AWS Recent Announcements

Amazon Bedrock AgentCore Identity now allows customers the ability to reference existing AWS Secrets Manager secret ARNs directly in AgentCore Identity Credential Providers. Previously, AgentCore Identity used a service-managed secret approach, where secrets were created and managed by the service on the customer’s behalf. This approach prevented customers from applying resource tags on create, encrypting secrets with a customer-managed key (CMK), or applying other organization-specific governance controls at the time of secret creation — causing friction for teams with strict governance requirements. Now, customers create and manage their secrets in AWS Secrets Manager using their own governance and compliance policies, including custom CMKs, tagging strategies, automatic rotation and resource policies, and then reference the existing secret ARN when configuring a Credential Provider in AgentCore Identity. This gives customers full ownership of how their secrets are created, classified, and governed, without changing how AgentCore Identity uses them at runtime. Amazon Bedrock AgentCore Identity bring your own secret is now generally available in 14 AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Canada (Central), Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), and Europe (Stockholm). To learn more, visit the Amazon Bedrock AgentCore Identity documentation.

Amazon Bedrock is a fully managed service that provides secure, enterprise-grade access to high-performing foundation models from leading AI companies, enabling you to build and scale generative AI applications. Amazon Bedrock customers can now monitor inference traffic to the bedrock-mantle endpoint with Amazon CloudWatch metrics, the same way they already do for the bedrock-runtime endpoint and other AWS services. The bedrock-mantle endpoint supports the OpenAI Responses API, OpenAI Chat Completions API, and the Anthropic Messages API, letting customers run existing OpenAI- or Anthropic-based applications on Amazon Bedrock with minimal code changes. CloudWatch metrics for the bedrock-mantle endpoint are published under the AWS/BedrockMantle namespace and include inference counts, input and output token totals, and client error counts. Metrics are published at multiple granularity levels, including account, project, model, and project-and-model, so customers can attribute usage and costs to the right workloads and teams. With this launch, customers can monitor production inference, set up alarms, and plan capacity on the bedrock-mantle endpoint. To get started, open the Amazon CloudWatch console, choose Metrics, and select the AWS/BedrockMantle namespace to view metrics for your account. CloudWatch metrics for the bedrock-mantle endpoint are available in all AWS Regions where the endpoint is offered: US East (N. Virginia, Ohio), US West (Oregon), Asia Pacific (Jakarta, Mumbai, Sydney, Tokyo), Europe (Frankfurt, Ireland, London, Milan, Stockholm), and South America (São Paulo). To learn more, see CloudWatch metrics for the bedrock-mantle endpoint.

Amazon Simple Email Service (Amazon SES) now supports tenant-level suppression lists, allowing email senders to isolate bounces and complaints per tenant. Previously, all tenants in an account shared a single suppression list, meaning one tenant’s email issues caused emails for other tenants to be suppressed. With this feature, each tenant maintains a separate suppression list, ensuring that bounces and complaints affect only the tenant that generated them. This capability benefits any sender managing distinct email streams from a single SES account. Key use cases include SaaS providers sending on behalf of multiple customers, enterprises separating transactional and marketing mail across business units, agencies managing campaigns for different brands, or any application where a complaint from one sending program shouldn’t suppress delivery for another.  You can configure suppression behavior using two settings: suppression scope (TENANT or ACCOUNT) and suppressed reasons (BOUNCE, COMPLAINT, or both). Amazon SES automatically records bounces and complaints to the appropriate tenant’s list. You can also manually manage suppressed addresses using API operations including PutSuppressedDestination, GetSuppressedDestination, DeleteSuppressedDestination, and ListSuppressedDestinations with the TenantName parameter. To learn more about tenant-level suppression lists in Amazon SES, visit the Amazon SES console or refer to the documentation.

Today, Amazon Simple Email Service (SES) launched a new set of deliverability features that help customers get more information about their outbound sending deliverability performance and reputation. Customers can now see the percentage of messages that are placed in recipient spam folders based on samples of industry data, as well as see when their domains and IPs are listed on public email sender block lists. This makes it easier for customers to optimize their sending content to maximize customer engagement.  Previously, customers could use SES’ Virtual Deliverability Manager to visualize the full end-to-end journey of email deliverability metrics. This included delivery rates, bounce rates of various types, as well as complaint, open and click rates. Customers did not have visibility into how many emails were placed in the spam folder, making it difficult to estimate how many emails were actually seen by recipients. Now, based on representative data sampled from the industry, customers can see inbox placement rates by sending domain and campaign. Customers can also pro-actively test candidate email content to estimate inbox placement rates at top mailbox providers before sending to any of their target recipients. Finally, customers get peripheral awareness and passive monitoring of industry blocklist activity, helping to identify when a reputation change may affect their ability to send emails to mailbox providers. SES supports inbox placement rates and blocklist monitoring in all AWS commercial regions where SES is available.  For more information, see the documentation for the Virtual Deliverability Manager global deliverability.

