Introducing Serverless Thin Indexing Shards
Elastic Cloud Serverless

Introducing Serverless Thin Indexing Shards

Learn more about Thin Indexing Shards, a new component developed especially for Elasticsearch in our Elastic Cloud Serverless offering.

Tanguy Leroux

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Building multilingual RAG with Elastic and Mistral
IntegrationsHow ToGenerative AIVector Database

Building multilingual RAG with Elastic and Mistral

Building a multilingual RAG application using Elastic and Mixtral 8x22B model

Gustavo Llermaly

Mistral AI embedding models now available via Elasticsearch Open Inference API
IntegrationsHow ToGenerative AIVector Database

Mistral AI embedding models now available via Elasticsearch Open Inference API

Learn more about how to use Mistral embeddings with Elastic built search experiences!

Mark Hoy

How we optimized refresh costs in Elasticsearch Serverless
Elastic Cloud Serverless

How we optimized refresh costs in Elasticsearch Serverless

We explore how serverless Elasticsearch facilitates searches using data stored in a blob store while maintaining the same visibility semantics as stateful Elasticsearch. We discuss the challenges encountered during implementation and share strategies for balancing costs and complexity.

Francisco Fernández Castaño

Henning Andersen

Ingest autoscaling in Elasticsearch
Elastic Cloud Serverless

Ingest autoscaling in Elasticsearch

Learn more about how Elasticsearch autoscales to address ingestion load.

Pooya Salehi

Henning Andersen

Francisco Fernández Castaño

Serverless semantic search with ELSER in Python: Exploring Summer Olympic games history
How To

Serverless semantic search with ELSER in Python: Exploring Summer Olympic games history

This blog shows how to fetch information from an Elasticsearch index, in a natural language expression, using semantic search. We will load previous olympic games data set and then use the ELSER model to perform semantic searches.

Essodjolo Kahanam

Protecting Sensitive and PII information in RAG with Elasticsearch and LlamaIndex
IntegrationsHow ToGenerative AI

Protecting Sensitive and PII information in RAG with Elasticsearch and LlamaIndex

How to protect sensitive and PII data in a RAG application with Elasticsearch and LlamaIndex.

Srikanth Manvi

Building advanced visualizations with Kibana and Vega
How To

Building advanced visualizations with Kibana and Vega

Have you struggled to build the Kibana visualizations you need using Lens and TSDB? Learn how to create complex visualizations using Kibana and Vega.

Carly Richmond

Introducing the sparse vector query: Searching sparse vectors with inference or precomputed query vectors
Vector Database

Introducing the sparse vector query: Searching sparse vectors with inference or precomputed query vectors

Introducing the sparse vector query, powering sparse vector search in the future

Kathleen DeRusso

GenAI for Customer Support — Part 2: Building a Knowledge Library
Inside Elastic

GenAI for Customer Support — Part 2: Building a Knowledge Library

This series gives you an inside look at how we're using generative AI in customer support. Join us as we share our journey in real-time!

Cory Mangini