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

What's inside

Learning objectives

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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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
Show more
Show less

Syllabus

We'll cover the main components of the Elastic Stack and take a look at Elasticsearch's architecture and main concepts. And, we'll actually install Elasticsearch on your own PC and see if it works!

Udemy 101: Getting the Most From This Course

Important note

Section 1 Intro

We'll talk about why Elasticsearch is important and what you can expect from this course. Then, we'll install a virtual Ubuntu machine right on your own desktop PC, install Elasticsearch on it, and search the complete works of William Shakespeare!

Let's look at the components of the Elastic Stack from a 30,000-foot level, and see how they all fit together.

Elasticsearch exposes a RESTful API, and we communicate with Elasticsearch using nothing but standard HTTP requests and responses. Let's cover the basics of how that works.

Elasticsearch Basics: Logical Concepts

Term Frequency / Inverse Document Frequency (TF/IDF)

Using Elasticsearch

What's New in Elasticsearch 8

How Elasticsearch Scales

Quiz: Elasticsearch Concepts and Architecture

Section 1 Wrapup

Create new search indices for structured and unstructured data, insert / update / delete documents, handle concurrency issues, and model relational data.

Section 2 Intro

Connecting to your Cluster

Note: alternate download location for the MovieLens data set

Introducing the MovieLens Data Set

Analyzers

A note on entering CURL commands.

Import a Single Movie via JSON / REST

Insert Many Movies at Once with the Bulk API

Updating Data in Elasticsearch

Deleting Data in Elasticsearch

[Exercise] Insert, Update and Delete a Movie

Dealing with Concurrency

Using Analyzers and Tokenizers

Data Modeling and Parent/Child Relationships, Part 1

Data Modeling and Parent/Child Relationships, Part 2

Flattened Datatype

Dealing with Mapping Exceptions

Section 2 Wrapup

Issue search queries for textual and structured data on Elasticsearch in different ways. Conduct full-text, fuzzy, partial, and phrase searches. Paginate and sort your results. Use filters.

Section 3 Intro

"Query Lite" interface

JSON Search In-Depth

Phrase Matching

[Exercise] Querying in Different Ways

Pagination

Sorting

More with Filters

[Exercise] Using Filters

Fuzzy Queries

Partial Matching

Query-time Search As You Type

N-Grams, Part 1

N-Grams, Part 2

"Search as you Type" Field Type

Section 3 Wrapup

Import existing data into Elasticsearch from a variety of sources: JSON requests, script API's, Logstash, JDBC, Amazon S3, Kafka, and Spark.

Section 4 Intro

Importing Data with a Script

Importing with Client Libraries

[Exercise] Importing with a Script

Introducing Logstash

Installing Logstash

Running Logstash

Logstash and MySQL, Part 1

Logstash and MySQL, Part 2

Importing CSV Data with Logstash

Importing JSON Data with Logstash

Logstash and S3

Parsing and Filtering Logstash with Grok

Workaround if the Grok Debugger app in the next lecture is down...

Hands-on examples of parsing logs with Logstash into Elasticsearch using Grok patterns. Includes Apache, NGINX, MongoDB, AWS ELB, AWS ALB, MySQL slow logs, Elasticsearch logs, Elasticsearch slow logs, IIS, and AWS CloudFront logs.

Logstash Input Plugins, Part 1: Heartbeat

Logstash Input Plugins, Part 2: Generator Input and Dead Letter Queue

Logstash Input Plugins, Part 3: HTTP Poller

Syslog with Logstash Deep Dive

Elasticsearch and Kafka, Part 1

Elasticsearch and Kafka, Part 2

Elasticsearch and Apache Spark, Part 1

Elasticsearch and Apache Spark, Part 2

[Exercise] Importing Data with Spark

Section 4 Wrapup

Use buckets, metrics, and nested aggregations to gain insights into your index's structured data.

Section 5 Intro

Aggregations, Buckets, and Metrics

Histograms

Time Series

[Exercise] Generating Histogram Data

Nested Aggregations, Part 1

Nested Aggregations, Part 2

Section 5 Wrapup

Install and use Kibana to visualize the data in your indices.

