Category: Learning Levels

OpenSearch is an open source, distributed search engine suitable for a wide array of use-cases such as ecommerce search, enterprise search (content management search, document search, knowledge management search, and so on), site search, application search, and semantic search. It’s also an analytics suite that you can use to perform interactive log analytics, real-time application […]

A protein is a sequence of amino acids that, when chained together, creates a 3D structure. This 3D structure allows the protein to bind to other structures within the body and initiate changes. This binding is core to the working of many drugs. A common workflow within drug discovery is searching for similar proteins, because […]

Amazon OpenSearch Service introduced the OpenSearch Optimized Instances (OR1), deliver price-performance improvement over existing instances. The newly introduced OR1 instances are ideally tailored for heavy indexing use cases like log analytics and observability workloads. OR1 instances use a local and a remote store. The local storage utilizes either Amazon Elastic Block Store (Amazon EBS) of […]

Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed orchestration service for Apache Airflow that significantly improves security and availability, and reduces infrastructure management overhead when setting up and operating end-to-end data pipelines in the cloud. Today, we are announcing the availability of Apache Airflow version 2.9.2 environments on Amazon MWAA. Apache Airflow […]

In this post, we show you how to get started with Apache XTable on AWS and how you can use it in a batch pipeline orchestrated with Amazon Managed Workflows for Apache Airflow (Amazon MWAA). To understand how XTable and similar solutions work, we start with a high-level background on metadata management in an OTF and then dive deeper into XTable and its usage.

EchoStar, a connectivity company providing television entertainment, wireless communications, and award-winning technology to residential and business customers throughout the US, deployed the first standalone, cloud-native Open RAN 5G network on AWS public cloud. This post provides an overview of real-time data analysis with Amazon Redshift and how EchoStar uses it to ingest hundreds of megabytes per second. As data sources and volumes grew across its network, EchoStar migrated from a single Redshift Serverless workgroup to a multi-warehouse architecture with live data sharing.

Customers with data engineers and data scientists are using Amazon Managed Workflows for Apache Airflow (Amazon MWAA) as a central orchestration platform for running data pipelines and machine learning (ML) workloads. To support these pipelines, they often require additional Python packages, such as Apache Airflow Providers. For example, a pipeline may require the Snowflake provider […]

Amazon DataZone, a fully managed data management service, helps organizations catalog, discover, analyze, share, and govern data between data producers and consumers. We are excited to announce the introduction of advanced search filtering capabilities in the Amazon DataZone business data catalog. With the improved rendering of glossary terms, you can now navigate large sets of […]

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. You can start with just a few hundred gigabytes of data and scale to a petabyte or more. This enables you to use your data to acquire new insights for your business and customers. The objective of a disaster recovery plan is […]

Data streaming enables generative AI to take advantage of real-time data and provide businesses with rapid insights. This post looks at how to integrate generative AI capabilities when implementing a streaming architecture on AWS using managed services such as Managed Service for Apache Flink and Amazon Kinesis Data Streams for processing streaming data and Amazon Bedrock to utilize generative AI capabilities. We include a reference architecture and a step-by-step guide on infrastructure setup and sample code for implementing the solution with the AWS Cloud Development Kit (AWS CDK). You can find the code to try it out yourself on the GitHub repo.