Elasticsearch 6 and Elastic Stack – In Depth and Hands On!
Elasticsearch 6 and Elastic Stack – In Depth and Hands On!, available at $54.99, has an average rating of 4.45, with 100 lectures, 3 quizzes, based on 44 reviews, and has 343 subscribers.
You will learn about Install and configure Elasticsearch on a cluster Develop an understanding of Elasticsearch dichotomy, Elasticsearch APIs, and how to interact with a cluster via API Dive deeper into Elasticsearch interactions with filers, ranges, matches along with aggregations Probe Elastic Stack and use Kibana, Logstash and filebeats, to develop a pipeline to get data from an external source into Elasticsearch Build an Elasticsearch application Learn how to use Kibana to visualize data and tell data stories in real-time Learn the skills required to instantly search petabytes of data and provide amazing customer interactions Leverage HTTP-based APIs for ElasticSearch insert, query, and configure operations This course is ideal for individuals who are This learning path is for developers, architects, data professionals, and system administrators who want to add Elasticsearch to their toolchest for searching, analyzing, and visualizing data sets. It is particularly useful for This learning path is for developers, architects, data professionals, and system administrators who want to add Elasticsearch to their toolchest for searching, analyzing, and visualizing data sets.
Enroll now: Elasticsearch 6 and Elastic Stack – In Depth and Hands On!
Summary
Title: Elasticsearch 6 and Elastic Stack – In Depth and Hands On!
Price: $54.99
Average Rating: 4.45
Number of Lectures: 100
Number of Quizzes: 3
Number of Published Lectures: 100
Number of Published Quizzes: 3
Number of Curriculum Items: 103
Number of Published Curriculum Objects: 103
Original Price: $199.99
Quality Status: approved
Status: Live
What You Will Learn
- Install and configure Elasticsearch on a cluster
- Develop an understanding of Elasticsearch dichotomy, Elasticsearch APIs, and how to interact with a cluster via API
- Dive deeper into Elasticsearch interactions with filers, ranges, matches along with aggregations
- Probe Elastic Stack and use Kibana, Logstash and filebeats, to develop a pipeline to get data from an external source into Elasticsearch
- Build an Elasticsearch application
- Learn how to use Kibana to visualize data and tell data stories in real-time
- Learn the skills required to instantly search petabytes of data and provide amazing customer interactions
- Leverage HTTP-based APIs for ElasticSearch insert, query, and configure operations
Who Should Attend
- This learning path is for developers, architects, data professionals, and system administrators who want to add Elasticsearch to their toolchest for searching, analyzing, and visualizing data sets.
Target Audiences
- This learning path is for developers, architects, data professionals, and system administrators who want to add Elasticsearch to their toolchest for searching, analyzing, and visualizing data sets.
Elasticsearch 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. If you’re a technologist who wants to add Elasticsearch to their tool chest for searching and analyzing big data sets, then go for this Learning Path.
This comprehensive 3-in-1 course is a hands-on guide to using Elasticsearch in conjunction with Elastic Stack, to search, analyze, and visualize data with Elasticsearch, Logstash, Beats, Kibana, and more. You will gain a firm understanding of all the fundamentals of Elasticsearch 6 to build efficient search and analytics applications using Elasticsearch 6. You will also learn what Elastic stack is all about, and how to use it efficiently to build powerful real-time data processing applications. This course covers each and every concept of ElasticSearch and Elastic Stack with the help of practical examples making it easy for you to understand and implement in your own applications.
This training program includes 3 complete courses, carefully chosen to give you the most comprehensive training possible.
The first course, Learning Elasticsearch 6, begins with explaining you what is Elasticsearch, what is it used for, and why is it important. You will then be introduced to the new features of Elasticsearch 6 and its fundamental components such as indices, documents, nodes and clusters, all which form the dichotomy of Elasticsearch. You will also learn how to add more power to your searches using filters, ranges, and more. Next, you will explore how Elasticsearch can be used with the other components of the Elastic Stack such as LogStash, Kibana, and Beats, to get data into an Elasticsearch cluster. Finally, you will develop a Elasticsearch application.
