Category: Amazon OpenSearch Service

Amazon OpenSearch Service has long supported both lexical and vector search, since the introduction of its kNN plugin in 2020. With recent developments in generative AI, including AWS’s launch of Amazon Bedrock earlier in 2023, you can now use Amazon Bedrock-hosted models in conjunction with the vector database capabilities of OpenSearch Service, allowing you to implement semantic search, retrieval augmented generation (RAG), recommendation engines, and rich media search based on high-quality vector search. The recent launch of the vector engine for Amazon OpenSearch Serverless makes it even easier to deploy such solutions.

We recently announced new enhancements to Amazon OpenSearch Serverless that can scan and search source data sizes of up to 6 TB. At launch, OpenSearch Serverless supported searching one or more indexes within a collection, with the total combined size of up to 1 TB. With the support for 6 TB source data, you can now scale up your log analytics, machine learning applications, and ecommerce data more effectively. With OpenSearch Serverless, you can enjoy the benefits of these expanded limits without having to worry about sizing, monitoring your usage, or manually scaling an OpenSearch domain.

Modern applications apply security controls across many systems and their subsystems. Keeping all of these systems in sync would be a major undertaking if you tried to implement it separately. Centralized identity management is the way to maintain a single identity provider (IdP) that can authenticate actors and manage and distribute their rights. OpenSearch is […]

This post was co-written by Sheel Saket, Senior Data Science Manager at FIS, and Rupesh Tiwari, Senior Architect at Amazon Web Services. Do you ever find yourself grappling with multiple defect logging mechanisms, scattered project management tools, and fragmented software development platforms? Have you experienced the frustration of lacking a unified view, hindering your ability […]

We are pleased to announce the preview release of the vector engine for Amazon OpenSearch Serverless. The vector engine provides a simple, scalable, and high-performing similarity search capability in Amazon OpenSearch Serverless that makes it easy for you to build modern machine learning (ML) augmented search experiences and generative artificial intelligence (AI) applications without having […]

This is a guest blog post co-written with Zack Rossman from Alcion. Alcion, a security-first, AI-driven backup-as-a-service (BaaS) platform, helps Microsoft 365 administrators quickly and intuitively protect data from cyber threats and accidental data loss. In the event of data loss, Alcion customers need to search metadata for the backed-up items (files, emails, contacts, events, […]

In this post, we show how to build a log ingestion pipeline using the new Amazon OpenSearch Ingestion, a fully managed data collector that delivers real-time log and trace data to Amazon OpenSearch Service domains. OpenSearch Ingestion is powered by the open-source data collector Data Prepper. Data Prepper is part of the open-source OpenSearch project. […]

Amazon OpenSearch Serverless helps you index, analyze, and search your logs and data using OpenSearch APIs and dashboards. The OpenSearch Serverless collection is a group of indexes. API and dashboard clients can access the collections from public networks or one or more VPCs. For VPC access to collections and dashboards, you can create VPC endpoints. […]

Using Amazon OpenSearch Service’s vector database capabilities, you can implement semantic search, Retrieval Augmented Generation (RAG) with LLMs, recommendation engines, and search in rich media. Learn how.

With the recent introduction of Amazon Security Lake, it has never been simpler to access all your security-related data in one place. Whether it’s findings from AWS Security Hub, DNS query data from Amazon Route 53, network events such as VPC Flow Logs, or third-party integrations provided by partners such as Barracuda Email Protection, Cisco […]