Learn Elasticsearch from scratch and lay the foundation for learning the ELK stack (Elasticsearch, Logstash & Kibana).

With this course, you will learn:

How to build a powerful search engine with Elasticsearch

The theory of Elasticsearch and how it works under-the-hood

Write complex search queries

To be proficient with the concepts and terminology of Elasticsearch

The course is a combination of theory and learning by doing. Before giving examples of how to perform certain queries, you will have been equipped with the necessary theory in advance. This ensures that you not only know how to perform powerful searches with Elasticsearch, but that you also understand the relevant theory; you will get a deep understanding of how Elasticsearch works under the hood.

Learn how to build a search engine and break into big data by mastering Elasticsearch 6, Kibana and Logstash (ELK stack)

With this course, you will learn how to:

Build an Elasticsearch 6 cluster from scratch

Perform various searches using the query DSL

Perform powerful realtime analytics using the Aggregations DSL

Combine Filters, Queries and Aggregations and understand document relevancy and searching

This course is designed to be practical and easy to follow by repeating key concepts with step by step instructions and best practices for building a search Engine from scratch.

Search, analyze, and visualize big data on a cluster with Elasticsearch, Logstash, Beats, Kibana, and more.

In this course, you will learn how to:

Install and configure Elasticsearch 6 on a cluster

Create search indices and mappings

Search full-text and structured data in several different ways

Import data into Elasticsearch using several different 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

Every lesson in this course has hands-on examples where you’ll practice each skill using a virtual machine running Elasticsearch on your own PC.

With this course, 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. You’ll also spin up Elasticsearch clusters in the cloud using Amazon Elasticsearch Service and the Elastic Cloud.

Learn software skills with rising demand. ElasticSearch is a core component of ELK stack and an excellent search server

With this course, you will:

Understand the features and utility of ElasticSearch

Understand the basic concepts about Big Data

Install, configure and administer ElasticSearch cluster

In this course, you will focus on one enterprise search engine- The ElasticSearch which is one of the core components of the ELK stack. You will look at the overview and explore the technology that goes into this tool.

This course aims to provide you enough knowledge about ELK and ElasticSearch so that you can run and operate your own search cluster using these components together.

Learn Elasticsearch from scratch with this hands-on course and become an Elasticsearch Jedi.

With this course, you will:

Do create, read, update and delete operations on Elasticsearch

Have a good understanding of searching and sorting documents in Elasticsearch

Know how mapping and analyzers work and learn how to use them effectively

Become an Elasticsearch jedi

You will begin learning Elasticsearch with a gentle introduction where you can setup your environment and launch your node of Elasticsearch for the first time. After that, you will dive into Create/Read/Update/Delete operations and show you how to do them in bulk. For each operation you will do several examples so you can learn by doing.

Later, you will learn about mappings and analyzers in a whole chapter dedicated to them which are important subjects if you want to master Elasticsearch. One of the most important chapters is Search in Depth where you will master the essential part of searching documents in Elasticsearch. Your last chapter will be Sorting where you will look into how you can sort our documents and how relevancy in Elasticsearch works.

Process events with Logstash, which is a key part of the ELK stack (Elasticsearch, Logstash, Kibana).

Understand the fundamental concepts of Logstash

Build pipelines that process and manipulates thousands of events

Send data to Logstash from numerous sources and to several destinations

Build a fully functional pipeline that handles Apache web server logs

This course will start from the very basics and gradually transition into more advanced topics. The course is designed so that you can follow along the whole time step by step, and you can find all of the configuration files within a GitHub repository.

The course covers topics such as handling Apache web server logs (both access and error logs), data enrichment, sending data to Elasticsearch, visualizing data with Kibana, along with covering a number of popular use cases that you are likely to come across.

Build a fully featured and scalable search UI with Elasticsearch.

With this course, you will learn how to:

Ingest real data into your index and create a working Elasticsearch cluster

Categorize different types of data automatically with Elasticsearch and manage them effectively

Work with a variety of queries and learn how and when to use them correctly

Implement exciting features that help you search and highlight data

Build custom search filters that help you with advanced data search

Get to grips with the best practices for separating out the structure of an AngularJS application into its various components

Add a bit more to your search server by applying relevancy tuning and addressing security concerns

Starting with an introduction to Elasticsearch and client-side applications, you’ll then move on to learn how Elasticsearch automatically classifies field types, and what to do if they need to be overridden. You will also cover many of the query types that Elasticsearch provides to return results for our AngularJS application.

Once you have some basic results, you will add filters (called aggregations in Elasticsearch) to make it easy for users to narrow down the results to a specific topic. Then you will cover how to implement autocomplete and highlighting, and ultimately wrap up with an overview of deployment and security.

Learn software skills with rising demand. LogStash is a core component of ELK stack and a data ingestion tool.

This course aims to provide you enough knowledge about ELK and LogStash so that you can run and operate your own data ingestion pipelines cluster using these components together. But specifically:

You will get familiar with the features and benefits offered by LogStash

This course provides detailed demos of installation and configuration of LogStash

In this course, you will focus on one such enterprise data collection and collation tool- the LogStash which is one of the core components of the ELK stack. You will look at the overview and explore the technology that goes behind this tool.

Learn software skills with rising demand. Kibana is a core component of ELK stack and a data visualization tool

In this course, you will focus on this enterprise data visualization tool — Kibana which is one of the core components of the ELK stack. You will look at the overview and explore the technology that goes behind this tool.

This course aims to provide you enough knowledge about ELK and Kibana so that you can build useful visualizations based on your data using these components together. But specifically:

You will get familiar with the features and benefits offered by Kibana.

This course provides detailed demos of installation and configuration of Kibana; it will equip you well for future use of this technology.

This course will introduce users to Elasticsearch, how it works, and how to use it with .NET projects.

This course will introduce users to Elasticsearch, do a walkthrough of a basic installation, and teach the user how to index data and query it efficiently.

The course will then go on to teach more advanced querying techniques, filters, and analytics. Finally, the course will show users how to integrate Elasticsearch with their .NET projects using a basic console application example.

Elasticsearch is a popular enterprise search engine, which allows you to build powerful search capability.

This course focuses on understanding search components and algorithms from first principles, and applying these in practice using REST APIs.

In this course, you’ll be introduced to Elasticsearch by learning the basic building blocks of search algorithms, and how the basic data structure at the heart of every search engine works.

First, you’ll cover how to install and set up a single node server, index and update documents whose contents you want to search, perform a variety of search queries on these document contents, and run analysis to extract insights from your data.

Next, you’ll explore the TF/IDF algorithm for search ranking and relevance, and the important factors which determine how a document is scored for every search term.

Finally, you’ll learn how Elasticsearch handles a variety of searches, such as full-text queries, term queries, compound queries, and filters. You’ll also run analytical queries on interesting data subsets specified by search terms.