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Building a 10-billion wallet crypto-intelligence platform: Elliptic’s journey with Amazon DynamoDB | AWS Database Blog
In this post, we explore how Elliptic uses Amazon DynamoDB to build a crypto-intelligence platform that scales to over 10 billion wallets globally and supports real-time risk detection across the fast-evolving digital asset ecosystem. We discuss the data model design, indexing strategies, and operational setup that Elliptic uses to power real-time risk analysis and complex investigations at scale.
Implement a secure MLOps platform based on Terraform and GitHub | Artificial Intelligence
Machine learning operations (MLOps) is the combination of people, processes, and technology to productionize ML use cases efficiently. To achieve this, enterprise customers must develop MLOps platforms to support reproducibility, robustness, and end-to-end observability of the ML use case’s lifecycle. Those platforms are based on a multi-account setup by adopting strict security constraints, development best […]
Implement automated monitoring for Amazon Bedrock batch inference | Artificial Intelligence
In this post, we demonstrated how a financial services company can use an FM to process large volumes of customer records and get specific data-driven product recommendations. We also showed how to implement an automated monitoring solution for Amazon Bedrock batch inference jobs. By using EventBridge, Lambda, and DynamoDB, you can gain real-time visibility into batch processing operations, so you can efficiently generate personalized product recommendations based on customer credit data.
Best practices for migrating from Apache Airflow 2.x to Apache Airflow 3.x on Amazon MWAA | AWS Big Data Blog
Apache Airflow 3.x on Amazon MWAA introduces architectural improvements such as API-based task execution that provides enhanced security and isolation. This migration presents an opportunity to embrace next-generation workflow orchestration capabilities while providing business continuity. This post provides best practices and a streamlined approach to successfully navigate this critical migration, providing minimal disruption to your mission-critical data pipelines while maximizing the enhanced capabilities of Airflow 3.
Monitor Amazon Timestream for InfluxDB performance using the Timestream for InfluxDB Metrics dashboard | AWS Database Blog
The Timestream for InfluxDB Metrics dashboard adds the ability to perform trend analysis, create actionable insights, set up alerts, and automate reporting. You can configure the Timestream for InfluxDB Metrics dashboard to suit your business needs and build a robust and optimized time series workflow. In this post we walk you through how to deploy the Timestream for InfluxDB Metrics dashboard to start monitoring the performance of your fleet of Timestream for InfluxDB databases.
Responsible AI: How PowerSchool safeguards millions of students with AI-powered content filtering using Amazon SageMaker AI | Artificial Intelligence
In this post, we demonstrate how PowerSchool built and deployed a custom content filtering solution using Amazon SageMaker AI that achieved better accuracy while maintaining low false positive rates. We walk through our technical approach to fine tuning Llama 3.1 8B, our deployment architecture, and the performance results from internal validations.
Seamlessly Integrate Data on Google BigQuery and ClickHouse Cloud with AWS Glue | AWS Big Data Blog
Migrating from Google Cloud’s BigQuery to ClickHouse Cloud on AWS allows businesses to leverage the speed and efficiency of ClickHouse for real-time analytics while benefiting from AWS’s scalable and secure environment. This article provides a comprehensive guide to executing a direct data migration using AWS Glue ETL, highlighting the advantages and best practices for a […]
Bridging data silos: cross-bounded context querying with Vanguard’s Operational Read-only Data Store (ORDS) using Amazon Redshift | AWS Big Data Blog
At Vanguard, we faced significant challenges with our legacy mainframe system that limited our ability to deliver modern, personalized customer experiences. Our centralized database architecture created performance bottlenecks and made it difficult to scale services independently for our millions of personal and institutional investors. In this post, we show you how we modernized our data architecture using Amazon Redshift as our Operational Read-only Data Store (ORDS).
Unlock global AI inference scalability using new global cross-Region inference on Amazon Bedrock with Anthropic’s Claude Sonnet 4.5 | Artificial Intelligence
Organizations are increasingly integrating generative AI capabilities into their applications to enhance customer experiences, streamline operations, and drive innovation. As generative AI workloads continue to grow in scale and importance, organizations face new challenges in maintaining consistent performance, reliability, and availability of their AI-powered applications. Customers are looking to scale their AI inference workloads across […]
Key components of a data-driven agentic AI application | AWS Database Blog
In this post, we look at the costs, benefits, and drawbacks of replacing services for agentic AI with direct database access. Including those that work well and are proven in production, and new services yet to be built. Let’s take a closer look at the anatomy of an agentic AI application and what would factor into such decisions.
Secure ingress connectivity to Amazon Bedrock AgentCore Gateway using interface VPC endpoints | Artificial Intelligence
In this post, we demonstrate how to access AgentCore Gateway through a VPC interface endpoint from an Amazon Elastic Compute Cloud (Amazon EC2) instance in a VPC. We also show how to configure your VPC endpoint policy to provide secure access to the AgentCore Gateway while maintaining the principle of least privilege access.
