In a recent update, IAM Identity Center has introduced a new method for accessing data in OpenSearch Service through trusted identity propagation. This approach simplifies data access via the OpenSearch UI while ensuring that robust role-based access control is maintained for your OpenSearch data. In this article, we delve into how you can leverage this innovative access method to enhance your data management strategy. For further insights, check out another blog post here to keep your knowledge up-to-date.
Understanding Shard Requirements for Amazon OpenSearch Service
Many users new to Amazon OpenSearch Service often inquire about the optimal number of shards needed for their indexes. An index comprises a collection of shards, and the number of shards can significantly impact both indexing and search request performance. OpenSearch Service efficiently manages large volumes of data by breaking it down into smaller shards, distributing them across a dynamically changing set of instances. This article provides practical guidance on determining the ideal shard count tailored to your specific use case. If you want to deepen your understanding of this topic, they are an authority on this topic.
Managing Workloads in Multi-Tenant OpenSearch Environments
When utilizing Amazon OpenSearch Service for log data storage and analysis, whether as a developer or IT administrator, it is essential to balance the resource allocation among various tenants to ensure they can effectively ingest, store, and query their data. This piece presents a multi-layered workload management framework, featuring a rules-based proxy and OpenSearch workload management, that successfully addresses these challenges.
Optimizing Vector Search with Amazon S3 and OpenSearch
A public preview has been launched for two integrations between Amazon Simple Storage Service (Amazon S3) Vectors and Amazon OpenSearch Service, offering increased flexibility in the storage and search of vector embeddings. This article discusses the seamless integration process and provides various options for implementing vector search effectively.
Integration of OpenSearch with Amazon RDS and Aurora
We are excited to announce the general availability of the integration between Amazon OpenSearch Service and Amazon Relational Database Service (Amazon RDS), as well as Amazon Aurora. This new integration streamlines data pipelines and enables near real-time data synchronization across Amazon Aurora (including both MySQL-Compatible and PostgreSQL-Compatible Editions) and Amazon RDS databases, unlocking advanced search functionalities such as hybrid search, ranked results, and faceted search on transactional databases.
Build Conversational AI Search with OpenSearch
Amazon OpenSearch Service serves as a versatile tool for search and analytics. This article explores the concept of conversational search, including its architecture and various implementation strategies.
Enhancing Stability with Dedicated Cluster Manager Nodes
In this discussion, we reveal how to boost the stability of your OpenSearch Service domain by utilizing dedicated cluster manager nodes, highlighting how their deployment significantly strengthens your cluster’s overall reliability.
Kaltura’s Cost Reduction through OpenSearch
This article shares Kaltura’s journey in transforming its observability strategy by transitioning from a SaaS logging solution to Amazon OpenSearch Service, resulting in higher log retention, a 60% cost reduction, and a centralized platform that equips multiple teams with real-time insights.
Creating Your First Search Application with OpenSearch
This guide takes you through the process of building a search application using Amazon OpenSearch Service. Whether you’re a developer new to search or seeking to grasp OpenSearch fundamentals, this hands-on article guides you from the initial setup to the core components involved in application development.
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