Tag: SysAdmin

Amazon SageMaker HyperPod now supports G7e and r5d.16xlarge instances. SageMaker HyperPod is a purpose-built infrastructure for developing, training, and deploying foundation models at scale. It provides a resilient and performant environment with built-in fault tolerance, automated cluster recovery, and optimized distributed training libraries, reducing the undifferentiated heavy lifting of managing large-scale AI/ML infrastructure.  G7e instances are powered by NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs and deliver up to 2.3x better inference performance than G6e instances, allowing you to process more requests per second while reducing latency. With up to 768 GB of total GPU memory, G7e instances let you deploy larger language models or run multiple models on a single endpoint. You can use these instances for deploying LLMs, agentic AI, multimodal generative AI, and physical AI models

AWS announces availability of new Linux bundles for Amazon WorkSpaces Personal, including Rocky Linux 9, Red Hat Enterprise Linux 9, and Ubuntu 24.04. With these bundles, customers can launch WorkSpaces powered by the latest enterprise-grade Linux operating systems and take advantage of modern versions of Linux packages only available in these updated releases. While Rocky Linux 8, Red Hat Enterprise Linux 8, and Ubuntu 22.04 powered WorkSpaces bundles remain available, the new OS options bring access to the latest software ecosystems, improved security postures, and extended long-term support lifecycles offered by each respective distribution. These new bundles also provide a migration path for Amazon Linux 2 customers ahead of its end of life in June 2026. You can get started using managed Rocky Linux 9, Red Hat Enterprise Linux 9, or Ubuntu 24.04 WorkSpaces bundles by selecting one when creating a new Linux WorkSpace. These new bundles are available in all AWS R

AWS Lambda now supports Provisioned Mode for event source mappings (ESMs) that subscribe to Apache Kafka event sources in the Asia Pacific (Taipei), AWS GovCloud (US-East), and AWS GovCloud (US-West) Regions. Provisioned Mode allows you to optimize the throughput of your Kafka ESM by provisioning event polling resources that remain ready to handle sudden spikes in traffic, helping you build highly responsive and scalable event-driven Kafka applications with stringent performance requirements. Customers building streaming data applications often use Kafka as an event source for Lambda functions, relying on Lambda's fully managed ESM to automatically scale polling resources in response to events. However, for event-driven Kafka applications that need to handle unpredictable bursts of traffic, lack of control over the throughput of ESM can lead to delays in your users' experience. Provisioned Mode for Kafka ESM enables customers to fine-tune the throughput of their Amazon Manag

Amazon Quick now integrates with Vee, the AI assistant from Visier's people analytics platform, through the model context protocol (MCP). HR business partners, finance managers, and operations leaders can now get governed access to live workforce intelligence from Visier directly within their Amazon Quick workspace without switching tools. After setting up the connection in Quick using Visier’s remote MCP server, you can ask questions in natural language about headcount, attrition, tenure, and open requisitions and receive answers grounded in Visier's governed workforce data model. Vee can also be invoked from automated Quick Flows to run recurring workforce reviews or draft documents. Quick intelligently routes relevant prompts to Vee and returns contextualized answers alongside enterprise knowledge – such as budgets, policies, and plans stored in Quick Spaces – so every answer reflects the full organizational picture. The Visier integration with Amazon Quick

Amazon Bedrock AgentCore Gateway and Identity now provide secure and controlled egress traffic management for your applications, enabling seamless communication with resources in your Virtual Private Cloud (VPC). VPC egress for AgentCore Gateway targets and Identity credential providers are offered in both managed and self-managed configurations. With VPC egress support, customers can now invoke private resources (e.g., EKS-hosted MCP servers) directly from their AgentCore Gateway. Managed VPC egress covers most customer use cases. For more complex networking setups, customers can configure their own VPC Lattice resources. AgentCore Identity VPC egress supports connectivity to Identity Providers (IdPs) running inside a customer’s VPC. This enables two key capabilities: validating inbound access tokens issued by your private IdP and fetching tokens from your IdP for outbound request authentication. Finally, this launch supports private DNS resolution for managed VPC egress

