Category: Amazon OpenSearch Service
In this blog post, we discuss the impact of Amazon Elastic Block Store (Amazon EBS) volume IOPS and throughput limits on Amazon OpenSearch Service domain and how to prevent/mitigate throughput throttling situation.
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.
Ingesting a high volume of streaming data has been a defining characteristic of operational analytics workloads with Amazon OpenSearch Service. Many of these workloads involve either self-managed Apache Kafka or Amazon Managed Streaming for Apache Kafka (Amazon MSK) to satisfy their data streaming needs. Consuming data from Amazon MSK and writing to OpenSearch Service has been a challenge for customers. AWS Lambda, custom code, Kafka Connect, and Logstash have been used for ingesting this data. These methods involve tools that must be built and maintained. In this post, we introduce Amazon MSK as a source to Amazon OpenSearch Ingestion, a serverless, fully managed, real-time data collector for OpenSearch Service that makes this ingestion even easier.
This post demonstrates how to use Terraform to create, deploy, and clean up OpenSearch Serverless infrastructure.. Amazon OpenSearch Serverless provides the search and analytical functionality of OpenSearch without the manual overhead of configuring, managing, and scaling OpenSearch clusters. It automatically scales the resources based on your workload, and you only pay for the resources consumed. Managing OpenSearch Serverless is simple, but with infrastructure as code (IaC) software like Terraform, you can simplify your resource management even more.
Amazon OpenSearch Serverless is a serverless deployment option for Amazon OpenSearch Service that makes it simple for you to run search and analytics workloads without having to think about infrastructure management. The compute capacity used for data ingestion, and search and query in OpenSearch Serverless is measured in OpenSearch Compute Units (OCUs). Customers can configure […]
Amazon Security Lake centralizes access and management of your security data by aggregating security event logs from AWS environments, other cloud providers, on premise infrastructure, and other software as a service (SaaS) solutions. By converting logs and events using Open Cybersecurity Schema Framework, an open standard for storing security events in a common and shareable format, […]
Since its release in January 2021, the OpenSearch project has released 14 versions through June 2023. Amazon OpenSearch Service supports the latest versions of OpenSearch up to version 2.7. OpenSearch Service provides two configuration options to deploy and operate OpenSearch at scale in the cloud. With OpenSearch Service managed domains, you specify a hardware configuration […]
In this post, we explore how to deploy Amazon CloudWatch metrics using an AWS CloudFormation template to monitor an OpenSearch Service domain’s storage and shard skew. This solution uses an AWS Lambda function to extract storage and shard distribution metadata from your OpenSearch Service domain, calculates the level of skew, and then pushes this information to CloudWatch metrics so that you can easily monitor, alert, and respond.
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.