Kategorie: Amazon AWS

Amazon SageMaker adds serverless workflows to Identity Center domains

Amazon SageMaker Unified Studio now supports Serverless Workflows in Identity Center domains.  With this launch, customers using Identity Center domains can orchestrate data processing tasks with Apache Airflow (powered by Managed Workflows for Apache Airflow) without provisioning or managing Airflow infrastructure. Serverless Workflows were previously available only in IAM-based domains. 
Serverless Workflows automatically provision compute resources when a workflow runs and release them when it completes, so you only pay for actual workflow run time. Each workflow runs with its own execution role and isolated worker, providing workflow-level security and preventing cross-workflow interference. With Serverless Workflows, Identity Center domain customers also get access to the Visual Workflow experience with support for around 200 operators, including built-in integration with AWS services such as Amazon S3, Amazon Redshift, Amazon EMR, AWS Glue, and Amazon SageMaker AI.
Serverless Workflows in Identity Center domains are available in all AWS Regions where SageMaker Unified Studio is supported. To learn more, visit the Serverless Workflows documentation.
Quelle: aws.amazon.com

AWS Lambda expands response streaming support to all commercial AWS Regions

AWS Lambda response streaming is now available in all commercial AWS Regions, bringing full regional parity for this capability. Customers in newly supported Regions can use the InvokeWithResponseStream API to progressively stream response payloads back to clients as data becomes available.
Response streaming enables functions to send partial responses to clients incrementally rather than buffering the entire response before transmission. This reduces time-to-first-byte (TTFB) latency and is well suited for latency-sensitive workloads such as LLM-based applications as well as web and mobile applications where users benefit from seeing responses appear incrementally. Response streaming supports payloads up to a default maximum of 200 MB.
With this expansion, customers in all commercial Regions can stream responses using the InvokeWithResponseStream API through a supported AWS SDK, or through Amazon API Gateway REST APIs with response streaming enabled. Response streaming supports Node.js managed runtimes as well as custom runtimes.
Streaming responses incur an additional cost for network transfer of the response payload. You are billed based on the number of bytes generated and streamed out of your Lambda function over the first 6 MB. To get started with Lambda response streaming, visit the AWS Lambda documentation. 
Quelle: aws.amazon.com

AWS Certificate Manager now supports native certificate search

AWS Certificate Manager (ACM) now provides a search bar in the console that customers can use to find certificates using one or more certificate parameters such as domain name, certificate ARN, and/or certificate validity. For example, ACM users who manages multiple certificates can search for certificates with specific domains that are due to expire soon. To get started, use the new SearchCertificates API, or navigate to the ACM console and use the search bar to search by one or more certificate parameters. This feature is available in all Public AWS, AWS China, and AWS GovCloud regions. To learn more about this feature, please refer to Search Certificates. You can learn more about ACM and get started here.
Quelle: aws.amazon.com

Announcing Amazon S3 Files, making S3 buckets accessible as file systems

S3 Files delivers a shared file system that connects any AWS compute resource directly with your data in Amazon S3. With S3 Files, Amazon S3 is the first and only cloud object store that provides fully-featured, high-performance file system access to your data. It provides full file system semantics and low-latency performance, without your data ever leaving S3. That means file-based applications, agents, and teams can now access and work with your S3 data as a file system using the tools they already depend on. Built using Amazon EFS, S3 Files gives you the performance and simplicity of a file system with the scalability, durability, and cost-effectiveness of S3. You no longer need to duplicate your data or cycle it between object storage and file system storage. S3 Files maintains a view of the objects in your bucket and intelligently translates your file system operations into efficient S3 requests on your behalf. Your file-based applications run on your S3 data with no code changes, AI agents persist memory and share state across pipelines, and ML teams run data preparation workloads without duplicating or staging files first. Now, file-based tools and applications across your organization can work with your S3 data directly from any compute instance, container, and function using the tools your teams and agents already depend on.    Organizations store their analytics data and data lakes in S3, but file-based tools, agents, and applications have never been able to directly work with that data. Bridging that gap meant managing a separate file system, duplicating data, and building complex pipelines to keep object and file storage in sync. S3 Files eliminates that friction and overhead. Using S3 Files, your data is accessible through the file system and directly through S3 APIs at the same time. Thousands of compute resources can connect to the same S3 file system simultaneously, enabling shared access across clusters without duplicating data. S3 Files works with all of your new and existing data in S3 buckets, with no migration required.    S3 Files caches actively used data for low-latency access and provides up to multiple terabytes per second of aggregate read throughput, so storage never limits performance. There are no data silos, no synchronization complexities, and no tradeoffs. File and object storage, together in one place without compromise.
S3 Files is now generally available in 34 AWS Regions. For the full list of supported Regions, visit the AWS Capabilities tool. To learn more, visit the product page, S3 pricing page, documentation, and AWS News Blog.
Quelle: aws.amazon.com