AWS End User Messaging now supports RCS for Business messaging in 20 additional countries, bringing the total to 22. Businesses can now send verified, branded RCS messages to customers in Austria, Brazil, Colombia, Czech Republic, Denmark, Dominican Republic, France, Germany, Guatemala, Italy, Mexico, Netherlands, Norway, Peru, Poland, Singapore, Slovakia, Spain, Sweden, and the United Kingdom, in addition to the United States and Canada. Customers can use the existing SendTextMessage API to send RCS messages to these countries with no application changes. Messages are delivered from a recognized business identity, and when a recipient’s device does not support RCS, they automatically fall back to SMS for reliable delivery. RCS for Business is available in all AWS Regions where AWS End User Messaging is available. Pricing varies by destination country; see the AWS End User Messaging pricing page for details. To learn more, see RCS for Business in the AWS End User Messaging User Guide.

Amazon Connect Customer now supports scheduling tasks up to 90 days in advance, helping organizations plan, route, and track long-running follow-up work. For example, an insurance team managing an auto repair claim can schedule future tasks for an adjuster visit, parts availability check, and repair completion follow-up, with each task routed to the right team at the right time with relevant claim context. You can schedule tasks using the StartTaskContact API, flows, or the agent workspace. This feature is available in all commercial and AWS GovCloud (US) regions where Amazon Connect Customer is offered. To learn more, see our documentation. To learn more about Connect Customer, visit the Amazon Connect Customer website. 

AWS Shield Advanced announces distributed denial-of-service (DDoS) attack flow logs, giving you packet-level visibility into traffic hitting Shield Advanced protected resources during a DDoS attack. The log data is published to Amazon S3, Amazon CloudWatch Logs, or Amazon Data Firehose, for forensic analysis and compliance purposes. The DDoS attack flow logs, capture critical packet-level details, including source and destination IP addresses, ports, protocols, packet and byte counts, source country information, and others. The log data is automatically published to your chosen destination at 5-minute intervals during active attacks. Once published, you can retrieve and analyze your flow log data using your preferred analytics tools, enabling post-incident investigation, threat intelligence gathering, and compliance reporting. To enable flow logs, you must protect the resources with Shield Advanced, and configure log delivery based on your destination. The feature is avaialble in all regions where AWS Shield Advanced is available. To learn more about configuring and using DDoS attack flow logs, visit the AWS Shield Advanced documentation.

AWS Interconnect – multicloud now offers a free 500 Mbps multicloud Interconnect, making it easier to privately connect your workloads on AWS and other public clouds. Customers have been adopting multicloud strategies while migrating more applications to the cloud. With AWS Interconnect – multicloud, AWS simplified the way cloud services providers (CSPs) offer managed, highly-resilient, private connectivity for customers. The specification that powers Interconnect is open and already adopted by Google Cloud and Oracle Cloud Infrastructure (currently in Public Preview), with Microsoft Azure coming later in 2026. Today we are making it easier for customers to evaluate, test, and operate workloads between AWS and another CSP. The new Free Tier Interconnect gives customers a fully managed, 500 Mbps Interconnect to another CSP at no charge on the AWS side, with the same network path, facility, and device resiliency as our paid offering. The other CSP determines their pricing and charges independently of AWS for their side of the infrastructure. Please review the other CSP’s pricing before creating your Interconnect. With a 500 Mbps Interconnect, you can transfer approximately 160 TB of data per month, enough to support significant multicloud workloads, data replication, or hybrid application architectures without incurring AWS Interconnect charges. To help customers monitor their network health and performance across clouds, each Free Tier multicloud Interconnect includes an Amazon CloudWatch Network Synthetic Monitor at no extra cost. The Free Tier is limited to one local (Tier 1) Interconnect per customer, per AWS Region to each CSP that is Generally Available with AWS and is subject to the AWS Service Terms. To get started, use the AWS Direct Connect Console and select AWS Interconnect from the navigation menu. To learn more, visit the AWS Interconnect User Guide.