Section 6 Intro

Installing Kibana

Playing with Kibana

[Exercise] Exploring Data with Kibana

Kibana Lens

Kibana Management

Elasticsearch SQL

Using Kibana Canvas

Elasticsearch and Apache Hadoop

Section 6 Wrapup

Use FileBeat and Kibana to import and analyze server log data in near-real-time.

Section 7 Intro

Data Frame Transforms

FileBeat and the Elastic Stack Architecture

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Helps operational teams manage large data sets in milliseconds to glean insights that may speed up execution and decision making

Cost effective for learning about data engineering and analytics with a possible career boost

Helps developers become more valuable engineers

May require additional software to meet hardware requirements

Assumes learners have existing background knowledge of data analysis

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Elasticsearch 8 and the Elastic Stack: In Depth and Hands On with these activities:

Review Elasticsearch Basics

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Review the fundamentals of Elasticsearch, such as its architecture, data model, and basic search operations, to enhance comprehension during the course.

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Revisit documentation or tutorials on Elasticsearch concepts.
Complete practice exercises to reinforce understanding of basic search queries.

Read 'Elasticsearch: The Definitive Guide'

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Deepen your knowledge of Elasticsearch by reading this comprehensive guide. It covers advanced topics such as cluster management, indexing strategies, and performance tuning, providing a valuable resource for solidifying your understanding.

View Elasticsearch: The Definitive Guide: A... on Amazon

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Read specific chapters or sections relevant to the course topics.
Take notes, highlight important passages, and engage with the material actively.

Show all two activities

Career center

Learners who complete Elasticsearch 8 and the Elastic Stack: In Depth and Hands On will develop knowledge and skills that may be useful to these careers:

Elasticsearch Developer

An Elasticsearch Developer is responsible for developing and maintaining Elasticsearch applications. They use their knowledge of Elasticsearch's APIs and features to build scalable and efficient search and analytics applications. This course provides a deep dive into Elasticsearch, covering topics such as data ingestion, indexing, querying, aggregation, and performance tuning. It also covers advanced topics such as security, replication, and disaster recovery. These skills are essential for Elasticsearch Developers who want to build and maintain high-performance Elasticsearch applications.

See salaries and explore the career path for Elasticsearch Developer

Data Engineer

A Data Engineer is responsible for designing, building, and maintaining data pipelines and infrastructure. They ensure that data is collected, processed, and stored in a way that meets the needs of the business. This course provides a deep dive into Elasticsearch, a popular data storage and processing engine. It covers topics such as data ingestion, indexing, querying, aggregation, and performance tuning. These skills are essential for Data Engineers who want to use Elasticsearch to build scalable and efficient data pipelines.

See salaries and explore the career path for Data Engineer

Data Analyst

A Data Analyst is responsible for collecting, cleaning, and analyzing data to identify trends and patterns. They use this information to make informed decisions and solve business problems. This course provides a comprehensive overview of Elasticsearch, a powerful data analysis tool. It covers topics such as data import, querying, aggregation, and visualization. These skills are essential for Data Analysts who want to use Elasticsearch to gain insights from data.

See salaries and explore the career path for Data Analyst

Data Scientist

A Data Scientist is responsible for using data to solve business problems. They use a variety of techniques, including machine learning, statistics, and data visualization, to extract insights from data. This course provides a strong foundation in Elasticsearch, a powerful data analysis tool. It covers topics such as data import, querying, aggregation, and visualization. These skills are essential for Data Scientists who want to use Elasticsearch to gain insights from data.

See salaries and explore the career path for Data Scientist

Database Administrator

A Database Administrator is responsible for the installation, configuration, maintenance, and performance of database management systems (DBMS). They ensure that the DBMS is running smoothly and that data is stored and retrieved efficiently. This course provides a strong foundation in Elasticsearch, a popular DBMS, and covers topics such as data modeling, indexing, querying, aggregation, and performance tuning. These skills are essential for Database Administrators.

See salaries and explore the career path for Database Administrator

Software Engineer

A Software Engineer is responsible for developing and maintaining software applications. They use their knowledge of programming languages and software engineering principles to build software that meets the needs of users. This course provides a comprehensive overview of Elasticsearch, a powerful search and analytics engine. It covers topics such as data modeling, indexing, querying, and aggregation. These skills are essential for Software Engineers who want to use Elasticsearch to build and maintain effective software applications.

