Kategorie: Amazon AWS

SageMaker Unified Studio automates Glue connector provisioning for cross-subnet job retries

Amazon SageMaker Unified Studio now supports automatic creation of connections for Glue job retries across subnets to improve data pipeline resilience. This helps organizations running business-critical data pipelines reduce unplanned downtime and meet their SLAs — without requiring engineers to manually configure backup connectors or intervene during subnet failures.
With this launch, SageMaker Unified Studio automates the provisioning of Glue connectors across subnets defined in the domain VPC configuration. Administrators can define their domain VPC with multiple private subnets across availability zones, and the system provisions the connectors needed for all new projects so that failed jobs can be retried on an alternate subnet automatically. If a Glue job fails because the primary subnet is unavailable due to IP address exhaustion or availability zone degradation, the job can be retried on a connector in a different subnet. No user action is needed beyond the initial VPC configuration on the domain.
This feature is available in all AWS Regions where Amazon SageMaker Unified Studio is available. To learn more, visit the Amazon SageMaker Unified Studio documentation. 
Quelle: aws.amazon.com

Amazon EC2 C7i-flex, M7i-flex & M7i instances now available in Asia Pacific (Hyderabad) region

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C7i-flex, M7i-flex and M7i instances powered by custom 4th Gen Intel Xeon Scalable processors (code-named Sapphire Rapids) are available in Asia Pacific (Hyderabad) region. These custom processors, available only on AWS, offer up to 15% better performance over comparable x86-based Intel processors utilized by other cloud providers. C7i-flex and M7i-flex instances are the easiest way for you to get price-performance benefits for a majority of general-purpose workloads. They deliver up to 19% better price-performance compared to C6i and M6i  instances respectively. These instances offer the most common sizes, from large to 16xlarge, and are a great first choice for applications that don’t fully utilize all compute resources such as web and application servers, virtual-desktops, batch-processing, and microservices. 
 
M7i deliver up to 15% better price-performance compared to M6i. M7i instances are a great choice for workloads that need the largest instance sizes or continuous high CPU usage, such as gaming servers, CPU-based machine learning (ML), and video-streaming. M7i offer larger instance sizes, up to 48xlarge, and two bare metal sizes (metal-24xl, metal-48xl). These bare-metal sizes support built-in Intel accelerators: Data Streaming Accelerator, In-Memory Analytics Accelerator, and QuickAssist Technology that are used to facilitate efficient offload and acceleration of data operations and optimize performance for workloads. To learn more, visit the EC2  C7i-flex and M7i/M7i-flex instances pages.
Quelle: aws.amazon.com

Amazon CloudWatch Logs Insights adds new query commands and functions

Amazon CloudWatch Logs Insights query language now supports 13 new commands and functions that give you more powerful ways to query, transform, and analyze your logs. Customers analyzing logs in CloudWatch Logs Insights often need to perform string manipulation, encode or decode field values, parse non-JSON log formats, or calculate geographic distances, so they can derive deeper insights from their logs. With this launch, CloudWatch Logs Insights provides new string and numeric functions (round, startswith, endswith, case, regex_replace, haversine), encoding and decoding functions (urlencode, urldecode, base64encode, base64decode), and new parse and analysis commands (parse logfmt, expand, relevantfields). You can now filter logs by string prefixes, decode Base64 payloads inline, parse logfmt structured logs into fields, expand nested JSON arrays into individual records, calculate distances between coordinates, and automatically surface relevant fields in high-cardinality log groups. These commands and functions are available today in all commercial AWS Regions. To learn more, see the Amazon CloudWatch Logs documentation.
Quelle: aws.amazon.com

Amazon Bedrock expands support for request-level usage attribution

Amazon Bedrock customers can now attribute model inference usage to specific teams, applications, environments, and experiments at the individual request level on the InvokeModel and InvokeModelWithResponseStream APIs. This gives customers fine-grained visibility into how their Amazon Bedrock usage is distributed across their organization, helping them understand consumption patterns, optimize spend, and report usage back to internal stakeholders without provisioning additional resources. This launch builds on Amazon Bedrock’s existing portfolio of usage attribution capabilities. Customers can already attribute model inference usage at the resource and identity level using application inference profiles, IAM principal-based attribution, project-level tracking on the OpenAI-compatible bedrock-mantle endpoint, and workspace-level tracking for Anthropic Claude models. For finer-grained, per-request attribution, the Converse and ConverseStream APIs have supported request-level metadata since launch. Today’s release brings the same capability to the InvokeModel and InvokeModelWithResponseStream APIs, giving customers a consistent way to tag inference calls across the entire bedrock-runtime endpoint. With this launch, customers can tag each Amazon Bedrock model inference call with attributes like team, project, or environment, and analyze usage by these tags in Amazon Bedrock model invocation logs. To get started, enable model invocation logging in the AWS Region where you call Amazon Bedrock, then add metadata to your inference requests. This feature is available in all AWS commercial Regions where Amazon Bedrock is available. To learn more, see Request metadata. 
Quelle: aws.amazon.com

