8/5/2026, 12:00:00 AM ~ 8/6/2026, 12:00:00 AM (UTC)
Recent Announcements
AWS Lambda announces scalable network bandwidth up to 3,000 Mbps for functions outside a VPC
AWS Lambda now supports scalable network bandwidth for Lambda functions, enabling faster data transfer to and from your execution environment for latency-sensitive workloads. This feature enables functions outside a VPC configured with 2 GB of memory or more to access network bandwidth that scales proportionally, from 625 Mbps at 2 GB up to 3,000 Mbps at 10 GB.\n Customers use Lambda to build latency-sensitive data processing workloads, which need to transfer large volumes of data - up to several terabytes - from external data sources into the function’s execution environment for processing. As data volume and performance requirements grow, the existing limit of 625 Mbps can constrain data transfer speeds to and from an execution environment. With this launch, network throughput increases proportionally from 625 Mbps at 2 GB up to 3,000 Mbps at 10 GB, helping reduce function execution times and per-invocation costs while improving end-user experience. To get started, submit a request through AWS Service Quotas under the Network bandwidth per execution environment quota to enable scalable network bandwidth on your account. Once enabled, bandwidth will scale automatically based on your function’s memory configuration for all functions outside a VPC in your account. Scalable network bandwidth for functions outside a VPC is available at no additional charge in all commercial AWS Regions. To learn more, visit the Lambda quotas page.
Amazon Keyspaces (for Apache Cassandra) is now available in the Canada West (Calgary) Region (ca-west-1), allowing customers in the Canada West Region to build Cassandra-compatible applications with lower latency while keeping their data within the Region to meet data residency requirements. \n Amazon Keyspaces (for Apache Cassandra) is a scalable, highly available, and managed Apache Cassandra–compatible database service. Amazon Keyspaces is serverless, so you pay for only the resources that you use and you can build applications that serve thousands of requests per second with virtually unlimited throughput and storage.
This regional expansion enables organizations in Canada to build highly scalable, low-latency applications using familiar Cassandra Query Language (CQL) without the operational burden of managing Cassandra clusters.
To learn more about on Keyspaces, visit the Amazon Keyspaces documentation.
AWS Marketplace adds AI Insights so buyers can understand pricing before they buy
You can now understand how a product’s pricing works before you buy it. Available in the pricing section of the listing in AWS Marketplace, AI Insights explains each product’s pricing in plain language: what a pricing unit maps to, how your bill changes as usage scales, how multiple pricing dimensions combine into one cost, and what is and isn’t included. Answering these questions used to mean having to visit multiple websites and piecing together pricing details on your own. Now the context sits on the listing, so you can evaluate pricing and move to purchase without switching tabs.\n AI Insights cites sources so you can see where the explanations come from. AI Insights draws from the pricing the seller publishes on the Marketplace listing, and additional pricing context on the seller’s public website.
AI Insights is live today on most listings where external pricing context is available. It is available in all commercial AWS Regions where AWS Marketplace is available. To see it, open any product listing on the AWS Marketplace website and scroll to the pricing section. Sellers can review what appears on their listing and request edits at any time through the Contact Us form linked in the AI Insights page on the AWS Marketplace Seller Guide.
Amazon DynamoDB now supports real-time vector search
Today, AWS announces the general availability of vector search for Amazon DynamoDB, a new feature to index and search vectors in real time. As vector datasets grow into the billions or trillions, vector search at scale traditionally trades off search speed, scale, and accuracy: latency climbs with vector count unless you accept lower recall or throughput. DynamoDB now supports native vector search with single-digit millisecond latency at 99%+ recall and is designed for any scale, even trillions of vectors.\n With DynamoDB vector search, you store vector embeddings alongside your other attributes and generate them using a model of your choice, including models available on Amazon Bedrock. You create a vector index and run approximate nearest neighbor searches, pick the vector index partition key to scale, and filter on attributes to scope results. You get the same serverless benefits you rely on today: zero infrastructure management, zero downtime, zero maintenance windows, and pay for only what you use. You can already use DynamoDB to store memory for AI agents, and with vector search you can now add semantic retrieval over that memory for agentic grounding, along with product similarity search, personalized advertising, retrieval augmented generation, and recommendation systems, with predictable performance. To learn more, visit the AWS News Blog, Amazon DynamoDB product page, and Amazon DynamoDB Developer Guide.