Amazon Lightsail is now available in the Asia Pacific (Malaysia) Region

Starting today, Amazon Lightsail is available in the Asia Pacific (Malaysia) Region. This expansion brings the power and simplicity of Lightsail to customers in Malaysia and surrounding regions. With this launch, customers in Malaysia and nearby countries can now enjoy lower latency and better performance for their applications while meeting local data residency requirements. The new Region provides access to Lightsail’s full range of features including instances that meet your compute needs—from general purpose to compute-optimized and memory-optimized bundles—as well as managed databases, containers, load balancers and more, all with the same simple, predictable pricing that Lightsail customers love. Lightsail is available in these AWS Regions: US East (Ohio, N. Virginia), US West (Oregon), Canada (Central), Europe (Frankfurt, Ireland, London, Paris, Stockholm), Asia Pacific (Malaysia, Jakarta, Mumbai, Seoul, Singapore, Sydney, Tokyo). To learn more about Regions and Availability Zones for Lightsail, please refer to the documentation. You can use this Region through the Lightsail Console, AWS Command Line Interface (CLI) and AWS SDKs.
Quelle: aws.amazon.com

AWS Cost Explorer launches Natural Language Query capabilities powered by Amazon Q

AWS Cost Explorer now brings Amazon Q Developer’s generative AI capabilities directly into your cost analysis workflows. You can now use natural language queries to ask Amazon Q questions about your AWS cost and usage data. In addition to providing answers to your question, you now also receive automatically updated visualizations in Cost Explorer. This enables faster cost analysis, reduces time to insights, and makes cost visibility accessible to every team member.
With this launch, you can start your cost analysis with the new suggested prompts in Cost Explorer. These prompts include commonly asked cost questions like “Show me my top spending services for this month.” Amazon Q provides detailed insights while Cost Explorer simultaneously updates with the corresponding visualization, filters, and groupings. You can also ask custom questions in your own words using the new ‘Ask Question’ button, exploring your spending patterns conversationally. Cost Explorer automatically updates charts and tables when analysis is based on your cost and usage data. When Amazon Q compiles insights from additional datasets such as pricing or anomaly detection, visualizations are displayed in Amazon Q’s new artifacts panel. You can continue the conversation with follow-up questions while maintaining full context, allowing you to go from a quick cost check to a deep investigation without switching tools or breaking your workflow.
Natural language cost analysis for AWS Cost Explorer is available today in all commercial AWS Regions at no additional charge. To learn more, visit AWS Cost Explorer. To get started, see the user guide.
Quelle: aws.amazon.com

Amazon SageMaker Unified Studio adds notebook import/export and developer acceleration features

Amazon SageMaker Unified Studio notebooks now support import/export capabilities, enabling migration from JupyterLab and other notebook platforms. This release also introduces developer acceleration features including cell reordering, keyboard shortcuts, cell renaming, and multi-line SQL support, designed to enhance productivity for data engineers and data scientists professionals working with notebook-based workflows.
The new import/export functionality supports .ipynb, .json, and .py formats while preserving cell types and metadata, making platform migration straightforward. You can export notebooks in four formats including Jupyter notebook with requirements (.zip), standard .ipynb, Python scripts (.py), and SageMaker Unified Studio native format (.json). Developer acceleration features enable you to reorder cells without copy-paste duplication, assign custom names to cells for improved navigation in large notebooks, use familiar keyboard shortcuts for faster development, and execute multiple SQL statements in a single cell with results displayed in separate tabs for easy comparison and analysis.
This feature is available in all AWS Regions where Amazon SageMaker Unified Studio is available. To learn more, visit the Amazon SageMaker Unified Studio marketing page and user guide. 
Quelle: aws.amazon.com