Amazon RDS Custom now supports the latest GDR updates for Microsoft SQL Server

Amazon Relational Database Service (Amazon RDS) Custom for SQL Server now supports the latest General Distribution Release (GDR) updates for Microsoft SQL Server. This release includes support for SQL Server 2019 CU32+GDR KB5084816 (RDS version 15.00.4465.1.v1) and SQL Server 2022 CU24+GDR KB5083252 (RDS version 16.00.4250.1.v1). The GDR updates address vulnerabilities described in CVE-2026-32167 and CVE-2026-32176. For additional information on the improvements and fixes included in these updates, see Microsoft documentation for KB5084816, KB5083252. You can upgrade your Amazon RDS Custom for SQL Server instances to apply these recommended updates using Amazon RDS Management Console, or by using the AWS SDK or CLI. To learn more about upgrading your database instances, see Amazon RDS Custom User Guide.
Quelle: aws.amazon.com

Amazon Aurora MySQL 8.4 is now generally available

Amazon Aurora MySQL-Compatible Edition now supports MySQL 8.4, a community MySQL Long Term Support (LTS) major version. Aurora MySQL 8.4 launches with compatibility for community MySQL 8.4.7 and introduces aligned version numbering, so the version number you run on Aurora matches the community MySQL version it is compatible with. Aurora also manages the underlying patch on your behalf, simplifying day-to-day operations. Aurora MySQL now targets major versions within 12 months of community MySQL LTS releases, minor versions within 3 months of each community minor, and an Aurora LTS minor within 12 months of each major. For engine specific release objectives, see the Aurora and RDS open source release calendar announcement. Aurora MySQL 8.4 strengthens security defaults for new clusters. TLS is enforced by default with only TLS 1.2 and 1.3 supported, new accounts use the caching_sha2_password authentication plugin, and password validation policies are customizable through DB cluster parameter groups. Automated upgrade prechecks identify compatibility issues before your cluster goes offline, giving you confidence before you upgrade. To learn more about the Aurora MySQL 8.4 customer experience, refer to the Aurora MySQL 8.4 launch announcement blog. You can upgrade your database using Amazon RDS Blue/Green Deployments, in-place upgrade, or restore from a snapshot. Learn more about performing major version upgrades in the Amazon Aurora User Guide. You can also migrate to Aurora MySQL 8.4 from external MySQL sources using AWS Database Migration Service or Percona XtraBackup. Aurora MySQL 8.4 is available in all AWS Regions where Aurora MySQL is available. Amazon Aurora MySQL is designed for unparalleled high performance and availability at global scale with full MySQL compatibility. It provides scale-to-zero serverless compute, Aurora Global Database for Multi-Region resilience, Aurora I/O-Optimized for improved price performance on I/O-intensive workloads, and built-in security and continuous backups. To get started with Amazon Aurora, take a look at our getting started page.
Quelle: aws.amazon.com

Amazon SageMaker AI now supports OpenAI-compatible APIs for inference endpoints

Amazon SageMaker Inference now supports OpenAI-compatible APIs, so you can use the tools and frameworks you already know, like the OpenAI SDK, LangChain, and Strands Agents, to connect directly to your SageMaker endpoints. Switching requires nothing more than changing an endpoint URL — no custom integration code, no SDK wrappers, no rewrites. With this launch, you no longer need to adopt a different API format or change your authentication approach. Simply change your endpoint URL, and your existing SDK calls, streaming logic, and framework integrations continue to work as-is. You immediately gain the ability to choose your own GPU instances, keep data in your own VPC, run any open source or fine-tuned model, and scale with auto-scaling policies tuned to your workload. Authentication uses existing AWS credentials with automatic token refresh, so there is nothing extra to manage in production. This capability is available today in US East (N. Virginia), US West (Oregon), US East (Ohio), Asia Pacific (Mumbai), Asia Pacific (Jakarta), Europe (Ireland), Europe (Frankfurt), South America (São Paulo), Asia Pacific (Tokyo), Asia Pacific (Seoul), Europe (London), Asia Pacific (Singapore), Asia Pacific (Sydney), and Canada (Central). To learn more and get started, read the launch blog or visit the SageMaker Inference documentation.
Quelle: aws.amazon.com

