Amazon AWS News, Entwicklungen, Updates, HowTos - Seite 9 von 786

Today, Amazon Elastic Kubernetes Service (Amazon EKS) announced certificate authority (CA) rotation, enabling customers to rotate their cluster’s CA through a managed lifecycle with automated safeguards. Each Amazon EKS cluster has its own CA that allows encrypted connections to the cluster’s Kubernetes API, and now you can rotate the CA before it expires to ensure your cluster remains operational and secure.
Amazon EKS clusters created since launch in 2018 have CAs with a 10-year validity period, and clusters from that era are now approaching the point where CA rotation activities should begin. CA rotation in Amazon EKS is a shared responsibility. Amazon EKS manages the rotation lifecycle and automatically updates AWS-managed components to trust the successor CA. Customers are responsible for replacing their worker nodes and updating external clients to trust the successor CA before it is activated. EKS Auto Mode instances and AWS Fargate nodes are updated automatically by AWS, but customers are still responsible for updating any external clients that connect to the cluster’s API server. Amazon EKS provides automated safeguards to support customers through this process, including advance notifications before CA expiration, automatic appending of a successor CA if one is not created by the customer, and automatic activation if the customer does not activate on their own schedule. A rollback capability allows customers to revert to the previous CA to resolve any issues that may arise with their updates during the transition to the successor CA.
Amazon EKS CA rotation is available at no additional cost in all commercial AWS Regions. To get started with CA rotation, you can use the AWS CLI, EKS APIs, CloudFormation, and the AWS console. For more information, see the Amazon EKS documentation and Deep dive into Amazon EKS certificate authority rotation.
Quelle: aws.amazon.com

21. August 2026

da Agency

AWS Marketplace now supports category-based notifications and multi-channel delivery for partners

AWS partners can now configure category-based notifications and multi-channel delivery for AWS Marketplace notifications through AWS User Notifications. Previously, partners received their AWS Marketplace notifications through their AWS account’s root email address or custom email aliases, with no way to select notification categories or route each category to the teams responsible for managing it. With this launch, partners can choose which contacts receive each notification category and how those notifications are delivered.
Four notification categories are available. Product listings notifications cover open product tasks, recurring scan findings for AMI and container products, and Vendor Insights security profile snapshots for SaaS products. Offers and agreements notifications cover private offers, reseller activity, professional services requests, agreement starts and cancellations, cancellation requests, and agreement creation failures. Payments and disbursements notifications cover payment requests, billing adjustments, invoice submission outcomes, payment failures, and disbursement issues. Account management notifications cover business and bank account verification actions, approvals, expirations, and rejections.
By default, notifications are delivered by email to the AWS account’s root email address. Partners can add recipients through additional email addresses and distribution lists. Partners can also receive notifications through the AWS Console Mobile Application or Amazon Q Developer in chat applications such as Slack and Microsoft Teams. After enabling managed notifications, partners can select the contacts and delivery channels that receive each category.
AWS Marketplace category-based notifications are available in all AWS Commercial Regions where AWS Marketplace is available. To learn more, see Managing email notifications for AWS Marketplace events in the AWS Marketplace documentation. To enable managed notifications, visit the AWS User Notifications console.
Quelle: aws.amazon.com

21. August 2026

da Agency

AWS Direct Connect introduces inbound prefix controls and higher prefix scale

Today, AWS Direct Connect announced inbound prefix controls, a new capability that lets you allocate and manage inbound route-prefix allocations for your private and transit virtual interfaces (VIFs) based on your workload’s needs. You can now allocate up to 1,000 prefixes each for IPv4 and IPv6 on your VIFs on dedicated and hosted connections.
Previously, Direct Connect VIFs accepted a maximum of 100 route prefixes advertised from your on-premises network to AWS on a private or transit VIF. If you had a larger or growing network, you had to architect around this ceiling, for example, by summarizing routes or segmenting across multiple VIFs or connections. With inbound prefix controls, you can allocate up to 1,000 prefixes to a single VIF and advertise your routes directly.
Inbound prefix controls introduce new prefix capacity pools at the dedicated connection level and at the Direct Connect gateway (DXGW) level. When you create or update a VIF, you allocate a specific number of prefixes to it, and that allocation draws from the dedicated connection’s pool and the DXGW’s pool when you attach it. This lets you right-size prefix capacity per workload—for example, a large allocation for a transit VIF carrying many routes and a smaller allocation for a private VIF on the same connection. Connection pool sizes scale with connection speed, and link aggregation group (LAG) pools scale with the number of member connections.
You can configure prefix allocations using the AWS Direct Connect console or CLI/API. Inbound prefix controls are available at no additional cost in all commercial AWS Regions where AWS Direct Connect is available, AWS GovCloud Regions (US-East and US-West), as well as the Amazon Web Services China (Beijing) Region, operated by Sinnet, and the Amazon Web Services China (Ningxia) Region, operated by NWCD.
To learn more, see Inbound prefix controls for AWS Direct Connect in the AWS Direct Connect User Guide.
Quelle: aws.amazon.com

21. August 2026

da Agency

Generative AI Inference Recommendation for Amazon SageMaker now available in the SageMaker AI Studio

Amazon SageMaker AI now offers Generative AI Inference Recommendations in SageMaker AI Studio, giving customers a guided, low-code, no-code path to find the best inference configuration for their workload. This builds on the API-based launch in April 2026, extending the same benchmarking infrastructure to teams that prefer a visual workflow over programmatic access.
Deploying generative AI models in production requires finding the right combination of instance type, serving container, and optimization strategy. Getting this right typically involves weeks of manual benchmarking, configuration tuning, and trial-and-error, with no easy way to know if the final setup is actually optimal. With the new experience, customers describe their workload and what matters most, whether that’s latency, throughput, or cost, and SageMaker AI does the rest. It benchmarks multiple configurations on real GPU infrastructure using NVIDIA AIPerf, applies goal-aligned techniques like speculative decoding for throughput or kernel tuning for latency, and returns ranked, production-ready recommendations with measured performance data. Teams get to a validated configuration in hours instead of weeks, without needing to decide which techniques to apply or how to configure them.
With the new experience, customers describe their workload and what matters most, whether that’s latency, throughput, or cost, and SageMaker AI does the rest. It benchmarks multiple configurations on real GPU infrastructure using NVIDIA AIPerf, applies goal-aligned techniques like speculative decoding for throughput or kernel tuning for latency, and returns ranked, production-ready recommendations with measured performance data. Teams get to a validated configuration in hours instead of weeks, without needing to decide which techniques to apply or how to configure them.
In SageMaker AI Studio under Jobs, Inference optimization, customers select a use-case profile (Interact, Generate, Summarize, or Custom), choose an optimization goal (minimize latency, maximize throughput, or minimize cost), and pick their model from JumpStart, S3, Model Registry, or an existing SageMaker model. Recommendations are ranked by TTFT, inter-token latency, throughput, and cost, and can be compared visually before deploying to a SageMaker real-time endpoint directly from Studio.
There is no additional cost for generating recommendations. Standard compute costs apply for optimization jobs and endpoints provisioned during benchmarking. This capability is available in US East (N. Virginia), US West (Oregon), US East (Ohio), Europe (Ireland), Europe (Frankfurt), Asia Pacific (Singapore), Asia Pacific (Tokyo). To learn more, visit the blog post or the documentation.
Quelle: aws.amazon.com