8/29/2025, 12:00:00 AM ~ 9/1/2025, 12:00:00 AM (UTC)
Recent Announcements
Amazon Managed Service for Prometheus adds direct PagerDuty integration
Amazon Managed Service for Prometheus, a fully managed Prometheus-compatible monitoring service now sends alerts directly to PagerDuty, making it easier to manage your incident notifications. You no longer need to create custom Lambda functions or set up additional services to connect with PagerDuty. This direct integration makes alert delivery more reliable and simplifies the authentication process.\n This feature is now available in all AWS regions where Amazon Managed Service for Prometheus is generally available. To configure PagerDuty as a receiver for your Amazon Managed Service for Prometheus alerts, visit the Alert manager tab in the AWS console for Amazon Managed Service for Prometheus or use the AWS CLI, SDK, or APIs. Check out the Amazon Managed Service for Prometheus user guide for detailed documentation.
Amazon SageMaker introduces account-agnostic, reusable project profiles
Amazon SageMaker introduces account-agnostic, reusable project profiles (templates) in Amazon SageMaker Unified Studio domain, enabling domain administrators to define project configurations once and reuse them across multiple AWS accounts and regions. Project profiles are no longer tied to a specific AWS account or region. Instead, platform teams can reference an account pool—a new domain entity that enables dynamic account and region selection at the time of project creation, based on custom enterprise authorization policies or user-specific logic. This decoupling of profile definitions from static deployment settings simplifies governance, reduces duplication, and accelerates onboarding across large-scale data and ML environments.\n Project creators benefit from a more flexible experience: during project creation, they can select from a personalized list of authorized AWS accounts and regions, powered by custom resolution strategies or predefined account pools. This model supports organizations operating across hundreds or thousands of accounts, while preserving centralized control and permission boundaries. This feature is now available in all AWS Regions where Amazon SageMaker Unified Studio is supported.
To learn more about account-agnostic project profiles in Amazon SageMaker refer to account pools in Amazon SageMaker Unified Studio.
RDS Data API now supports IPv6
RDS Data API now supports Internet Protocol Version 6 (IPv6), enabling dual-stack configuration (IPv4 and IPv6) connectivity for your Aurora databases. IPv6 enables an expanded address space, enabling you to scale your application on AWS beyond the typical constraints of the number of IPv4 addresses in your VPC.\n With IPv6, you can assign easy to manage contiguous IP ranges to micro-services and can get virtually unlimited scale for your applications. Moreover, with support for both IPv4 and IPv6, you can gradually transition applications from IPv4 to IPv6, enabling safer migration. IPv6 support is available in all commercial AWS regions where RDS Data API is offered, except Canada (Central). To learn more about Data API and instructions on configuring your network to use IPv6 endpoints, see the documentation. RDS Data API eliminates the use of drivers and improves application scalability by automatically pooling and sharing database connections rather than requiring you to manage connections. Data API also enables access to Aurora databases via AWS AppSync GraphQL APIs. See the documentation to learn more about Data API.
AWS End User Messaging now supports international sending for US toll-free numbers
Today, AWS End User Messaging announces support for international sending for US toll-free numbers. International sending support allows customers to send SMS messages to 150+ country destinations including Canada using their US toll-free numbers. With this this launch, customers can leverage a single phone number to send to many supported country destinations globally simplifying their account and resource setup.\n AWS End User Messaging provides developers with a scalable and cost-effective messaging infrastructure without compromising the safety, security, or results of their communications. Developers can integrate messaging to support uses cases such as one-time passcodes (OTP) at sign-ups, account updates, appointment reminders, delivery notifications, promotions and more. Support for international sending for US toll-free numbers is available in all AWS Regions where End User Messaging is available, see the AWS Region table. To learn more, see AWS End User Messaging.
