Amazon Web Services

Amazon Web Services provides a wide range of infrastructure and application services that allow you to operate almost anything in the cloud. This includes everything from large enterprise applications and big data initiatives to social gaming and mobile applications. Discover how millions of users—ranging from rapidly growing startups and major corporations to top government organizations—are leveraging AWS to reduce expenses, enhance flexibility, and speed up innovation.

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介绍 2025 年最新 AWS Heroes！ | Amazon Web Services

3 weeks ago | aws.amazon.com | Taylor Katherine Lacy

AWS 社区是一个由创新者、问题解决者和思想领袖组成的活力网络，共同推动云技术发展。今天我们很高兴重点介绍三位杰出人物，他们完美诠释了创新精神、知识共享和社区建设的真谛。从为数百万用户设计可扩展解决方案，到培育包容性技术团体，这些专业人士正在 AWS 社区中做出显著贡献。让我们热烈欢迎他们！ Christian Bonzelet — 德国科隆开发工具 Hero Christian Bonzelet 是德甲联赛的 AWS 解决方案架构师，也是 promptz.dev（一个专为 Amazon Q 开发者版设计的提示库）的创建者。他为 AWS 社区带来了十余年的媒体和娱乐行业专业经验。Christian 自 2013 年在第一个 AWS 项目中为德国一家大型电视广播公司设计大规模投票系统以来，始终热衷于探索 AWS、无服务器架构和 AI/ML 技术。他擅长帮助团队优化 AWS 实施方案并开发符合业务需求的解决方案，特别是在设计服务数百万用户的高可扩展系统方面。Christian 以系统设计与架构的协作方式闻名，并积极与 AWS 社区分享他的见解和经验。 David Victoria...
Streamline your Eclipse workflows with Amazon Q Developer, now generally available | Amazon Web Services

3 weeks ago | aws.amazon.com | Madhu Balaji

Today, we’re excited to announce the general availability of Amazon Q Developer plugin for the Eclipse integrated development environments (IDE). This release builds upon the developer experience introduced in our November 2024 public preview, bringing powerful AI-assisted development capabilities directly into Eclipse 2025-03(4.35.0) and later versions.
Introducing our newest 2025 AWS Heroes cohort | Amazon Web Services

3 weeks ago | aws.amazon.com | Taylor Jacobsen |Taylor Katherine Lacy

The AWS community is a vibrant network of innovators, problem-solvers, and thought leaders who drive cloud technology forward. Today, we’re excited to shine a spotlight on three exceptional individuals who embody the spirit of innovation, knowledge-sharing, and community building. From architecting scalable solutions for millions of users to fostering inclusive tech groups, these professionals are making notable contributions within the AWS community.
BigGo accelerates AI product launch by 50% using AWS | BigGo Case Study | AWS

3 weeks ago | aws.amazon.com

Learn how BigGo launched its generative AI–powered product description and news service for ecommerce websites in half the time with Amazon Bedrock.
Build a secure serverless streaming pipeline with Amazon MSK Serverless, Amazon EMR Serverless and IAM | Amazon Web Services

3 weeks ago | aws.amazon.com | Nitin Kumar |Shubham Purwar |Prashanthi Chinthala

AWS Big Data Blog The exponential growth and vast volume of streaming data have made it a vital resource for organizations worldwide. To unlock its full potential, real-time analytics are essential for extracting actionable insights.
Bridging the gap between development and production: Seamless model lifecycle management with Amazon Bedrock | Amazon Web Services

4 weeks ago | aws.amazon.com | Ishan Singh |Neeraj Lamba

In the landscape of generative AI, organizations are increasingly adopting a structured approach to deploy their AI applications, mirroring traditional software development practices. This approach typically involves separate development and production environments, each with its own AWS account, to create logical separation, enhance security, and streamline workflows.
Unify streaming and analytical data with Amazon Data Firehose and Amazon SageMaker Lakehouse | Amazon Web Services

1 month ago | aws.amazon.com | Maria Ho |Phaneendra Vuliyaragoli |Kalyan Janaki

AWS Big Data Blog Organizations are increasingly required to derive real-time insights from their data while maintaining the ability to perform analytics. This dual requirement presents a significant challenge: how to effectively bridge the gap between streaming data and analytical workloads without creating complex, hard-to-maintain data pipelines.
Why model choice matters: Flexible AI unlocks freedom to innovate | Amazon Web Services

1 month ago | aws.amazon.com | Rahul Pathak

Successful generative AI (gen AI) implementation hinges on a critical and fundamental decision that many organizations overlook: selecting the right foundation models (FMs) for their unique business challenges. Every organization has diverse needs requiring specific AI capabilities—what works perfectly for one use case may be imperfect or impractical for another due to cost-benefit tradeoffs, operational inefficiencies, or misalignment with business outcomes.
Implementing Federation on Amazon MQ for RabbitMQ Private Brokers | Amazon Web Services

1 month ago | aws.amazon.com | Ishita Chakraborty |Vinodh Kannan Sadayamuthu

AWS Compute Blog Federation in RabbitMQ helps in message exchange and flow across multiple RabbitMQ brokers. Amazon MQ for RabbitMQ allows federated exchanges and queues via the Federation Plugin. The federation plugin enables a downstream broker to consume a message from an exchange or a queue on an upstream.
Scalable analytics and centralized governance for Apache Iceberg tables using Amazon S3 Tables and Amazon Redshift | Amazon Web Services

1 month ago | aws.amazon.com | Satesh Sonti |Jonathan M. Katz |Grant Usage

Amazon Redshift supports querying data stored in Apache Iceberg tables managed by Amazon S3 Tables, which we previously covered as part of getting started blog post. While this blog post helps you to get started using Amazon Redshift with Amazon S3 Tables, there are additional steps you need to consider when working with your data in production environments, including who has access to your data and with what level of permissions.