ElasticSearch as you have never known it before – EXCLUSIVE CONTENT


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Here I want to present an introduction to my on-line course: “Elasticsearch as you have never known it before”. At that course I am sharing my production experience with using ElasticSearch for building advanced search systems and recommendation modules. I am also providing real practice examples with using Java, Python and PHP programming languages. You may view the whole course at udemy using next link with discount: link to udemy

The course is built in such a way it would be useful both: for complete beginners and for people who are working with ElasticSearch but would like to extend their practice knowledge. It would be especially useful for those who are going to build some recommendation systems or advanced search mechanisms in the near future. The course consists of 5 modules. First module is aimed for beginners and can be skipped by people who are already working with ElasticSearch. Here I will tell you about basics:

  • how to install and configure the environment using Docker
  • how data at ElasticSearch are organized
  • why mapping is so important and what all that mess around tokenizers and analyzers means

In the second section I will show how to build an advanced search system step by step on a real example of a simplified booking.com version. We will touch the topics about ES geopower here.

Next course section is devoted to the recommendation module. Here we will speak about recommendation systems in general – about pros and cons of today’s methods. And again together we will build a real system using ElasticSearch. We will create a recommendation mechanism for virtual example of cleaning houses’ marketplace. 

In the fourth section I will show real examples using PHP Symfony, Python Flask and Java Spring Boot frameworks for integration with Elasticsearch 7 and Elasticsearch 8 versions. And again we will create real microservice applying best programming practices and interesting design patterns like builder pattern or filter pattern. I will touch here also the question of debugging the possible problems.

The fifth and the last part is about using ElasticSearch for production. Here I will share with you my knowledge on how to set up a highly available cluster, how to calculate shard size and storage requirements, how to index millions of documents in the most efficient way and even how to preserve zero downtime at reindexing. I As the reader of that blog you are also getting possibility to use coupon for the best possible low price.

P.S. If you are interested at DevOps insides of elasticearch cluster or how to deploy HA elasticsearch at AWS using terraform and ansible – then I recommend my advanced course: ““AWS devops: Elasticsearch at AWS using terraform and ansible.”

About the author


Software engineer with over 18 year’s experience. Everyday stack: PHP, Python, Java, Javascript, Symfony, Flask, Spring, Vue, Docker, AWS Cloud, Machine Learning, Ansible, Terraform, Jenkins, MariaDB, MySQL, Mongo, Redis, ElasticSeach

architecture AWS cluster cyber-security devops devops-basics docker elasticsearch flask geo high availability java machine learning opensearch php programming languages python recommendation systems search systems spring boot symfony