Amazon QuickSight now supports connectivity to Google Sheets
Today, Amazon QuickSight is announcing the general availability of a native Google Sheets connector.\n Customers can now connect to Google Sheets by logging in with their Google account and importing sheets into a QuickSight SPICE dataset for analysis. Google Sheets connector for Amazon QuickSight is now available in the following regions: US East (N.Virginia and Ohio), US West (Oregon), Canada (Central), South America (Sao Paulo), Europe (Frankfurt, Stockholm, Ireland, London), Asia Pacific (Singapore, Tokyo, Seoul, Sydney). For more details, read our blog post here.
Amazon Neptune Analytics now introduces stop/start capability
Today, we are excited to announce support for Stop/Start in Amazon Neptune Analytics, a new capability that enables organizations to pause and resume their graph workloads on demand,helping reduce costs during idle periods without losing data or configuration.\n Many customers use Neptune Analytics for periodic graph workloads such as fraud detection, recommendation engines, or research simulations that run periodically. Until now, customers had to choose between keeping their Neptune Analytics graphs online even when not in use or deleting and recreating them each time they were needed. This approach was not only expensive, but also time-consuming, requiring manual infrastructure management, repeated data imports, and updates to downstream pipelines to accommodate each newly created graph. This adds significant operational overhead and complexity to their analytics workflows. With Stop/Start, customers can now pause a graph workload via the AWS Console, CLI, or API, and resume it later with a single action. While the graph is stopped, they pay only 10% of the normal compute cost, and all data and settings are preserved without needing to delete or rebuild graphs. This feature is particularly valuable for cost-conscious startups, research teams, and enterprises with analytics workloads. It simplifies lifecycle management and unlocks experimentation at lower price points. Stop/Start for Neptune Analytics is available in all commercial regions where Neptune Analytics is offered. You can start using this feature today via the Neptune Analytics console, AWS CLI, or AWS SDKs. To learn more, visit the documentation and the pricing page.
Amazon QuickSight now available in Israel (Tel Aviv) Region and United Arab Emirates (Dubai) Region
Amazon QuickSight is a fast, scalable, and fully managed Business Intelligence service that lets you easily create and publish interactive dashboards across your organization is now available in Israel (Tel Aviv) and United Arab Emirates (Dubai) Regions. QuickSight dashboards can be authored on any modern web browser with no clients to install or manage; dashboards can be shared with 10s of 1000s of users without the need to provision or manage any infrastructure. QuickSight dashboards can also be seamlessly embedded into your applications, portals, and websites to provide rich, interactive analytics for end-users.\n With this launch, QuickSight expands to 25 regions, including: US East (Ohio and N. Virginia), US West (Oregon), Europe (Spain, Stockholm, Paris, Frankfurt, Ireland, London, Milan and Zurich), Asia Pacific (Mumbai, Seoul, Singapore, Sydney, Beijing, Tokyo and Jakarta), Canada (Central), South America (São Paulo), Africa (Cape Town), AWS GovCloud (US-East, US-West), and now Israel (Tel Aviv) and United Arab Emirates (Dubai). To learn more about Amazon QuickSight, please see our product page, documentation and available regions here.
AWS HealthOmics now supports third-party container registries for private workflows
AWS HealthOmics introduces support for third-party container registries, enabled through Amazon Elastic Container Registry (ECR) pull-through cache, along with URI remapping rules for automatic translation of third-party container URIs to ECR URIs. This enhancement enables AWS HealthOmics customers to more easily access containerized tools from popular third-party registries without needing to manually migrate them to private ECR repositories, or make changes to the workflow definition. AWS HealthOmics is a HIPAA-eligible service that helps healthcare and life sciences customers accelerate scientific breakthroughs with fully managed biological data stores and workflows.\n The ECR pull-through cache capability allows bioinformatics teams to automatically retrieve and cache containers from popular registries including Amazon ECR Public, Docker Hub, Quay, GitHub Container Registry, GitLab Container Registry, Kubernetes container image registry, and Microsoft Azure Container Registry. This helps customers accelerate workflow development and execution by eliminating manual container synchronization tasks. Additionally, the new container URI remapping feature automatically translates third-party registry references in workflow definitions to corresponding private ECR URIs using customer-defined mapping rules, eliminating the need to manually update workflow definitions when migrating workflows. ECR pull-through cache and container URI remapping features are now supported in all regions where AWS HealthOmics is available: US East (N. Virginia), US West (Oregon), Europe (Frankfurt, Ireland, London), Asia Pacific (Singapore), and Israel (Tel Aviv). To learn more about these new features and how to implement them in your workflows, see the AWS HealthOmics documentation.