Enhance agentic workflows with enterprise search using Kore.ai and Amazon Q Business | Artificial Intelligence
In this post, we demonstrate how organizations can enhance their employee productivity by integrating Kore.ai’s AI for Work platform with Amazon Q Business. We show how to configure AI for Work as a data accessor for Amazon Q index for independent software vendors (ISVs), so employees can search enterprise knowledge and execute end-to-end agentic workflows involving search, reasoning, actions, and content generation.
Accelerate development with the Amazon Bedrock AgentCore MCP server | Artificial Intelligence
Today, we’re excited to announce the Amazon Bedrock AgentCore Model Context Protocol (MCP) Server. With built-in support for runtime, gateway integration, identity management, and agent memory, the AgentCore MCP Server is purpose-built to speed up creation of components compatible with Bedrock AgentCore. You can use the AgentCore MCP server for rapid prototyping, production AI solutions, […]
Optimize efficiency with language analyzers using scalable multilingual search in Amazon OpenSearch Service | AWS Big Data Blog
Organizations manage content across multiple languages as they expand globally. Ecommerce platforms, customer support systems, and knowledge bases require efficient multilingual search capabilities to serve diverse user bases effectively. This unified search approach helps multinational organizations maintain centralized content repositories while making sure users, regardless of their preferred language, can effectively find and access relevant […]
Build a dynamic workflow orchestration engine with Amazon DynamoDB and AWS Lambda | AWS Database Blog
In this post, I show you how to build a serverless workflow orchestration engine that uses Amazon DynamoDB and AWS Lambda. The complete implementation is available in a GitHub repository, which includes two fully functional examples that you can deploy and run immediately to see the orchestration engine in action.
How Laravel Nightwatch handles billions of observability events in real time with Amazon MSK and ClickHouse Cloud | AWS Big Data Blog
Laravel, one of the world’s most popular web frameworks, launched its first-party observability platform, Laravel Nightwatch, to provide developers with real-time insights into application performance. Built entirely on AWS managed services and ClickHouse Cloud, the service already processes over one billion events per day while maintaining sub-second query latency, giving developers instant visibility into the health of their applications.
Introducing Apache Airflow 3 on Amazon MWAA: New features and capabilities | AWS Big Data Blog
AWS announced the general availability of Apache Airflow 3 on Amazon Managed Workflows for Apache Airflow (Amazon MWAA). This release transforms how organizations use Apache Airflow to orchestrate data pipelines and business processes in the cloud, bringing enhanced security, improved performance, and modern workflow orchestration capabilities to Amazon MWAA customers. This post explores the features of Airflow 3 on Amazon MWAA and outlines enhancements that improve your workflow orchestration capabilities
Rox accelerates sales productivity with AI agents powered by Amazon Bedrock | Artificial Intelligence
We’re excited to announce that Rox is generally available, with Rox infrastructure built on AWS and delivered across web, Slack, macOS, and iOS. In this post, we share how Rox accelerates sales productivity with AI agents powered by Amazon Bedrock.
How Hapag-Lloyd improved schedule reliability with ML-powered vessel schedule predictions using Amazon SageMaker | Artificial Intelligence
In this post, we share how Hapag-Lloyd developed and implemented a machine learning (ML)-powered assistant predicting vessel arrival and departure times that revolutionizes their schedule planning. By using Amazon SageMaker AI and implementing robust MLOps practices, Hapag-Lloyd has enhanced its schedule reliability—a key performance indicator in the industry and quality promise to their customers.
Modernize fraud prevention: GraphStorm v0.5 for real-time inference | Artificial Intelligence
In this post, we demonstrate how to implement real-time fraud prevention using GraphStorm v0.5's new capabilities for deploying graph neural network (GNN) models through Amazon SageMaker. We show how to transition from model training to production-ready inference endpoints with minimal operational overhead, enabling sub-second fraud detection on transaction graphs with billions of nodes and edges.
Search++, Going Beyond Keywords with Amazon OpenSearch Service | AWS Big Data Blog
Search technology, specifically web search technology, has been around for more than 30 years. You entered a few words in a text box, clicked “Search,” and received a series of links. However, the results were often a mix of related, non-related, and general links. If the results didn’t contain the information you needed, you reformulated […]
How Smartsheet enhances recommendations using Amazon Neptune and Knowledge Graphs | AWS Database Blog
Smartsheet is a leading SaaS-based collaborative work management platform trusted by enterprises worldwide to manage projects, automate workflows, and drive collaboration at scale. In this post, we describe the Smartsheet Knowledge Graph, built in partnership between Smartsheet and AWS. The Smartsheet Knowledge Graph is a unified data model connecting people, content, and work in Smartsheet, representing how users interact with assets, content, and their collaborators.
Building health care agents using Amazon Bedrock AgentCore | Artificial Intelligence
In this solution, we demonstrate how the user (a parent) can interact with a Strands or LangGraph agent in conversational style and get information about the immunization history and schedule of their child, inquire about the available slots, and book appointments. With some changes, AI agents can be made event-driven so that they can automatically send reminders, book appointments, and so on.
