Category: Amazon OpenSearch Service

This post explains the internals of hybrid search and how to build a hybrid search solution using OpenSearch Service. We experiment with sample queries to explore and compare lexical, semantic, and hybrid search. All the code used in this post is publicly available in the GitHub repository.

2023 was been a busy year for Amazon OpenSearch Service! Learn more about the releases that OpenSearch Service launched in the first half of 2023. In the second half of 2023, OpenSearch Service added the support of two new OpenSearch versions: 2.9 and 2.11 These two versions introduce new features in the search space, machine […]

For building any generative AI application, enriching the large language models (LLMs) with new data is imperative. This is where the Retrieval Augmented Generation (RAG) technique comes in. RAG is a machine learning (ML) architecture that uses external documents (like Wikipedia) to augment its knowledge and achieve state-of-the-art results on knowledge-intensive tasks. For ingesting these […]

Unsupervised machine learning analytics has emerged as a powerful tool for anomaly detection in today’s data-rich landscape, especially with the growing volume of machine-generated data. In-stream anomaly detection offers real-time insights into data anomalies, enabling proactive response. Amazon OpenSearch Serverless focuses on delivering seamless scalability and management of search workloads; Amazon OpenSearch Ingestion complements this […]

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, […]

Today, we are launching Terraform support for Amazon OpenSearch Ingestion. Terraform is an infrastructure as code (IaC) tool that helps you build, deploy, and manage cloud resources efficiently. OpenSearch Ingestion is a fully managed, serverless data collector that delivers real-time log, metric, and trace data to Amazon OpenSearch Service domains and Amazon OpenSearch Serverless collections. […]

Amazon OpenSearch Serverless is an on-demand auto scaling configuration for Amazon OpenSearch Service. Since its release, the interest for OpenSearch Serverless had been steadily growing. Customers prefer to let the service manage its capacity automatically rather than having to manually provision capacity. Until now, customers have had to rely on using custom code or third-party […]

In this post, we explore the process of integrating Amazon Keyspaces and Amazon OpenSearch Service using AWS Lambda and Amazon OpenSearch Ingestion to enable advanced search capabilities. The content includes a reference architecture, a step-by-step guide on infrastructure setup, sample code for implementing the solution within a use case, and an AWS Cloud Development Kit (AWS CDK) application for deployment.

Amazon OpenSearch Service is a fully managed search and analytics service powered by the Apache Lucene search library that can be operated within a virtual private cloud (VPC). A VPC is a virtual network that’s dedicated to your AWS account. It’s logically isolated from other virtual networks in the AWS Cloud. Placing an OpenSearch Service […]

Amazon OpenSearch Service offers multiple domain configuration settings to meet your workload-specific requirements. As part of standard service operations, you may be required to update these configuration settings on a regular basis. Recently, Amazon OpenSearch Service launched visibility improvements that allow you to track configuration changes more effectively. We’ve introduced granular and more descriptive configuration […]