Kategorie: Amazon AWS

AWS Management Console now displays AWS Local Zones in the Region Selector

Today, AWS announces the addition of AWS Local Zones to the Region selector in the AWS Management Console, providing a unified experience across AWS global infrastructure. AWS Local Zones now appear alongside AWS Regions in the Console’s top navigation, making it easier for customers to quickly navigate to the Console page for managing their resources in AWS Local Zones.
Now, when customers select the Local Zones tab in the Region selector, they will see all opted-in AWS Local Zones in one place. Clicking on an AWS Local Zone takes customers directly to its parent Region’s Console page to view and manage resources. This capability streamlines navigation for customers operating across multiple AWS Local Zones parented to different AWS Regions.
This capability is available across all AWS Local Zones in public AWS Regions. To get started, navigate to the Region selector in the AWS Management Console. For more information, see the AWS Local Zones documentation.
Quelle: aws.amazon.com

Amazon SageMaker Studio now supports GPU capacity reservation through SageMaker Flexible Training Plans

Amazon SageMaker Studio IDEs, including JupyterLab and Code Editor, now support GPU capacity reservations through SageMaker Flexible Training Plans (FTP), giving you predictable access to high-demand, high-performance computational resources within your budget. By leveraging FTP, you can achieve up to 65% cost savings compared to On-Demand instances while running ML workflows in JupyterLab or Code Editor. FTP provides a fully self-serve procurement experience. To get started, navigate to the SageMaker FTP console and select your preferred instance type, reservation length, and start date for your Studio IDE workload. Review your order, complete the purchase, and wait for the plan to become active. When creating a Studio app from the SageMaker Studio UI, select your purchased plan from the Instance dropdown. SageMaker provisions the instance automatically with no infrastructure management required on your part. As your plan nears expiration, the IDE proactively notifies you, giving you time to save your work before the reservation ends.
To learn more about using FTP capacity reservation capability with Studio IDEs, see Using Training Plans with Studio IDEs. To learn about launching JupyterLab and Code Editor applications in SageMaker Studio, see Studio Spaces documentation.
 
Quelle: aws.amazon.com

Amazon Redshift adds ALTER TABLE for Iceberg tables and writes via the AWS Glue Data Catalog mount

Amazon Redshift now supports writing directly to Apache Iceberg tables via the AWS Glue Data Catalog (awsdatacatalog) mount and ALTER TABLE DDL statements to modify the schema, partitioning, and properties of Apache Iceberg tables. With write access through the auto-mounted awsdatacatalog, you can land Redshift transformations in your data lake for any engine to query without creating external schemas—particularly useful for Iceberg tables federated with AWS Lake Formation. Supported ALTER TABLE operations include ADD/DROP/ALTER columns, RENAME COLUMN, SET TABLE PROPERTIES to overwrite the default compression type, and ADD/DROP/REPLACE PARTITION FIELD to adapt partitioning strategies as data volumes grow. Previously, updating the structure of Iceberg tables required deleting the table and its data, adding complexity and latency to data pipelines. Tables modified by Redshift remain compatible with other Iceberg-compatible engines, including Amazon EMR and Amazon Athena, preserving cross-engine interoperability. AWS Lake Formation permissions are supported for Iceberg write operations. These capabilities are available in all AWS Regions where Amazon Redshift is available. To get started, visit the Referencing Iceberg tables in Amazon Redshift and Altering table definitions sections in the Amazon Redshift Database Developer Guide.
Quelle: aws.amazon.com

AWS SAM CLI adds AWS CloudFormation Language Extensions support to accelerate local serverless development

AWS SAM CLI now supports AWS CloudFormation Language Extensions, enabling you to reduce duplication in your infrastructure as code (IaC) templates while retaining the full local development workflow. This accelerates your serverless development by letting you define resources once and iterate locally without waiting for cloud deployments.
Developers frequently need to define multiple similar resources, such as Lambda functions, DynamoDB tables, or SNS topics, from a single template definition. However, developers who use SAM CLI to build, test, and deploy their serverless applications previously could not process templates that use CloudFormation Language Extensions. This required choosing between reducing template duplication and using SAM CLI for local development. Now, SAM CLI processes Language Extensions in memory for local operations while preserving your original template for CloudFormation deployment. You can define your resources once and test them locally across all SAM CLI commands, catching errors like invalid syntax or missing dependencies before deploying. This shortens your iteration cycles and reduces time spent debugging failed deployments in the cloud.
To get started, download or update SAM CLI to the latest version. Add the AWS::LanguageExtensions transform to your SAM template and use Fn::ForEach to generate multiple resources from a single definition. SAM CLI commands including sam build, sam local invoke, sam sync, sam local start-api, and sam validate will automatically expand your loops and process each generated resource. You can invoke expanded functions by name, for example sam local invoke AlphaFunction. SAM CLI also supports Fn::Length, Fn::ToJsonString, Fn::FindInMap with DefaultValue, and conditional DeletionPolicy and UpdateReplacePolicy attributes.
To learn more, visit the SAM CLI developer guide and launch blog post.
Quelle: aws.amazon.com

Amazon EVS enables support for 32 hosts per environment

Today, we are announcing that Amazon Elastic VMware Service (Amazon EVS) now supports up to 32 ESXi hosts per environment, double the previous limit of 16 hosts.
Amazon EVS gives you flexibility in how you configure VMware Cloud Foundation (VCF) domains and clusters within an environment. You can put all your hosts into a single large cluster, spread them across several smaller clusters, or any combination that fits your needs. With this release, you can now submit a service quota increase to scale up to a total of 32 hosts and reduce the operational overhead of managing multiple environments.
This latest release is available in all regions where Amazon EVS is offered.
For more details on the steps and procedure, visit the Amazon EVS product detail page and user guide.
Quelle: aws.amazon.com

