AWS Big Data Blog

Category: Amazon OpenSearch Service

An automated approach to perform an in-place engine upgrade in Amazon OpenSearch Service

Software upgrades bring new features and better performance, and keep you current with the software provider. However, upgrades for software services can be difficult to complete successfully, especially when you can’t tolerate downtime and when the new version’s APIs introduce breaking changes and deprecation that you must remediate. This post shows you how to upgrade […]

Enable cost-efficient operational analytics with Amazon OpenSearch Ingestion

As the scale and complexity of microservices and distributed applications continues to expand, customers are seeking guidance for building cost-efficient infrastructure supporting operational analytics use cases. Operational analytics is a popular use case with Amazon OpenSearch Service. A few of the defining characteristics of these use cases are ingesting a high volume of time series […]

Build multi-layer maps in Amazon OpenSearch Service

With the release of Amazon OpenSearch Service 2.5, you can create maps with multiple layers to visualize your geographical data. You can build each layer from a different index pattern to separate data sources. Organizing the map in layers makes it more straightforward to visualize, view, and analyze geographical data. The layering also helps fetch […]

SmugMug’s durable search pipelines for Amazon OpenSearch Service

SmugMug operates two very large online photo platforms, SmugMug and Flickr, enabling more than 100 million customers to safely store, search, share, and sell tens of billions of photos. Customers uploading and searching through decades of photos helped turn search into critical infrastructure, growing steadily since SmugMug first used Amazon CloudSearch in 2012, followed by […]

Unleash the power of Snapshot Management to take automated snapshots using Amazon OpenSearch Service

Snapshot Management helps you create point-in-time backups of your domain using OpenSearch Dashboards, including both data and configuration settings (for visualizations and dashboards). You can use these snapshots to restore your cluster to a specific state, recover from potential failures, and even clone environments for testing or development purposes. In this post, we share how to use Snapshot Management to take automated snapshots using OpenSearch Service.

Achieve higher query throughput: Auto scaling in Amazon OpenSearch Serverless now supports shard replica scaling

Amazon OpenSearch Serverless is the serverless option for Amazon OpenSearch Service that makes it simple for you to run search and analytics workloads without having to think about infrastructure management. We recently announced new enhancements to autoscaling in OpenSearch Serverless that scales capacity automatically in response to your query loads. At launch, OpenSearch Serverless supported […]

Network connectivity patterns for Amazon OpenSearch Serverless

Amazon OpenSearch Serverless is an on-demand, auto-scaling configuration for Amazon OpenSearch Service. OpenSearch Serverless enables a broad set of use cases, such as real-time application monitoring, log analytics, and website search. OpenSearch Serverless lets you use OpenSearch without having to worry about scaling and managing an OpenSearch cluster. A collection can be accessed over the […]

Improved resiliency with cluster manager task throttling for Amazon OpenSearch Service

Amazon OpenSearch Service is a managed service that makes it simple to secure, deploy, and operate OpenSearch clusters at scale in the AWS Cloud. Amazon OpenSearch clusters are comprised of data nodes and cluster manager nodes. The cluster manager nodes elect a leader among themselves. The leader node is the authority on the metadata in […]

Use the reverse token filter to enable suffix matching queries in OpenSearch

In this post, we show how you can implement a suffix-based search. OpenSearch is an open-source RESTful search engine built on top of the Apache Lucene library. OpenSearch full-text search is fast, can give the result of complex queries within a fraction of a second. With OpenSearch, you can convert unstructured text into structured text using different text analyzers, tokenizers, and filters to improve search. OpenSearch uses a default analyzer, called the standard analyzer, which works well for most use cases out of the box. But for some use cases, it may not work best, and you need to use a specific analyzer.