In the second course, Learning Elastic Stack 6.0, after a quick overview of the newly introduced features in Elastic Stack 6, you’ll learn how to set up the stack by installing the tools, and explore their basic configurations. You will then demonstrate the creation of custom plugins using Kibana. You will also get some useful tips on how to use the Elastic Cloud and deploy the Elastic Stack in production environments.
The third course, Mastering ElasticSearch 6.x and the Elastic Stack, focuses on two major use cases with Elasticsearch. The first use case is on leveraging the powerful full-text search engine ElasticSearch is built on, allowing developers to add blazingly fast search features to applications. The second use case is on leveraging different components of the Elastic Stack to continuously monitor applications, infrastructure, or even customer transactions.
By the end of this Learning Path, you will be well-versed with the concepts of Elasticsearch and Elastic Stack to build complete, open source solutions for storing, managing, analyzing, and visualizing structured and unstructured data.
Meet Your Expert(s):
We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:
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Ethan Anthony is a San Francisco based Data Scientist who specializes in distributed data-centric technologies. He is also the Founder of XResults, where the vision is to harness the power of big data to deliver intuitive customer-facing solutions, largely to non-technical professionals. Ethan is Harvard-educated in the areas of data science and software engineering. He began using Elasticsearch in 2012 and delivered solutions based on the Elastic Stack to a broad range of clientele. Ethan has also consulted globally with firms in a cross-section of industry verticals, from the U.S. to the Far East.
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Pranav Shukla is the founder and CEO of Valens DataLabs, a technologist, husband, and father of two. He is a big data architect and software craftsman who uses JVM-based languages. Pranav has diverse experience of over 14 years in architecting enterprise applications for Fortune 500 companies and startups. His core expertise lies in building JVM-based, scalable, reactive, and data-driven applications using Java/Scala, the Hadoop ecosystem, Apache Spark, and NoSQL databases. He is a big data engineering, analytics, and machine learning enthusiast. Pranav founded Valens DataLabs with a vision to help companies leverage data to their competitive advantage. Valens DataLabs specializes in developing next-generation, cloud-based, reactive, and data-intensive applications using big data and web technologies. The company believes in agile practices, lean principles, test-driven and behavior-driven development, continuous integration, and continuous delivery for sustainable software systems.
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Sharath Kumar M N has done his masters in Computer Science at The University of Texas, Dallas, USA. He has been in the IT industry for more than ten years now and is the Elasticsearch Solutions Architect at Oracle. He is an Elastic Stack advocate, and being an avid speaker he has also given several tech talks in conferences such as the Oracle Code Event. Sharath is a certified trainer—Elastic Certified Instructor—one of the few technology experts in the world who has been certified by Elastic Inc to deliver their official from the creators of Elastic training. He is also a data science and machine learning enthusiast. In his free time, he enjoys trekking, listening to music, playing with his lovely pets Guddu and Milo and the geek in him loves exploring his Python skills for stock market analysis.
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Chris Fauerbach is an active technical expert in the area of cybersecurity and the Elastic Stack. As a seasoned software engineer, he’s built multiple commercial products on the Elastic Stack and has a passion for teaching. Chris continues to research new technologies and explore new ways to solve problems. As he has become an expert in his field, he has been focusing primarily on writing and teaching.
Course Curriculum
Chapter 1: Learning ElasticSearch 6
Lecture 1: The Course Overview
Lecture 2: What is Elasticsearch?
Lecture 3: Goals of Elasticsearch
Lecture 4: Installing Elasticsearch
Lecture 5: What is an Index?
Lecture 6: Docs in Elasticsearch
Lecture 7: What is a Cluster?
Lecture 8: Shards and Replicas
Lecture 9: Bulk API
Lecture 10: Introduction to RESTful API
Lecture 11: Searching with RESTful API
Lecture 12: Updating with RESTful API
Lecture 13: Introduction to DSL
Lecture 14: DSL — Context, Relevancy, and Score
Lecture 15: Exists Query
Lecture 16: Introduction to Elastic Stack
Lecture 17: Kibana
Lecture 18: Logstash
Lecture 19: X-Pack
Lecture 20: Beats
Lecture 21: Prep for Log Analysis
Lecture 22: Securing Elasticsearch with X-Pack
Lecture 23: Building the Pipeline
Lecture 24: Running the Pipeline
Lecture 25: Term, Range, and Boosting
Lecture 26: Aggregation Based Analytics
Lecture 27: Aggregation Based Analytics (Continued)
Lecture 28: Geo Query by Example
Lecture 29: Sorting in Elasticsearch
Lecture 30: Synonyms in Elasticsearch
Lecture 31: Intro to Machine Learning
Lecture 32: Elasticsearch and Machine Learning
Lecture 33: Machine Learning Walkthrough
Lecture 34: Supplemental — Getting Data
Chapter 2: Learning Elastic Stack 6.0
Lecture 1: The Course Overview
Lecture 2: What is Elasticsearch, and Why Use It?