Amazon Redshift now allows you to get started with Amazon Redshift Serverless with a lower data warehouse base capacity configuration of 4 Redshift Processing Units (RPUs) in the Asia Pacific (Hong Kong), Asia Pacific (Seoul), Canada (Central), Europe (London), South America (Sao Paulo), AWS GovCloud (US-East), and AWS GovCloud (US-West) regions. Amazon Redshift Serverless measures data warehouse capacity in RPUs. 1 RPU provides you 16 GB of memory. You pay only for the duration of workloads you run in RPU-hours on a per-second basis. Previously, the minimum base capacity required to run Amazon Redshift Serverless was 8 RPUs. You can start using Amazon Redshift Serverless for as low as $1.50 per hour and pay only for the compute capacity your data warehouse consumes when it is active. For predictable workloads, Amazon Redshift Serverless capacity reservations with 1-year and 3-year terms provide additional price-performance benefits. Amazon Redshift Serverless enables users to run and scale analytics without managing data warehouse clusters. The new lower capacity configuration makes Amazon Redshift Serverless suitable for both production and development environments, particularly when workloads require minimal compute and memory resources. This entry-level configuration supports data warehouses with up to 32 TB of Redshift managed storage, offering a maximum of 100 columns per table and 64 GB of memory. To get started, see the Amazon Redshift Serverless feature page, user documentation, and API Reference.

Amazon Relational Database Service (Amazon RDS) for Oracle now supports the Oracle April 2026 Release Update (RU) for Oracle Database versions 19c and 21c, and the corresponding Supplemental Patch Bundle for Oracle Database version 19c. We recommend upgrading to the April 2026 RU as it includes security updates for Oracle database products. Starting with April 2026 releases, the Oracle Spatial Patch Bundle has been renamed to Supplemental Patch Bundle (SPB). The SPB includes additional database patches recommended by Oracle for specific use cases, such as Oracle Spatial, Oracle Data Pump, and Oracle GoldenGate. You can apply the April 2026 RU from the Amazon RDS Management Console, or by using the AWS SDK or CLI. To automatically apply updates to your database instance during your maintenance window, enable Automatic Minor Version Upgrade. You can apply the Supplemental Patch Bundle update for new database instances, or upgrade existing instances to engine version ‘19.0.0.0.ru-2026-04.spb-1.r1’ by selecting the “Supplemental Patch Bundle Engine Versions” checkbox in the AWS Console. You can also use AWS Organizations upgrade rollout policy to stagger automatic minor version upgrades for your Amazon RDS database instances. This feature allows you to automatically apply updates to non-production environments, validate the updates, and then automatically apply the same update to production environments. For additional details about using AWS Organizations upgrade rollout policy for automatic minor version upgrades, refer to Amazon RDS for Oracle documentation .

Oracle Database@AWS is now generally available in eight additional AWS Regions: EU-Central-2 (Zurich), EU-South-1 (Milan), EU-South-2 (Spain), EU-West-3 (Paris), AP-Northeast-3 (Osaka), AP-Southeast-1 (Singapore), AP-Southeast-4 (Melbourne) and SA-East-1 (Sao Paulo). Oracle Database@AWS enables customers to access Oracle Cloud Infrastructure (OCI) managed Oracle Exadata systems within AWS data centers. With this launch, customers in Europe, South America, and Asia Pacific with in-region data residency requirements can migrate on-premises Oracle Exadata and Oracle Real Application Clusters (RAC) applications to AWS. With this expansion, Oracle Database@AWS services are now available in twenty Regions: US-East-1 (N. Virginia), US-West-2 (Oregon), US-East-2 (Ohio), CA-Central-1 (Canada Central), SA-East-1 (Sao Paulo), EU-Central-1 (Frankfurt), EU-West-1 (Dublin), EU-West-2 (London), EU-Central-2 (Zurich), EU-South-1 (Milan), EU-South-2 (Spain), EU-West-3 (Paris), AP-Northeast-1 (Tokyo), AP-Northeast-3 (Osaka), AP-Southeast-1 (Singapore), AP-Southeast-2 (Sydney), AP-Southeast-4 (Melbourne), AP-South-1 (Mumbai), AP-South-2 (Hyderabad), and AP-Northeast-2 (Seoul). To use Oracle Database@AWS services, request a private offer from Oracle through the AWS Marketplace, and use AWS Management Console to setup your databases. To learn more, visit Oracle Database@AWS overview and documentation.