See salaries and explore the career path for Software Engineer

Information Architect

An Information Architect is responsible for designing and organizing information systems. They ensure that information is easy to find, understand, and use. This course provides a strong foundation in Elasticsearch, a powerful search and analytics engine. It covers topics such as data modeling, indexing, querying, and aggregation. These skills are essential for Information Architects who want to use Elasticsearch to design and implement effective information systems.

See salaries and explore the career path for Information Architect

Machine Learning Engineer

A Machine Learning Engineer is responsible for developing and deploying machine learning models. They use a variety of techniques, including data analysis, model training, and evaluation, to build models that can solve real-world problems. This course provides a strong foundation in Elasticsearch, a powerful data analysis tool. It covers topics such as data import, querying, aggregation, and visualization. These skills are essential for Machine Learning Engineers who want to use Elasticsearch to build and evaluate machine learning models.

See salaries and explore the career path for Machine Learning Engineer

Software Architect

A Software Architect is responsible for designing and implementing software systems. They use their knowledge of software engineering principles and best practices to build systems that are scalable, reliable, and secure. This course provides a deep dive into Elasticsearch, covering topics such as data ingestion, indexing, querying, aggregation, and performance tuning. It also covers advanced topics such as security, replication, and disaster recovery. These skills are essential for Software Architects who want to design and implement high-performance Elasticsearch applications.

See salaries and explore the career path for Software Architect

DevOps Engineer

A DevOps Engineer is responsible for bridging the gap between development and operations teams. They ensure that software is developed, tested, and deployed efficiently and reliably. This course provides a comprehensive overview of Elasticsearch, a powerful tool for log management and monitoring. It covers topics such as data import, querying, aggregation, and visualization. These skills are essential for DevOps Engineers who want to use Elasticsearch to improve the reliability and performance of their software systems.

See salaries and explore the career path for DevOps Engineer

Information Security Analyst

An Information Security Analyst is responsible for protecting an organization's information systems from security threats. They use a variety of techniques, including data analysis and threat detection, to identify and mitigate security risks. This course provides a comprehensive overview of Elasticsearch, a powerful tool for log management and monitoring. It covers topics such as data import, querying, aggregation, and visualization. These skills are essential for Information Security Analysts who want to use Elasticsearch to improve the security of their organization's information systems.

See salaries and explore the career path for Information Security Analyst

Systems Administrator

A Systems Administrator is responsible for managing and maintaining computer systems. They ensure that systems are running smoothly and that data is stored and retrieved efficiently. This course provides a strong foundation in Elasticsearch, a popular DBMS, and covers topics such as data modeling, indexing, querying, aggregation, and performance tuning. These skills are essential for Systems Administrators who want to use Elasticsearch to improve the performance and reliability of their systems.

See salaries and explore the career path for Systems Administrator

Technical Writer

A Technical Writer is responsible for creating and maintaining documentation for software and hardware products. They use their knowledge of technical concepts and writing skills to create clear and concise documentation that helps users understand and use products effectively. This course may be useful for Technical Writers who want to learn more about Elasticsearch, a popular search and analytics engine. It covers topics such as data modeling, indexing, querying, and aggregation. This knowledge can be helpful for Technical Writers who need to document Elasticsearch-based systems.

See salaries and explore the career path for Technical Writer

Web Developer

A Web Developer is responsible for developing and maintaining websites. They use their knowledge of programming languages and web development technologies to create websites that are visually appealing and easy to use. This course may be useful for Web Developers who want to learn more about Elasticsearch, a popular search and analytics engine. It covers topics such as data modeling, indexing, querying, and aggregation. This knowledge can be helpful for Web Developers who need to build websites that use Elasticsearch for search or analytics functionality.

See salaries and explore the career path for Web Developer

User Experience Designer

A User Experience Designer is responsible for designing and evaluating the user experience of software and hardware products. They use their knowledge of human-computer interaction principles and design techniques to create products that are easy to use and enjoyable to use. This course may be useful for User Experience Designers who want to learn more about Elasticsearch, a popular search and analytics engine. It covers topics such as data modeling, indexing, querying, and aggregation. This knowledge can be helpful for User Experience Designers who need to design and evaluate products that use Elasticsearch.

See salaries and explore the career path for User Experience Designer

Elasticsearch 8 and the Elastic Stack

In Depth and Hands On

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