Amazon Connect now provides eight new metrics to measure and improve AI agent performance, including goal success rate, faithfulness score, and tool selection accuracy. These metrics offer visibility into the quality of AI-driven customer interactions, enabling measurement and continuous improvement of AI agent outcomes. With this launch, you can monitor whether AI agents successfully resolved customer requests, assess faithfulness and detect contextual hallucinations. You can also evaluate tool selection and utilization accuracy, and capture customer feedback through thumbs up/down ratings when enabled.  You can access these new metrics through Amazon Connect's AI Agent Performance dashboard, or through the GetMetricDataV2 API and zero-ETL data lake for custom reporting or integration with your existing analytics workflows. This feature is available in all AWS Regions where Amazon Connect AI Agents is supported. For more information, see the 

Amazon EC2 High Memory U7i-8TB instances (u7i-8tb.112xlarge) are now available in AWS Europe (Stockholm, Zurich) regions, U7in-16TB instances (u7in-16tb.224xlarge) are now available in the AWS US East (Ohio) region, and U7in-24TB instances (u7in-24tb.224xlarge) are now available in the AWS Europe (Stockholm) region. U7i instances are part of the AWS 7th generation and are powered by custom fourth-generation Intel Xeon Scalable processors (Sapphire Rapids). U7i-8TB instances offer 8 TiB of DDR5 memory, U7in-16TB instances offer 16 TiB of DDR5 memory, and U7in-24TB instances offer 24 TiB of DDR5 memory, enabling customers to scale transaction processing throughput in a fast-growing data environment. U7i-8TB instances deliver 448 vCPUs and support up to 100 Gbps of Amazon EBS bandwidth, 100 Gbps of network bandwidth, and ENA Express. Both U7in-16TB and U7in-24TB instances deliver 896 vCPUs and support up to 100 Gbps of Amazon EBS bandwidth for faster data loading and backups, 2

AWS Marketplace sellers can now delete bank accounts directly from the Payment Settings page in the AWS Marketplace Management Portal (AMMP). This new self-service capability addresses a long-standing gap in payment account management, allowing sellers to remove ACH-type and SWIFT-type bank accounts without contacting customer service. This enhancement is particularly valuable for global enterprises and ISVs managing multiple currencies and banking relationships. With this update, sellers gain complete control over their payment account management. Key benefits include the ability to clean up unused accounts, remove failed or outdated banking relationships, and reduce payment routing risks. The feature also includes Last Updated timestamps to help differentiate between modified bank accounts.  To learn more, see the AWS Marketplace Seller Guide.

AWS Deadline Cloud now supports running custom scripts before and after job submission, giving studios the ability to integrate their pipeline directly into the submission workflow. AWS Deadline Cloud is a fully managed service that simplifies render management for teams creating computer-generated graphics and visual effects for films, television, web content, and design. With the new submission scripting capability, you can configure scripts that run automatically as part of every job submission. Pre-submission scripts run before job attachments are uploaded, allowing you to validate job configurations, discover and add additional input files such as textures or caches, modify submission parameters, or enforce studio policies. Post-submission scripts run after the job is created, enabling you to send notifications, update tracking systems, or log submission details. Scripts are defined in a simple YAML or JSON configuration file placed in your job bundle directory or in a

Amazon Athena now offers managed connectors for 12 data sources, including Amazon DynamoDB, PostgreSQL, MySQL, and Snowflake. Managed connectors are AWS Glue Data Catalog federated connectors that Athena creates and manages on your behalf, so you can query data outside Amazon S3 without deploying or maintaining connector resources in your AWS account. With Athena, you can interactively query relational, non-relational, object, and custom data sources without moving or duplicating data. To get started with managed connectors, you create a connection for your data source in Athena. Athena automatically sets up and manages connector resources on your behalf, registering the data source as a federated catalog in AWS Glue Data Catalog. You can then query the data source alongside your Amazon S3 data and optionally set up fine-grained access controls through AWS Lake Formation. Federated queries with managed connectors are avai