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How To - Elasticsearch Labs

How To

December 24, 2024

How to ingest data to Elasticsearch through Kafka

A step-by-step guide to integrating Apache Kafka with Elasticsearch for efficient data ingestion, indexing, and visualization using Python, Docker Compose, and Kafka Connect.

How to ingest data to Elasticsearch through Kafka
Ensuring business rules work seamlessly with semantic search

December 19, 2024

Ensuring business rules work seamlessly with semantic search

Harness the power of query rules combined with semantic search and rerankers.

Semantic search using the Open Crawler and Semantic Text

December 17, 2024

Semantic search using the Open Crawler and Semantic Text

Learn how to use the Open Crawler in combination with Semantic Text to easily crawl web sites and make them semantically searchable.

How to migrate your Ruby app from OpenSearch to Elasticsearch

December 13, 2024

How to migrate your Ruby app from OpenSearch to Elasticsearch

A guide to migrate a Ruby codebase from the OpenSearch client to the Elasticsearch client.

Live log and prosper: Elasticsearch newly specialized logsdb index mode

December 12, 2024

Live log and prosper: Elasticsearch newly specialized logsdb index mode

Elasticsearch’s latest innovation in log management cuts the storage footprint of log data by up to 65%, enabling observability and security teams to expand visibility without exceeding their budget while keeping all data accessible and searchable.

Adding filter capabilities to Vega Sankey visualizations in Kibana

December 11, 2024

Adding filter capabilities to Vega Sankey visualizations in Kibana

Interested in adding interactive filters to your Vega visualizations in Kibana? Discover how to leverage the `kibanaAddFilter` function to create a dynamic and responsive Sankey visualization with ease.

How to use Elasticsearch Vector Store Connector for Microsoft Semantic Kernel for AI Agent development

December 6, 2024

How to use Elasticsearch Vector Store Connector for Microsoft Semantic Kernel for AI Agent development

Microsoft Semantic Kernel is a lightweight, open-source development kit that lets you easily build AI agents and integrate the latest AI models into your C#, Python, or Java codebase. With the release of Semantic Kernel Elasticsearch Vector Store Connector, developers using Semantic Kernel for building AI agents can now plugin Elasticsearch as a scalable enterprise-grade vector store while continuing to use Semantic Kernel abstractions.

Using Elastic and Apple's OpenELM models for RAG systems

November 28, 2024

Using Elastic and Apple's OpenELM models for RAG systems

How to deploy and test the new Apple Models and build a RAG system using Elastic.

Late chunking in Elasticsearch with Jina Embeddings v2

November 22, 2024

Late chunking in Elasticsearch with Jina Embeddings v2

Using the Jina Embeddings v2 model in Elasticsearch and exploring the pros and cons of long context embeddings models.

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