ECS supports native integration with Amazon EBS volumes in GovCloud Regions

Amazon Elastic Container Service (ECS) now supports mounting Amazon Elastic Block Store (EBS) volumes to containers in the AWS GovCloud Regions. This capability makes it easier for you to deploy storage and data intensive applications such as ETL jobs, media transcoding, and ML inference workloads using serverless containers. With EBS task attachment, customers can allow ECS to provision, manage and de-provision EBS Volumes with each new ECS Task launch. EBS task attachment will automatically wire these volumes to their containerized workloads. Customers can have ECS format an empty volume on their behalf or bring an EBS snapshot for ECS to use to create new volumes. EBS task attachment is now available in the AWS GovCloud Regions for EC2, Fargate, and Managed Instances launch types. To learn more, see Use Amazon EBS volumes with Amazon ECS in the Amazon ECS Developer Guide.
Quelle: aws.amazon.com

AWS Security Hub now uncovers identity risks from unused access

Today, AWS Security Hub brings identity risk into the same unified console where central security teams already manage threats, exposures, and posture findings. Security Hub now detects unused IAM permissions, roles, and credentials across your AWS organization, helping central security teams identify and reduce identity risk at scale. Until now, managing identity risk across hundreds of accounts required toggling between multiple tools, with no unified view connecting unused permissions to actual resource exposure. Security Hub now surfaces these identity risks alongside threats, exposures, and posture findings in a unified console, enabling teams to prioritize remediation based on actual organizational risk. When you enable Security Hub for your organization, a service-linked IAM Access Analyzer is automatically created in each member account with no additional configuration required. Security Hub evaluates IAM principals against 90 days of actual access activity, detects unused access, and correlates identity findings with exposure context so teams can focus on the risks that matter most. Security Hub also provides on-demand generation of recommended least-privilege policies based on actual usage patterns, helping teams refine IAM permissions and reduce their attack surface. These capabilities represent a foundational step toward broader cloud infrastructure entitlement management in Security Hub, delivered with consistent workflows, automation rules, and downstream integrations. These capabilities are included with Security Hub Essentials at no additional cost. To learn more, see Understanding unused access findings in Security Hub in the AWS Security Hub User Guide and the AWS Security Hub product page. For the full list of AWS Regions where Security Hub is available, see the AWS Regional Services List.
Quelle: aws.amazon.com

Announcing the general availability of a new AWS Local Zone in Istanbul, Türkiye

Today, AWS announces the general availability of a new AWS Local Zone in Istanbul, Türkiye, bringing AWS infrastructure closer to end users, while enabling organizations to meet data residency requirements by storing and backing up data locally.
AWS Local Zones are AWS infrastructure deployments that extend core services, such as compute, storage, networking, and other select services, closer to metropolitan areas worldwide. AWS Local Zones help you achieve single-digit millisecond latency for end-user workloads, meet data residency requirements, support AI/ML inference workloads, and accelerate migration and modernization of legacy applications to the cloud, all while maintaining consistent AWS APIs, tools, and services as AWS Regions. AWS Local Zones are available in more than 30 metropolitan areas worldwide.
The AWS Local Zone in Istanbul supports Amazon Elastic Compute Cloud (Amazon EC2) with C7i, M7i, and R7i instances, Amazon S3 with the One Zone-Infrequent Access storage class, Amazon EBS with Local Snapshots and volume types gp3, gp2, io1, sc1, and st1, Amazon Elastic Container Service (Amazon ECS), Amazon Elastic Kubernetes Service (Amazon EKS), Amazon Virtual Private Cloud (Amazon VPC), AWS Direct Connect, and Application Load Balancer.  
To get started, enable the AWS Local Zone in Istanbul (eu-central-1-ist-1a) from the Zones tab in the Amazon EC2 console settings or by using the ModifyAvailabilityZoneGroup API. For pricing information, visit the AWS Local Zones pricing page. To learn more, visit the AWS Local Zones overview page. 
Quelle: aws.amazon.com