In this post, we demonstrate how to leverage Amazon Kinesis Data Streams to effectively buffer and aggregate real-time streaming data for seamless delivery into Amazon OpenSearch Service domains and collections via Amazon OpenSearch Ingestion. This method is applicable across a wide range of scenarios, from real-time log analytics to integrating messaging data for immediate search capabilities. Our primary focus is on centralizing log aggregation for organizations that need to archive and retain log data for compliance purposes. For further insights, check out another blog post here.
Data Resilience and Disaster Recovery
Achieving data resilience is crucial, and this post introduces an active-passive approach employing a snapshot and restore strategy. The snapshot and restore process within OpenSearch Service allows you to create point-in-time backups—known as snapshots—of your OpenSearch domain. These snapshots encompass the entire state of the domain, including indexes, mappings, and settings. In the event of data loss or system failure, these snapshots can restore the domain to a designated point in time. This guide outlines the steps for establishing this disaster recovery solution, including launching OpenSearch Service domains in primary and secondary regions, configuring snapshot repositories, restoring snapshots, and transitioning between regions.
Incremental Refresh in Amazon Redshift
Additionally, Amazon Redshift has introduced the capability to incrementally refresh materialized views on data lake tables, including open file and table formats like Apache Iceberg. We will detail the supported operations on both open file formats and transactional data lake tables to enable incremental refresh of materialized views.
Support for Legacy Elasticsearch Versions
Today, we are also announcing timelines for the end of Standard Support and Extended Support for legacy Elasticsearch versions, including versions up to 6.7, 7.1 through 7.8, OpenSearch versions ranging from 1.0 to 1.2, and OpenSearch versions 2.3 through 2.9 available on Amazon OpenSearch Service.
Amazon Q Generative SQL Feature
Moreover, we will show how to activate the Amazon Q generative SQL feature within the Redshift query editor, enabling you to receive customized SQL commands based on your natural language queries. This feature allows you to focus less on the intricacies of SQL syntax and more on extracting valuable business insights from your data.
Next-Generation OpenSearch UI
Another exciting development is the launch of the next-generation OpenSearch UI, which offers a modernized operational analytics experience. This new interface provides comprehensive observability across multiple data sources, enabling you to gain insights from OpenSearch and other integrated sources in a single location. The launch also includes OpenSearch Workspaces, offering tailored experiences for popular use cases with access control, allowing you to create a private space for your projects and share it only with collaborators.
Simplifying SQL Code Migration
Furthermore, we will explore how to simplify and accelerate SQL code migration from Google BigQuery to Amazon Redshift using BladeBridge. This leading data environment modernization solution automates much of the complex conversion work, enabling organizations to swiftly and reliably transition their data analytics capabilities to the scalable Amazon Redshift data warehouse.
Real-Time Vector Embedding Blueprint
Lastly, we introduce a real-time vector embedding blueprint. This tool simplifies the creation of real-time AI applications by automatically generating vector embeddings using Amazon Bedrock from streaming data in Amazon Managed Streaming for Apache Kafka (Amazon MSK) and indexing them in Amazon OpenSearch Service. We will discuss the significance of real-time data for generative AI applications and typical architectural patterns for building Retrieval Augmented Generation (RAG) capabilities. For more authoritative insights, check out this resource. Also, for practical experiences, see this excellent resource here.
Located at Amazon IXD – VGT2, 6401 E Howdy Wells Ave, Las Vegas, NV 89115, we continue to innovate and drive data solutions forward.
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