Amazon EMR announces S3A as the default connector
AWS announces Amazon EMR S3A, a new Amazon S3 connector that optimizes performance for Apache Hadoop, Apache Spark, and Apache Hive workloads on Amazon EMR. This new connector enhances the open source S3A architecture with AWS-specific optimizations to help organizations process large-scale data more efficiently. With direct integration support for S3 Express One Zone, S3 Glacier, and AWS Outposts, EMR S3A helps customers leverage different storage options in AWS to optimize both data access speed and storage cost on their EMR workloads.\n Additionally, the EMR S3A connector delivers advanced security features and performance capabilities that extend beyond open source S3A. Key improvements include Apache Spark built-in fine-grained access control support, enhanced S3A credentials resolver, MagicCommitter V2 for optimized file writes, and accelerated S3 prefix listing for columnar file formats. These enhancements are available starting with EMR release 7.10 and maintain compatibility with existing applications.
The Amazon EMR S3A connector is available in all AWS Regions where Amazon EMR is available and comes pre-configured with Amazon EMR release version 7.10 and later. To learn more about Amazon EMR S3A, see the Amazon EMR documentation.
Amazon EMR on EC2 Adds Apache Spark native FGAC and AWS Glue Data Catalog Views Support
Amazon EMR on EC2 announces two significant enhancements for governance: Apache Spark native fine-grained access control (FGAC) via AWS Lake Formation, and support for AWS Glue Data Catalog views. These features allow organizations to improve data security, simplify access management, and enhance data sharing capabilities across their analytics environments.\n The Apache Spark native FGAC implementation allows customers to define granular access policies once in AWS Lake Formation and apply them consistently across EMR clusters. This reduces security risks and administrative overhead while providing a unified approach to data governance. Customers can now use familiar Lake Formation grant and revoke statements to manage access controls for their Spark jobs and interactive sessions on EMR on EC2, similar to how this works for other AWS analytics services. AWS Glue Data Catalog views enables customers to create, manage, and query multi-engine SQL views across AWS regions, accounts, and organizations. This feature allows administrators to create views from Spark jobs that can be queried from multiple engines, while controlling data access through Lake Formation permissions. These permissions include named resource grants, data filters, and tags, with all access requests automatically logged in AWS CloudTrail for comprehensive auditing. Apache Spark native FGAC and Glue Data Catalog view features are available with Amazon EMR release 7.10 in all AWS Regions where EMR on EC2 is available. To learn more, visit Using AWS Lake Formation with Amazon EMR and Working with AWS Glue Data Catalog Views in the Amazon EMR documentation.
AWS IAM launches new VPC endpoint condition keys for network perimeter controls
AWS Identity and Access Management (IAM) now offers three new global condition keys that will make it easier for you to establish a network perimeter. The new condition keys - aws:VpceAccount, aws:VpceOrgPaths, and aws:VpceOrgID - help you ensure that requests to your AWS resources or by your identities are made through your VPC endpoints.\n The condition keys provide you with varied levels of granularity, enabling you to implement your network perimeter controls at an account, organization path, and entire organization level. The controls automatically scale with your VPC usage, eliminating the need to enumerate VPC endpoints or update policies as you add or remove them. You can use these condition keys with both new and existing service control policies (SCPs), resource control policies (RCPs), resource-based policies, and identity-based policies. The condition keys are supported for a select set of AWS services and are available in all commercial AWS Regions where those services support AWS PrivateLink. To learn more about these new condition keys and supported services, please visit the AWS IAM documentation and AWS blog.
