Blogs
Using Eland on Elasticsearch Serverless
Learn how to use Eland on Elasticsearch Serverless
Testing your Java code with mocks and real Elasticsearch
Learn how to write your automated tests for Elasticsearch, using mocks and Testcontainers
How to ingest data from AWS S3 into Elastic Cloud - Part 1 : Elastic Serverless Forwarder
Learn about different ways you can ingest data from AWS S3 into Elastic Cloud
Automating traditional search with LLMs
Learn how to use LLMs to write Elastic Query DSL and query structured data with filters
Elasticsearch open inference API adds support for Google AI Studio
Elasticsearch open inference API adds support for Google AI Studio
Vertex AI integration with Elasticsearch open inference API brings reranking to your RAG applications
Google Cloud customers can use Vertex AI embeddings and reranking models with Elasticsearch and take advantage of Vertex AI’s fully-managed, unified AI development platform for building generative AI apps.
Quickly create RAG apps with Vertex AI Gemini models and Elasticsearch playground
Quickly create RAG apps with Vertex AI Gemini models and Elasticsearch playground
Adding AI summaries to your site with Elastic
How to add an AI summary box along with the search results to enrich your search experience.
Navigating an Elastic vector database
An overview of operating a modern Elastic vector database with practical code samples.
Introducing LangChain4j to simplify LLM integration into Java applications
LangChain4j (LangChain for Java) is a powerful toolset to build your RAG application in plain Java.