Lecture 3: Exploring the Components of Elastic Stack
Lecture 4: Downloading and Installing
Lecture 5: Using the Kibana Console UI
Lecture 6: Mappings and Data Types
Lecture 7: CRUD Operations
Lecture 8: Creating Indexes and Taking Control of Mapping
Lecture 9: REST API Overview
Lecture 10: Logstash
Lecture 11: Architecture and Overview of Logstash Plugins
Lecture 12: Exploring Input Plugins
Lecture 13: Output Plugins
Lecture 14: The Basics of Aggregations
Lecture 15: Metric Aggregations
Lecture 16: Bucketing on String and Numeric Data
Lecture 17: Bucketing on Date/Time Data
Lecture 18: Bucketing on Geo-Spatial Data
Lecture 19: Parsing and Enriching Logs Using Logstash
Lecture 20: Beats
Lecture 21: Getting Started with Kibana
Lecture 22: Kibana UI
Lecture 23: Visualize
Lecture 24: Visualizations in Action
Lecture 25: Dashboards
Lecture 26: Timelion and Plugins
Lecture 27: Modeling data in Elasticsearch
Lecture 28: Building the Logstash Data Pipeline
Lecture 29: Visualizing the Data in Kibana
Chapter 3: Mastering ElasticSearch 6.x and the Elastic Stack
Lecture 1: The Course Overview
Lecture 2: Overview of a Final Working Solution – This Is What We're Working Towards
Lecture 3: Install and Configure Elasticsearch
Lecture 4: Install and Configure Kibana
Lecture 5: Enable Monitoring via X-Pack for Elasticsearch and Kibana
Lecture 6: Loading Example Data in Elasticsearch
Lecture 7: How Do We Store and Group Data – Documents
Lecture 8: Specifying Document Attributes – Data Types
Lecture 9: Classifying Similar Documents Types
Lecture 10: Organizing and Grouping Documents Indexes
Lecture 11: Give Me My Data Back – Searches
Lecture 12: Kibana Is Huge – Let’s Take It Apart
Lecture 13: Configuring Groups of Data for Querying – Index Patterns
Lecture 14: Time Range Queries – Slicing and Dicing
Lecture 15: Searches – Refining Queries to Find the Needle in the Haystack
Lecture 16: Saving and Sharing – Let Your Friends Know What You Found
Lecture 17: Logstash – Introduction
Lecture 18: Visualizing Pipelines in Kibana
Lecture 19: Process Documents with Filters
Lecture 20: Get Data into Logstash as a Server
Lecture 21: Working with Beats
Lecture 22: Outputs – Where Else Can Data Go
Lecture 23: Impress Your Boss with Charts and Graphs
Lecture 24: Building a Heads Up Dashboard
Lecture 25: Sharing Dashboards Recap
Lecture 26: Use Kibana to Monitor the Health of Your Elastic Stack
Lecture 27: Security – Provide Authentication and Authorization to Kibana
Lecture 28: Graph – Use the Built in Graph Interface to Pivot Around Data
Lecture 29: Machine Learning Is Hot, See How Elastic Facilitate0073
Lecture 30: Application Perfromance Monitoring – APM
Lecture 31: Application Performance Monitoring – APM (Continued)
Lecture 32: Timelion – Time Series
Instructors
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Packt Publishing
Tech Knowledge in Motion
Rating Distribution
- 1 stars: 2 votes
- 2 stars: 1 votes
- 3 stars: 10 votes
- 4 stars: 18 votes
- 5 stars: 13 votes
Frequently Asked Questions
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