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
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
Requirements
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
Description
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.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. 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.
Overview
Section 1: Installing and Understanding Elasticsearch
Lecture 1 Udemy 101: Getting the Most From This Course
Lecture 2 Section 1 Intro
Lecture 3 Installing Elasticsearch[Step by Step]
Lecture 4 Elasticsearch Overview
Lecture 5 Intro to HTTP and RESTful API's
Lecture 6 Elasticsearch Basics: Logical Concepts
Lecture 7 Term Frequency / Inverse Document Frequency (TF/IDF)
Lecture 8 Using Elasticsearch
Lecture 9 What's New in Elasticsearch 8
Lecture 10 How Elasticsearch Scales
Lecture 11 Quiz: Elasticsearch Concepts and Architecture
Lecture 12 Section 1 Wrapup
Section 2: Mapping and Indexing Data
Lecture 13 Section 2 Intro
Lecture 14 Connecting to your Cluster
Lecture 15 Note: alternate download location for the MovieLens data set
Lecture 16 Introducing the MovieLens Data Set
Lecture 17 Analyzers
Lecture 18 A note on entering CURL commands.
Lecture 19 Import a Single Movie via JSON / REST
Lecture 20 Insert Many Movies at Once with the Bulk API
Lecture 21 Updating Data in Elasticsearch
Lecture 22 Deleting Data in Elasticsearch
Lecture 23[Exercise] Insert, Update and Delete a Movie
Lecture 24 Dealing with Concurrency
Lecture 25 Using Analyzers and Tokenizers
Lecture 26 Data Modeling and Parent/Child Relationships, Part 1
Lecture 27 Data Modeling and Parent/Child Relationships, Part 2
Lecture 28 Flattened Datatype
Lecture 29 Dealing with Mapping Exceptions
Lecture 30 Section 2 Wrapup
Section 3: Searching with Elasticsearch
Lecture 31 Section 3 Intro
Lecture 32 "Query Lite" interface
Lecture 33 JSON Search In-Depth
Lecture 34 Phrase Matching
Lecture 35[Exercise] Querying in Different Ways
Lecture 36 Pagination
Lecture 37 Sorting
Lecture 38 More with Filters
Lecture 39[Exercise] Using Filters
Lecture 40 Fuzzy Queries
Lecture 41 Partial Matching
Lecture 42 Query-time Search As You Type
Lecture 43 N-Grams, Part 1
Lecture 44 N-Grams, Part 2
Lecture 45 "Search as you Type" Field Type
Lecture 46 Section 3 Wrapup
Section 4: Importing Data into your Index - Big or Small
Lecture 47 Section 4 Intro
Lecture 48 Importing Data with a Script
Lecture 49 Importing with Client Libraries
Lecture 50[Exercise] Importing with a Script
Lecture 51 Introducing Logstash
Lecture 52 Installing Logstash
Lecture 53 Running Logstash
Lecture 54 Logstash and MySQL, Part 1
Lecture 55 Logstash and MySQL, Part 2
Lecture 56 Importing CSV Data with Logstash
Lecture 57 Importing JSON Data with Logstash
Lecture 58 Logstash and S3
Lecture 59 Parsing and Filtering Logstash with Grok
Lecture 60 Logstash Grok Examples for Common Log Formats
Lecture 61 Logstash Input Plugins, Part 1: Heartbeat
Lecture 62 Logstash Input Plugins, Part 2: Generator Input and Dead Letter Queue
Lecture 63 Logstash Input Plugins, Part 3: HTTP Poller
Lecture 64 Logstash Input Plugins, Part 4: Twitter
Lecture 65 Syslog with Logstash Deep Dive
Lecture 66 Elasticsearch and Kafka, Part 1
Lecture 67 Elasticsearch and Kafka, Part 2
Lecture 68 Elasticsearch and Apache Spark, Part 1
Lecture 69 Elasticsearch and Apache Spark, Part 2
Lecture 70[Exercise] Importing Data with Spark
Lecture 71 Section 4 Wrapup
Section 5: Aggregation
Lecture 72 Section 5 Intro
Lecture 73 Aggregations, Buckets, and Metrics
Lecture 74 Histograms
Lecture 75 Time Series
Lecture 76[Exercise] Generating Histogram Data
Lecture 77 Nested Aggregations, Part 1
Lecture 78 Nested Aggregations, Part 2
Lecture 79 Section 5 Wrapup
Section 6: Using Kibana
Lecture 80 Section 6 Intro
Lecture 81 Installing Kibana
Lecture 82 Playing with Kibana
Lecture 83[Exercise] Exploring Data with Kibana
Lecture 84 Kibana Lens
Lecture 85 Kibana Management
Lecture 86 Elasticsearch SQL
Lecture 87 Using Kibana Canvas
Lecture 88 Elasticsearch and Apache Hadoop
Lecture 89 Section 6 Wrapup
Section 7: Analyzing Log Data with the Elastic Stack
Lecture 90 Section 7 Intro
Lecture 91 Data Frame Transforms
Lecture 92 FileBeat and the Elastic Stack Architecture
Lecture 93 X-Pack Security
Lecture 94 Installing FileBeat
Lecture 95 Analyzing Logs with Kibana Dashboards
Lecture 96[Exercise] Log analysis with Kibana
Lecture 97 Section 7 Wrapup
Section 8: Elasticsearch Operations
Lecture 98 Section 8 Intro
Lecture 99 Choosing the Right Number of Shards
Lecture 100 Adding Indices as a Scaling Strategy
Lecture 101 Index Alias Rotation
Lecture 102 Index Lifecycle Management
Lecture 103 Choosing your Cluster's Hardware
Lecture 104 Heap Sizing
Lecture 105 Monitoring
Lecture 106 Troubleshooting Common Issues
Lecture 107 Failover in Action, Part 1
Lecture 108 Index Design Changes (Grouping, Splitting, and Shrinking Indices)
Lecture 109 Snapshots
Lecture 110 Snapshot Lifecycle Management
Lecture 111 Rolling Restarts
Lecture 112 Uptime Monitoring with Heartbeat
Lecture 113 Section 8 Wrapup
Section 9: Elasticsearch in the Cloud
Lecture 114 Section 9 Intro
Lecture 115 Amazon Opensearch Service, Part 1
Lecture 116 Amazon Opensearch Service, Part 2
Lecture 117 The Elastic Cloud
Lecture 118 Section 9 Wrapup
Section 10: You Made It!
Lecture 119 Wrapping Up
Lecture 120 Bonus Lecture: More Courses to Explore!
Any technologist tasked with fast, scalable searching and analysis of big data sets.

Homepage

https://www.udemy.com/course/elasticsearch-7-and-elastic-stack/