Amazon S3 Tables are now available in the Asia Pacific (Taipei) and Asia Pacific (New Zealand) Regions. Amazon S3 Tables deliver the first cloud object store with built-in Apache Iceberg support, streamlining tabular data storage at scale. S3 Tables automatically perform continual table maintenance to optimize query efficiency and reduce storage costs as your data lake grows and evolves. Because S3 Tables support the Apache Iceberg standard, your data is easily queryable by both AWS and third-party engines. With the Intelligent-Tiering storage class, S3 Tables automatically manage costs based on access patterns with no performance impact or operational overhead. For more information about the AWS Regions where S3 Tables are available, see S3 Tables AWS Regions and endpoints. To learn more, see the following resources: Amazon S3 Tables Working with Amazon S3 Tables and table buckets S3 Tables pricing

Today, AWS Billing and Cost Management (BCM) announces support for Budgets widgets in BCM Dashboards, giving you the flexibility to customize your cost management console with the views that matter most to your organization. You can now monitor AWS Budgets alongside Cost Explorer reports and Savings Plans and Reserved Instance coverage and utilization reports, all in a single, tailored dashboard. Previously, reviewing budget performance required navigating to a separate console page. Now, finance teams and cloud administrators can add one or more Budgets widgets to any BCM Dashboard, displaying budget name, budgeted amount, actual spend, and forecasted amount. You can filter budgets by name, threshold, and budget type, directly within the widget, and choose which budgets appear on each dashboard, reducing the time spent switching between console pages and enabling faster budget monitoring across teams. Budget widgets are fully integrated with dashboard export capabilities, allowing you to include budget data in scheduled email reports or download it as CSV or PDF, making it easier to share budget status with stakeholders without manual data gathering.  Budgets widgets for BCM Dashboards are available in all AWS commercial Regions at no additional charge. To learn more, visit our User Guide.

Today, AWS IoT Core launches two new MQTT connection management APIs, GetConnection and ListSubscriptions, enabling you to easily access MQTT client connection and subscription information for your Internet of Things (IoT) devices. These APIs help you troubleshoot connectivity issues, monitor client behavior, and audit connection patterns across your device fleet. The GetConnection API gives you visibility into an IoT device connection by retrieving detailed connection information, including connection status, MQTT session details, and optional socket-level data such as source and target IP addresses, ports, and client VPC endpoint ID, controlled via granular IAM policies. The ListSubscriptions API complements this by returning all topic subscriptions, including QoS levels for a client’s MQTT session, for connected and offline clients with persistent sessions. This enables you to validate and identify overlapping or unnecessary subscriptions that may impact solution performance. Together with the existing DeleteConnection API, these new APIs provide a comprehensive MQTT connection management experience. These APIs are now available in all AWS regions where AWS IoT Core is supported. To learn more, visit the AWS IoT Core documentation and AWS IoT Core API reference guide.

AWS Organizations now automatically emits CloudTrail events to your management account whenever accounts join or leave your organization. These new events—AccountJoinedOrganization and AccountDepartedOrganization—provide security teams and cloud administrators with enhanced visibility into organizational membership changes, helping detect unauthorized activities and potential security incidents that previously could go unnoticed.  The AccountJoinedOrganization event captures how an account joined an organization (Created or Invited) and the join timestamp, while the AccountDepartedOrganization event records how an account departed —Left for accounts that departed voluntarily, Removed for accounts removed by the management account, or  Cleaned for accounts that were permanently closed along with the departure timestamp.  You can leverage these events to create CloudWatch alarms or Amazon EventBridge rules for real-time notifications, enabling rapid response to suspicious organizational changes. This capability supports critical use cases including fraud detection, compliance auditing, security monitoring, and incident investigation across your AWS environment.

Today, AWS announces the general availability of the next generation of AWS Resilience Hub, a central location in the AWS console that helps platform engineering and site reliability teams assess and strengthen the resilience of their critical workloads running on AWS. This new update expands on AWS Resilience Hub’s existing experience for meeting resilience objectives by introducing a new application model, dependency discovery, generative AI-powered failure mode analysis, modular resilience policies, and organization-wide reporting. With the next generation of Resilience Hub, teams model applications using a three-level hierarchy — systems, user journeys, and services — that reflects how these applications deliver business value. Through dependency discovery assessments, maintain up-to-date visibility into the AWS services, internal endpoints, and third-party endpoints that your services rely on. A generative AI-powered failure mode assessment analyzes your services against AWS Well-Architected best practices, the AWS Resilience Analysis Framework, and the organization’s resilience policies, generating prioritized, actionable recommendations. AWS Organizations integration enables central teams to define resilience policies and monitor posture across all accounts and regions from a single dashboard. The next generation of the AWS Resilience Hub is available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Canada (Central), Europe (Ireland), Europe (London), Europe (Frankfurt), Europe (Paris), Europe (Stockholm), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Asia Pacific (Seoul), and South America (São Paulo). To get started, visit the AWS console. To learn more about the next generation of AWS Resilience Hub, see the product page, or visit the AWS News Blog.  Existing AWS Resilience Hub customers can continue using their current experience and adopt the next generation of AWS Resilience Hub at their own pace. For guidance, see the migration user guide.

