05:30

21 - Updating Data in Elasticsearch.mp4

06:14

22 - Deleting Data in Elasticsearch.mp4

02:18

23 - Exercise Insert Update and Delete a Movie.mp4

04:18

24 - Dealing with Concurrency.mp4

10:25

25 - Using Analyzers and Tokenizers.mp4

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26 - 14728834.mp4

05:29

27 - Data Modeling and Parent Child Relationships Part.mp4

07:03

28 - Flattened Datatype.mp4

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29 - Dealing with Mapping Exceptions.mp4

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30 - 14737316.mp4

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3 - Searching with Elasticsearch

31 - 14737318.mp4

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32 - Query Lite interface.mp4

08:10

33 - JSON Search In Depth.mp4

10:19

34 - Phrase Matching.mp4

06:27

35 - Exercise Querying in Different Ways.mp4

04:31

36 - Pagination.mp4

06:23

37 - Sorting.mp4

08:00

38 - More with Filters.mp4

03:39

39 - Exercise Using Filters.mp4

02:45

40 - Fuzzy Queries.mp4

06:11

41 - Partial Matching.mp4

05:35

42 - Query time Search As You Type.mp4

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43 - N Grams Part.mp4

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44 - N Grams Part.mp4

08:06

45 - Search as you Type Field Type.mp4

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4 - Importing Data into your Index Big or Small

47 - 14737322.mp4

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48 - Importing Data with a Script.mp4

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49 - Importing with Client Libraries.mp4

08:44

50 - Exercise Importing with a Script.mp4

04:49

51 - Introducing Logstash.mp4

04:54

52 - Installing Logstash.mp4

08:21

53 - Running Logstash.mp4

05:16

54 - Logstash and MySQL Part.mp4

08:27

55 - Logstash and MySQL Part.mp4

07:52

56 - Importing CSV Data with Logstash.mp4

14:13

57 - Importing JSON Data with Logstash.mp4

20:35

58 - Logstash and S.mp4

08:20

59 - Parsing and Filtering Logstash with Grok.mp4

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60 - Logstash Grok Examples for Common Log Formats.mp4

34:18

61 - Logstash Input Plugins Part Heartbeat.mp4

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62 - Logstash Input Plugins Part Generator Input and Dead Letter Queue.mp4

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63 - Logstash Input Plugins Part HTTP Poller.mp4

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64 - 21364438.mp4

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65 - Syslog with Logstash Deep Dive.mp4

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66 - Elasticsearch and Kafka Part.mp4

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67 - 14729018.mp4

06:03

68 - Elasticsearch and Apache Spark Part.mp4

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69 - Elasticsearch and Apache Spark Part.mp4

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70 - Exercise Importing Data with Spark.mp4

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71 - 14737324.mp4

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5 - Aggregation

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73 - Aggregations Buckets and Metrics.mp4

10:19

74 - Histograms.mp4

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75 - Time Series.mp4

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76 - Exercise Generating Histogram Data.mp4

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77 - Nested Aggregations Part.mp4

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78 - Nested Aggregations Part.mp4

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6 - Using Kibana

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81 - Installing Kibana.mp4

05:28

82 - Playing with Kibana.mp4

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83 - Exercise Exploring Data with Kibana.mp4

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84 - Kibana Lens.mp4

16:14

85 - Kibana Management.mp4

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86 - Elasticsearch SQL.mp4

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87 - Using Kibana Canvas.mp4

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88 - Elasticsearch and Apache Hadoop.mp4

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89 - 14737352.mp4

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7 - Analyzing Log Data with the Elastic Stack

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91 - Data Frame Transforms.mp4

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92 - 14729120.mp4

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93 - 14729124.mp4

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94 - Installing FileBeat.mp4

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95 - Analyzing Logs with Kibana Dashboards.mp4

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96 - Exercise Log analysis with Kibana.mp4

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8 - Elasticsearch Operations

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99 - 14730538.mp4

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100 - Adding Indices as a Scaling Strategy.mp4

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101 - 14729158.mp4

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102 - Index Lifecycle Management.mp4

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103 - 14729162.mp4

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104 - 14729172.mp4

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105 - 14729178.mp4

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106 - Troubleshooting Common Issues.mp4

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107 - Failover in Action Part.mp4

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108 - Index Design Changes Grouping Splitting and Shrinking Indices.mp4

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109 - 14729942.mp4

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110 - Snapshot Lifecycle Management.mp4

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111 - Rolling Restarts.mp4

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112 - Uptime Monitoring with Heartbeat.mp4

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113 - 14737404.mp4

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9 - Elasticsearch in the Cloud

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115 - Amazon Opensearch Service Part.mp4

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116 - Amazon Opensearch Service Part.mp4

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117 - The Elastic Cloud.mp4

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118 - 14737418.mp4

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10 - You Made It

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120 - Bonus Lecture More Courses to Explore.html

Description

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

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

Who is this for?

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

What You Need to Know?

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

More details

Description
Elasticsearch andÂ 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! Itâ€™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 seenâ€” 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.
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, which allows you to glean new insights from your indexed data. We'll bucket and analyze data using Elasticsearch, and visualize it using the Elastic Stack's web UI, Kibana and Kibana Lens.
You'll learn how to manage operations on your Elastic Stack, monitoring 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 Opensearch 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.Â 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 tasked with fast, scalable searching and analysis of big data sets.

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Elasticsearch

Sundog Education by Frank Kane

Instructor's Courses

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.

Frank Kane

Instructor's Courses

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, I am unable to respond to private messages; please post your questions within the Q&A of your course. Thanks for understanding.

Sundog Education Team

Instructor's Courses

Our mission is to make highly valuable skills in machine learning, big data, AI, and data science accessible at prices anyone in the world can afford. Our current online courses have reached over 500,000 students worldwide. Sundog Education CEO, Frank Kane, 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.

Coralogix Ltd.

Instructor's Courses

Coralogix provides an ML-supported logging platform that accelerates the delivery pipeline for cloud companies performing CI/CD. Beyond searching, visualizing and creating alerts, Coralogix detects anomalies in your data and provides automatic version benchmarks. Simplify your ELK stack and Grafana workflows with our 100% managed, scaled and secured platform and never get lost with 24/7 instant human reply.

Udemy

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