Working in the search technology space in the early 2010s, it was impossible to miss the meteoric rise of Elasticsearch.
At the time, most search engines were closed-source and setting them up was a tedious process involving hours of editing configuration files. Elasticsearch changed all that. It was free, open source, and getting started was as simple as unzipping a file, running an executable, and throwing some data at it. The ease of getting started with Elasticsearch was nothing short of magical.
In 2012, the team behind Elasticsearch founded a company, Elastic. I remember thinking that if I ever got the chance to work for them, I’d jump right on it. That opportunity presented itself a few years later. In 2016, I joined Elastic as a trainer and technical writer. That’s when I truly fell in love with Elasticsearch. Its ease of use and elegant API made it a powerful Swiss army knife for data.
Fifteen years since its first release, Elasticsearch is more relevant than ever. Beyond search, it has evolved into a flexible data platform, with applications in areas like DevSecOps. More recently, with the advent of AI, Elasticsearch has become an excellent platform for retrieval-augmented generation and semantic search.
The breadth and depth of Elasticsearch can be overwhelming for beginners. In the early years of Elasticsearch, a great book that would help you get started was Elasticsearch: The Definitive Guide. However, ten years after its publishing date, it has become outdated. An up-to-date resource to help you get started with Elasticsearch does currently not exist, which got me thinking: with nearly a decade of experience teaching Elasticsearch, maybe I should create one.
Join me here at es24h.com, as I develop a modern guide that helps you get up and running with Elasticsearch in 24 hours. From running Elasticsearch for the first time, to data ingestion and writing queries, and even advanced topics like scripting and working with large language models.
Published: February 25, 2025 by Abdon