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Amazon SageMaker Unified Studio now lets data workers create and manage multiple code spaces (individually configured development environments) within a single project for IAM domains. Previously, projects were limited to one JupyterLab space and one Code Editor space embedded in the project. With this launch, you can now parallelly work on different workstreams or experiments with different compute and storage configuration needs, giving developers the flexibility they need as their workloads scale. For instance, data scientists can now work in parallel on any long running data transformation and model training workloads within the same project using separate spaces. With multiple spaces, each one maintains its own persistent Amazon EBS volume, ensuring that your files, data, and session state are preserved independently. You can scale compute and storage up or down

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C8i-flex instances are available in the Europe (Ireland, London), and Asia Pacific (New Zealand) regions. These instances are powered by custom Intel Xeon 6 processors, available only on AWS, delivering the highest performance and fastest memory bandwidth among comparable Intel processors in the cloud. C8i-flex instances offer up to 15% better price-performance, and 2.5x more memory bandwidth compared to previous generation Intel-based instances. They deliver up to 20% higher performance than C7i-flex instances, with even higher gains for specific workloads. The C8i-flex are up to 60% faster for NGINX web applications, up to 40% faster for AI deep learning recommendation models, and 35% faster for Memcached stores compared to C7i-flex. C8i-flex are the easiest way to get price performance benefits for a majority of compute intensive workloads like web and application servers, databases, caches, Apache Kafka, Elastics

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C8i instances are available in the Europe (Ireland) and Asia Pacific (New Zealand) regions. These instances are powered by custom Intel Xeon 6 processors, available only on AWS, delivering the highest performance and fastest memory bandwidth among comparable Intel processors in the cloud. C8i instances offer up to 15% better price-performance, and 2.5x more memory bandwidth compared to previous generation Intel-based instances. They deliver up to 20% higher performance than C7i instances, with even higher gains for specific workloads. The C8i instances deliver up to 60% faster for NGINX web applications, up to 40% faster for AI deep learning recommendation models, and 35% faster for Memcached stores compared to C7i. C8i instances are a great choice for all memory-intensive workloads, especially for workloads that need the largest instance sizes or continuous high CPU usage. C8i instances offer 13 sizes including 2 ba

AWS Network Firewall now supports expanded Managed Rules from AWS Marketplace partners, with new rule group optimizations through partners to include up to 10 million domain name indicators and up to 1 million IP addresses in their managed rule groups. Infoblox is expanding domain name indicators to protect your workloads from critical and high-risk domains. Lumen is introducing new rule groups to stop command and control attacks. ThreatSTOP is adding managed rules for Office of Foreign Assets Control (OFAC) sanctions and expanding global compliance protections with new European Union, Japan, and United Nations sanction coverage. These enhancements give you access to richer, more comprehensive threat intelligence directly within AWS Network Firewall, reducing the operational burden of managing threat feeds and enabling faster, more accurate protection against emerging threats. Whether you need to block malicious domains at scale, defend against command and control infrastru

Amazon EC2 now lets you control whether resources provisioned by managed instance offerings appear in your Amazon EC2 console views and API list operations. Amazon EC2 Managed Instances are instances provisioned and managed by a designated service provider, such as Amazon EKS, Amazon ECS, AWS Lambda or Amazon Workspaces. AWS is responsible for the configuration, patching, and health of managed EC2 instances as well as other associated resources like EBS volumes, snapshots and Network Interfaces. Until today, by default these managed resources appeared alongside self-managed ones in API responses and respective resource consoles even though AWS is responsible for managing these resources. Now, with Managed resource visibility settings, any new managed resources are hidden by default from your resource console views and describe API responses such as EC2 console and describe-instances API responses, to align better with the shared responsibility model of these resources.  

Amazon SageMaker AI now supports serverless model customization for Qwen3.5, enabling you to fine-tune Qwen3.5 4B, 9B, and 27B parameter models using supervised fine-tuning (SFT) and reinforcement fine-tuning (RFT). Qwen3.5 is a popular open-weight model family from Alibaba Cloud. Before this launch, you could deploy these base models on SageMaker AI and now, you can also adapt them to your specific domains and workflows.  Model customization enables you to tailor foundation models with your proprietary data so they more accurately reflect your domain knowledge, terminology, and quality standards. Rather than building models from scratch, fine-tuning lets you start from a capable base model and specialize it for your use cases, whether that's improving accuracy on domain-specific tasks, aligning outputs with your organization's tone, or improving performance on new tasks using your labeled data. With serverless customization, SageMaker AI handles all infrastructure

Amazon Elastic Container Service (Amazon ECS) now offers NVIDIA GPU health monitoring and auto repair functionality for Amazon ECS Managed Instances. The new capability automatically detects critical NVIDIA GPU hardware failures and replaces impaired instances, helping customers improve the availability and reliability of their GPU-accelerated containerized workloads. Running GPU-accelerated workloads, such as GenAI inference, requires specialized hardware management to mitigate failures and minimize disruption. Amazon ECS Managed Instances now continuously monitor GPU health using NVIDIA Data Center GPU Manager (DCGM) and proactively replace impaired capacity when critical failures occur. You can monitor GPU health through the DescribeContainerInstances API and receive notifications through Amazon EventBridge when instances become impaired. For workloads where you prefer to manage instance

AWS Secrets Manager now supports managed external secrets for MongoDB Atlas and Confluent Cloud. AWS Secrets Manager now supports managed external secrets for MongoDB Atlas and Confluent Cloud, enabling you to centrally manage and automatically rotate secrets for these third-party services directly from AWS Secrets Manager — without building or maintaining custom Lambda rotation functions. The MongoDB Atlas integration supports two secret types: database user secrets (username-password authentication via SCRAM) and service account secrets (OAuth client ID and secret). The Confluent Cloud integration supports API key rotation for service accounts, with support for both cluster-scoped and cloud resource management keys. All integrations include automatic rotation enabled by default, eliminating hardcoded secrets and reducing the operational overhead of managing secrets across multiple platforms. With managed external secrets, secret rotation is fully managed

Today, Amazon Bedrock AgentCore introduces new features to help developers go from an idea to working agent prototype faster and manage the full agent lifecycle from a single platform: a managed harness (in preview), the AgentCore CLI, and AgentCore skills for coding assistants. The managed harness (preview) lets developers define an agent by specifying a model, system prompt, and tools, then run it immediately with no orchestration code required. The harness manages the full agent loop: reasoning, tool selection, action execution, and response streaming. Each session gets its own microVM with filesystem and shell access. The harness is model agnostic with the ability to switch models mid-session. Any configuration set at create time can be overridden per invocation, so developers experiment without redeploying. When developers need full control, they can export the harness orchestration in Strands-based code. Filesystem persistence (preview) externalizes the local session s

Amazon Interactive Video Service (Amazon IVS) Low-Latency Streaming now supports server-side ad insertion (SSAI), enabling you to monetize your live streams with video ads. IVS SSAI integrates with AWS Elemental MediaTailor to stitch ads directly into the video stream on the server, delivering a seamless viewing experience while providing access to ad decisioning, audience targeting, and personalization capabilities.  IVS provides an API operation to insert ad breaks into your live stream, giving creators or operators control over when ads run. Ads are stitched into the stream on the server, reducing the impact of ad blockers and simplifying client-side integration. When a live stream is recorded to Amazon S3, IVS includes ad markers in the recording, enabling you to monetize on-demand content as well.  Amazon IVS is a managed live streaming solution designed to make low-latency or real-time video available to viewe