AWS Cost Explorer launches Natural Language Query capabilities powered by Amazon Q

AWS Cost Explorer now brings Amazon Q Developer’s generative AI capabilities directly into your cost analysis workflows. You can now use natural language queries to ask Amazon Q questions about your AWS cost and usage data. In addition to providing answers to your question, you now also receive automatically updated visualizations in Cost Explorer. This enables faster cost analysis, reduces time to insights, and makes cost visibility accessible to every team member.
With this launch, you can start your cost analysis with the new suggested prompts in Cost Explorer. These prompts include commonly asked cost questions like “Show me my top spending services for this month.” Amazon Q provides detailed insights while Cost Explorer simultaneously updates with the corresponding visualization, filters, and groupings. You can also ask custom questions in your own words using the new ‘Ask Question’ button, exploring your spending patterns conversationally. Cost Explorer automatically updates charts and tables when analysis is based on your cost and usage data. When Amazon Q compiles insights from additional datasets such as pricing or anomaly detection, visualizations are displayed in Amazon Q’s new artifacts panel. You can continue the conversation with follow-up questions while maintaining full context, allowing you to go from a quick cost check to a deep investigation without switching tools or breaking your workflow.
Natural language cost analysis for AWS Cost Explorer is available today in all commercial AWS Regions at no additional charge. To learn more, visit AWS Cost Explorer. To get started, see the user guide.
Quelle: aws.amazon.com

Amazon FSx for OpenZFS is now available in the AWS Asia Pacific (Melbourne) Region

Customers can now create Amazon FSx for OpenZFS file systems in the AWS Asia Pacific (Melbourne) Region, providing fully managed shared file storage built on the OpenZFS file system. Amazon FSx makes it easier and more cost effective to launch, run, and scale feature-rich, high-performance file systems in the cloud. It supports a wide range of workloads with its reliability, security, scalability, and broad set of capabilities. Amazon FSx for OpenZFS provides fully managed, cost-effective, shared file storage powered by the popular OpenZFS file system, and is designed to deliver sub-millisecond latencies and multi-GB/s throughput along with rich ZFS-powered data management capabilities (like snapshots, data cloning, and compression). To learn more about Amazon FSx for OpenZFS, visit our product page, and see the AWS Region Table for complete regional availability information.
Quelle: aws.amazon.com

AWS announces general availability of Smithy-Java client framework

AWS today announced the general availability of Smithy-Java, an open-source Java framework for generating type-safe clients and standalone classes from Smithy models. Smithy-Java addresses one of the most consistently requested capabilities from enterprise Smithy users: production-grade Java SDK generation. The framework allows you to generate clients from models and async patterns that increase cognitive load and maintenance burden for developers building modern Java applications.
Built on Java 21’s virtual threads, Smithy-Java provides a blocking-style API that is both simpler to use and competitive in performance with complex async alternatives. Key benefits include auto-generated type-safe clients from Smithy, protocol flexibility with runtime protocol swapping for gradual migration paths. The GA release includes the Java client code generator, support for AWS SigV4 and all major AWS protocols (AWS JSON, REST-JSON, REST-XML, AWS Query, and Smithy RPCv2-CBOR), standalone type code generation for sharing types across multiple services or data modeling, and a dynamic client that can call Smithy services without a codegen step.
The framework pioneers two architectural innovations: schema-driven serialization that reduces SDK size while improving performance, and binary decision diagrams (BDD) for endpoint rules resolution delivering significant latency improvements. Internal Amazon teams have already built complete services in weeks rather than months using Smithy-Java, with service teams depending on it internally. The framework is ideal for organizations invested in the Smithy ecosystem, teams requiring protocol-agnostic development, and developers building new services with generated server stubs.
To learn more, visit our blog post and follow the Smithy Java Quickstart guide.
Quelle: aws.amazon.com