Amazon Verified Permissions is available in four additional regions
Amazon Verified Permissions is now available in Asia Pacific (Taipei), Asia Pacific (Thailand), Asia Pacific (Malaysia), and Mexico (Central) Regions. The service provides fine-grained authorization for the applications that you build, allowing you to implement permissions as policies rather than application code. Applications call Verified Permissions to authorize access to APIs and resources managed by the application.\n Amazon Verified Permissions is a scalable permissions management and fine-grained authorization service for the applications that you build. Using Cedar, an expressive and analyzable open-source policy language, developers and administrators can define policy-based access controls using roles and attributes for more granular, context-aware access control. For example, an HR application might call Amazon Verified Permissions to determine if Alice is permitted access to Bob’s performance evaluation, given that she is in the HR Managers group.
With this Region expansion, Verified Permissions is now available in 35 regions globally. For more information, visit the Verified Permissions product page.
Introducing Amazon EC2 I8ge instances
AWS is announcing the general availability of Amazon Elastic Compute Cloud (Amazon EC2) storage optimized I8ge instances. I8ge instances are powered by AWS Graviton4 processors to deliver up to 60% better compute performance compared to previous generation Graviton2-based storage optimized Amazon EC2 instances. I8ge instances use the latest third generation AWS Nitro SSDs, local NVMe storage that deliver up to 55% better real-time storage performance per TB while offering up to 60% lower storage I/O latency and up to 75% lower storage I/O latency variability compared to previous generation Im4gn instances. At 120 TB, I8ge instances have the highest storage density among AWS Graviton-based storage optimized Amazon EC2 instances. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software enhancing the performance and security for your workloads.\n I8ge instances offer instance sizes up to 48xlarge including two metal sizes, 1,536 GiB of memory, and 120 TB instance storage. At 300 Gbps, these instances have the highest networking bandwidth among storage optimized Amazon EC2 instances. They are ideal for real-time applications that require much larger storage density such as relational databases, non-relational databases, streaming databases, search queries and data analytics.
I8ge instances are available in the following AWS Regions: US East (Ohio), US East (N. Virginia) and US West (Oregon).
To learn more, see Amazon EC2 I8ge instances. To begin your Graviton journey, visit the Level up your compute with AWS Graviton page. To get started, see AWS Management Console, AWS Command Line Interface (AWS CLI), and AWS SDKs.
The Amazon SageMaker lakehouse architecture now supports tag based access control (TBAC) for managing fine-grained data access across federated catalogs. This capability, previously available only for default AWS Glue Data Catalog resources, is now available across Amazon S3 Tables, Amazon Redshift data warehouses, and federated data sources including Amazon DynamoDB, PostgreSQL, and SQL Server. TBAC enables simplified permission management by logically grouping catalog resources using tags, allows scaling permissions across datasets with a minimal set of permissions, and also facilitates data sharing across different accounts.\n TBAC simplifies how administrators manage data access permissions by replacing direct resource-level permissions with tag-based grants. Instead of manually assigning permissions to individual tables or columns, administrators can now efficiently control access through tags that are automatically inherited by resources. This inheritance feature ensures that new tables automatically receive appropriate fine-grained access controls without additional policy modifications. You can get started with TBAC through the AWS Lake Formation console. Create tags using key-value pairs, associate them with databases, tables, or columns, and grant permissions to principals based on specific tags. Users can then access tagged resources through Amazon Athena, Amazon Redshift, Amazon EMR, or Amazon SageMaker Unified Studio. This feature is available through the AWS Management Console, AWS CLI, and AWS SDKs in all commercial AWS Regions. To get started, read the blog and visit the Lake Formation Tags documentation.
AWS Blogs
AWS Japan Blog (Japanese)
- Announcing AWS Innovate: Migrate and Modernize
- Construction and implementation of the AI agent development and sharing platform “KTC Agent Store” using Amazon Bedrock
- Billing and Cost Management MCP Server Announced
- Zero-ETL: Addressing Data Integration Challenges with AWS
AWS Big Data Blog
Containers
AWS for Industries
Artificial Intelligence
- Detect Amazon Bedrock misconfigurations with Datadog Cloud Security
- Set up custom domain names for Amazon Bedrock AgentCore Runtime agents
- Introducing auto scaling on Amazon SageMaker HyperPod