AWS IAM Identity Center now lets you decide whether to enable management of AWS account access when you create a new organization instance. This allows you to use IAM Identity Center to manage access to AWS applications only, without the need to manage access to AWS accounts. This feature is available at the time of initial configuration of an IAM Identity Center instance and does not affect existing IAM Identity Center instances.\n IAM Identity Center enables you to connect your workforce identities to AWS once and offer AWS application owners across your organization streamlined access management. Application end users benefit from single sign-on, user awareness, and consistent authentication experience across AWS applications. Previously, this meant you also needed to manage access to AWS accounts. With this release, account management is now optional. When you choose not to enable management of AWS accounts, IAM Identity Center does not provision its service-linked role into your member accounts, which reduces the access surface in your environment. You can enable account management permissions later through instance settings or the UpdateInstance API.
This capability is available in all AWS Regions where IAM Identity Center is available. To get started, see Configure instance settings in the IAM Identity Center User Guide.
Amazon Aurora serverless now scales faster to support agentic AI and other bursty workloads
Amazon Aurora serverless now delivers higher initial capacity during scale-up events, reaching up to 12 ACUs within a second and continuing to scale up to 256 ACUs as your workload grows. When the workload finishes, Aurora serverless automatically scales down to zero. This makes it especially well-suited for agentic AI applications, which typically have bursts of activity, long idle windows, and unpredictable traffic patterns. Aurora serverless handles all of it automatically, scaling capacity with your agents, so you only pay for what you use.\n This enhancement is enabled by default on all Aurora serverless clusters running on platform version 3 or 4, with no configuration changes required. Existing clusters on platform versions 1 and 2 can upgrade directly to the latest platform version 4 to benefit from these improvements. You can verify your cluster’s platform version in the AWS Management Console under the instance configuration section, or via the RDS API’s ServerlessV2PlatformVersion parameter. For pricing details and Region availability, visit Amazon Aurora Pricing. To learn more, read the Aurora serverless scaling documentation, and get started by creating an Aurora serverless database in just a few steps in the AWS Management Console.
AWS Blogs
AWS Japan Blog (Japanese)
- AWS Weekly Roundup: Bedrock’s GPT Model Price Reduction, CloudWatch Managed Collector for Prometheus Metrics, and More (2026/8/3)
- Introducing KNFSD File Cache: Extend NFS Storage to the Cloud
- Introducing Kiro Crew
- One agent, for every client: How we built the Kiro Agent Harness
- Understand the superior/subordinate relationships of AWS certifications and efficiently renew your certifications
AWS News Blog
AWS Cloud Financial Management
Containers
AWS Database Blog
- Oracle Machine Learning for SQL on Amazon RDS: Build machine learning models entirely in SQL
- Detect CDC failures faster with AWS DMS
- Build semantic search with native vector support in Amazon DynamoDB
AWS Developer Tools Blog
- Announcing response streaming for .NET on AWS Lambda
- Building and Deploying .NET AI Agents with Amazon Bedrock AgentCore
- AWS Tools Installer V2 is Now Generally Available
AWS HPC Blog
AWS for Industries
Artificial Intelligence
- How LendingTree built a multi-agent mortgage assistant on Amazon Bedrock
- How Mobileye transformed support operations using Amazon Bedrock AgentCore
- How we built an MCP bridge to give our AgentCore-hosted AI agent access to local MCP tools
- Run production AI agents in n8n with Amazon Bedrock AgentCore harness
Networking & Content Delivery
AWS Quantum Technologies Blog
AWS Security Blog
- AWS partners with Anthropic and OpenAI to bring AWS Continuum into developer workflows
- From 2 weeks to 2 minutes: Amazon Cognito launches Provisioned limits for self-service rate limit management
AWS Storage Blog
- Analyze Amazon S3 annotations at scale with materialized views
- Accelerate Amazon S3 Replication with automated S3 Batch Operations parallelization