Identifying and resolving performance issues caused by TOAST OID contention in Amazon Aurora PostgreSQL Compatible Edition and Amazon RDS for PostgreSQL | AWS Database Blog
In this post, we explore the challenges of OID exhaustion in PostgreSQL, focusing on its impact on TOAST tables and how it leads to performance issues. We will cover how to identify the problem by reviewing wait events, session activity, and table usage. Additionally, we discuss practical solutions, from cleaning up data to more advanced strategies such as partitioning.
Build multi-agent site reliability engineering assistants with Amazon Bedrock AgentCore | Artificial Intelligence
In this post, we demonstrate how to build a multi-agent SRE assistant using Amazon Bedrock AgentCore, LangGraph, and the Model Context Protocol (MCP). This system deploys specialized AI agents that collaborate to provide the deep, contextual intelligence that modern SRE teams need for effective incident response and infrastructure management.
Scaling cluster manager and admin APIs in Amazon OpenSearch Service | AWS Big Data Blog
In this post, we demonstrate the different bottlenecks that were identified and the corresponding solutions that were implemented in OpenSearch Service to scale cluster manager for large cluster deployments. These optimizations are available to all new domains or existing domains upgraded to OpenSearch Service versions 2.17 or above.
Implement event-driven architectures with Amazon DynamoDB | AWS Database Blog
In this three-part series, we explore approaches to implement enhanced event-driven patterns for DynamoDB-backed applications. In this post (Part 1), we focus on improving DynamoDB's native TTL functionality by implementing near real-time data eviction using EventBridge Scheduler, reducing the typical time to delete expired items from within a few days to less than one minute.
DoWhile loops now supported in Amazon Bedrock Flows | Artificial Intelligence
Today, we are excited to announce support for DoWhile loops in Amazon Bedrock Flows. With this powerful new capability, you can create iterative, condition-based workflows directly within your Amazon Bedrock flows, using Prompt nodes, AWS Lambda functions, Amazon Bedrock Agents, Amazon Bedrock Flows inline code, Amazon Bedrock Knowledge Bases, Amazon Simple Storage Service (Amazon S3), […]
Accelerate benefits claims processing with Amazon Bedrock Data Automation | Artificial Intelligence
In the benefits administration industry, claims processing is a vital operational pillar that makes sure employees and beneficiaries receive timely benefits, such as health, dental, or disability payments, while controlling costs and adhering to regulations like HIPAA and ERISA. In this post, we examine the typical benefit claims processing workflow and identify where generative AI-powered automation can deliver the greatest impact.
Implement event-driven architectures with Amazon DynamoDB – Part 3 | AWS Database Blog
In this three-part series, we explore approaches to implement enhanced event-driven patterns for DynamoDB-backed applications. Throughout this series, we’ve examined various strategies for managing data within DynamoDB. This post shifts the focus to an event-driven pattern that reliably schedules future downstream actions using EventBridge Scheduler.
How PropHero built an intelligent property investment advisor with continuous evaluation using Amazon Bedrock | Artificial Intelligence
In this post, we explore how we built a multi-agent conversational AI system using Amazon Bedrock that delivers knowledge-grounded property investment advice. We explore the agent architecture, model selection strategy, and comprehensive continuous evaluation system that facilitates quality conversations while facilitating rapid iteration and improvement.
Implement event-driven architectures with Amazon DynamoDB – Part 2 | AWS Database Blog
In this three-part series, we explore approaches to implement enhanced event-driven patterns for DynamoDB-backed applications. In this post (Part 2), we explore another method which uses global secondary indexes (GSIs) to handle fine-grained Time to Live (TTL) requirements.
Optimize Amazon EMR runtime for Apache Spark with EMR S3A | AWS Big Data Blog
With the Amazon EMR 7.10 runtime, Amazon EMR has introduced EMR S3A, an improved implementation of the open source S3A file system connector. In this post, we showcase the enhanced read and write performance advantages of using Amazon EMR 7.10.0 runtime for Apache Spark with EMR S3A as compared to EMRFS and the open source S3A file system connector.
Amazon OpenSearch Serverless monitoring: A CloudWatch setup guide | AWS Big Data Blog
In this post, we explore commonly used Amazon CloudWatch metrics and alarms for OpenSearch Serverless, walking through the process of selecting relevant metrics, setting appropriate thresholds, and configuring alerts. This guide will provide you with a comprehensive monitoring strategy that complements the serverless nature of your OpenSearch deployment while maintaining full operational visibility.
Raising the bar on Amazon DynamoDB data modeling | AWS Database Blog
In April 2025, we introduced the Amazon DynamoDB data modeling tool for the Model Context Protocol (MCP) server. The tool guides you through a conversation, collects your requirements, and produces a data model that includes tables, indexes, and cost considerations. In this post, we show you how we built this automated evaluation framework and how it helped us deliver reliable DynamoDB data modeling guidance at scale.
Long-term storage and analysis of Amazon RDS events with Amazon S3 and Amazon Athena | AWS Database Blog
In this post, we show you how to implement an automated solution for archiving Amazon RDS events to Amazon Simple Storage Service (Amazon S3). We also discuss how to analyze the events with Amazon Athena which helps enable proactive database management, helps maintain security and compliance, and provides valuable insights for capacity planning and troubleshooting.