AWS Partner Central agents now accelerates opportunity creation

Today, AWS announces that the AWS Partner Central agents now accelerate opportunity creation through natural language conversation. AWS Partner Central agents, released on March 16, 2026, are AI-powered capabilities built on Amazon Bedrock AgentCore that help partners surface pipeline insights, advance deals with next-step recommendations, and identify funding opportunities. With this update, partners create opportunities through a short conversation instead of completing a multi-step form, so partner sales teams spend less time on data entry and more time selling. Partners describe a deal in natural language, upload meeting notes, proposals, or call transcripts (PDF, DOCX, Excel, TXT), or clone an existing opportunity. The agent extracts the information, enriches customer details, and recommends improvements — such as adding missing context, correcting field values, or strengthening the business problem statement — so partners submit higher-quality opportunities, improve pipeline hygiene, and shorten sales cycles. Partners use the feature in the AWS Console through Amazon Q chat, and programmatically through Model Context Protocol (MCP), so sales teams create opportunities from their existing tools. AWS Partner Central agents are available in all commercial AWS Regions. To learn more about agentic capabilities in AWS Partner Central, review this blog. Partners can start using agents by visiting AWS Partner Central in the AWS console and accessing opportunities, after reviewing the agents guide, and to integrate agents into your existing tools, visit the Partner Central agents MCP server guide.
Quelle: aws.amazon.com

Amazon EMR Serverless is now available in additional AWS Regions

Amazon EMR Serverless is now generally available in six additional AWS Regions – Asia Pacific (Hyderabad), Asia Pacific (Malaysia), Asia Pacific (New Zealand), Asia Pacific (Taipei), Asia Pacific (Thailand), and Mexico (Central). Amazon EMR Serverless is a deployment option in Amazon EMR that makes it simple and cost effective for data engineers and analysts to run petabyte-scale data analytics in the cloud. With EMR Serverless, you can run your Apache Spark and Apache Hive applications without having to configure, optimize, tune, or manage clusters. EMR Serverless offers fine-grained automatic scaling, fast launch times, customizable worker configurations, and support for batch, interactive and streaming workloads. To get started, visit the Amazon EMR Serverless User Guide. For pricing info, visit the EMR Serverless pricing page.
Quelle: aws.amazon.com

Amazon CloudWatch Logs announces increased query result limits

Amazon CloudWatch Logs now supports retrieving up to 100,000 results using the Logs Insights query language. Customers can specify the limit in their query using the LIMIT command. Previously, customers were limited to 10,000 results and had to split their queries into smaller time ranges to retrieve all results. With this launch, customers can view a larger set of results and use existing features such as patterns, visualization, and export on the full 100,000 result set. The GetQueryResults API has also been updated to support pagination; each invocation can return up to 10,000 results along with a token that can be used to fetch the next set of results. The increased query result limits are available in all commercial AWS regions. You can execute queries and view up to 100,000 results using the Amazon CloudWatch console, AWS CLI, AWS CDK, and AWS SDKs. To learn more, see the Amazon CloudWatch Logs documentation.
Quelle: aws.amazon.com

AWS Organizations now supports higher quotas for service control policies (SCPs)

AWS Organizations now supports higher quotas for service control policies (SCPs). The maximum number of SCPs that can be attached to a single node (root, OU, or account) has increased from 5 to 10, and the maximum SCP size has increased from 5,120 to 10,240 characters.
With these higher quotas, you can write SCPs with finer-grained permissions and conditions, and attach more SCPs per node to build more comprehensive security controls across your organization.
These higher quotas are available in all commercial AWS Regions, the AWS GovCloud (US) Regions, and the China Regions, and are available automatically to all organizations with no action required. To learn more, see quotas for AWS Organizations in the AWS Organizations User Guide.
Quelle: aws.amazon.com

AWS announces AWS Interconnect – multicloud connectivity with Oracle Cloud Infrastructure in preview

AWS announces the public preview of AWS Interconnect — multicloud with Oracle Cloud Infrastructure (OCI).
Customers have been adopting multicloud strategies while migrating more applications to the cloud. They do so for many reasons including interoperability requirements, the freedom to choose technology that best suits their needs, and the ability to build and deploy applications on any environment with greater ease and speed. Previously, when interconnecting workloads across multiple cloud service providers (CSPs), customers had to go the route of a ‘do-it-yourself’ multicloud approach, leading to complexities of building and managing global multi-layered networks at scale. AWS Interconnect – multicloud is the first purpose-built product of its kind and a new way of how clouds connect and talk to each other, allowing customers to quickly provision resilient, scalable private connections to other cloud providers.
OCI is the latest CSP to adopt the open specification that powers AWS Interconnect. This allows AWS to provide a consistent, simple experience to our customers on OCI (preview), Google Cloud (Generally Available), and Microsoft Azure (coming later in 2026).
Interconnect – multicloud is available in preview with OCI in the us-east-1 (N. Virginia) AWS Region. You can create a preview Interconnect using the AWS Management Console, Command Line Interface (CLI), or API. For more information, see the AWS Interconnect – multicloud documentation.
Quelle: aws.amazon.com