Amazon Connect Customer now supports generative AI-powered post-contact summaries in eight additional language families: Portuguese, French, Italian, German, Spanish, Chinese, Japanese, and Korean. Post-contact summaries also now support non-US variations of English, including British English, Australian English, and other regional locales, ensuring summaries reflect locally appropriate spelling and terminology. Generative AI-powered post-contact summaries provide agents and managers with concise, structured overviews of customer conversations across voice, chat, and email channels, eliminating the need to read full transcripts. With this expansion, organizations can automatically generate summaries in the language of the conversation, helping agents complete after-contact work faster and enabling managers to review contacts across languages. For example, a global support organization can now generate post-contact summaries for calls handled in French, German, or Japanese, giving supervisors visibility into service quality across all regions. The newly supported languages are available in all AWS Regions where Amazon Connect Customer post-contact summaries are available. To learn more, refer to View generative AI-powered post-contact summaries in the Amazon Connect Customer Administrator Guide. To learn more about Amazon Connect Customer, visit the Amazon Connect Customer website.

AWS  now offers Claude Opus 4.8 — Anthropic’s most capable generally available model to date — delivering meaningful advances across agentic coding, professional knowledge work, and long-running autonomous tasks for developers and enterprises building production AI applications. Claude Opus 4.8 can perform longer autonomous runs, deeper reasoning, and consistency to be trusted with production work. For coding, the Opus 4.8 reads codebases like an engineer, plans before it edits, and holds context across long sessions in real repositories. For agentic tasks, it is better at finding paths around obstacles instead of stalling, recovering from its own errors, and knowing when to ask for help versus when to keep going. For knowledge work, it better synthesizes across long documents and complex sources, self-checks its output, and delivers structured deliverables that hold up to review. Customers have two ways to access Claude Opus 4.8: Amazon Bedrock and Claude Platform on AWS. Amazon Bedrock keeps your data within AWS infrastructure and provides access to Claude Opus 4.8 through a unified service with AWS-managed features like Guardrails, Knowledge Bases, and regional data residency. To learn more, see Amazon Bedrock documentation  and regional availability.. Claude Platform on AWS gives you direct access to Anthropic’s native platform experience and capabilities via the AWS Console. Build, test, and deploy with the same APIs, features, and console experience you’d get working with Anthropic directly, unified with AWS billing and authentication. To get started, see the Claude Platform on AWS documentation

Today, AWS announced the general availability of the next generation of Amazon OpenSearch Serverless, a fully managed search and vector engine designed for customers building agents. The next generation of OpenSearch Serverless auto scales 20x faster than its predecessor and provisions resources in seconds to meet the demands of even the most unpredictable agentic workflows. With scale-to-zero and pay-per-usage pricing, customers can now save up to 60% compared to the cost of provisioning Opensearch clusters for peak loads. The next generation of OpenSearch Serverless introduces complete decoupling of compute and storage through a new shared storage layer. This means customers can scale compute up and down independently, reducing costs during low-traffic periods while maintaining instant readiness for traffic spikes. To simplify network connectivity, OpenSearch Serverless now offers two resource-based endpoints – a collection level endpoint and a regional endpoint which makes multi-VPC and on-premise connectivity straightforward using standard VPC APIs. The next generation of OpenSearch Serverless also launches with native integrations with AI development platforms including Vercel and Kiro, enabling developers to provision search infrastructure directly from their development environment using natural language commands. OpenSearch Serverless is now also part of OpenSearch Agent Skills that allows you to bring OpenSearch capabilities to your agents when using popular coding platfroms like Claude Code, Cursor and Codex. At GA, search and vector are the two available collection types. The next generation of OpenSearch Serverless is available today in all commercial AWS regions where Amazon OpenSearch Serverless is currently available. For pricing details about the next generation of OpenSearch Serverless, visit the pricing page. To learn more about the next generation of Amazon OpenSearch Serverless, see the marketing page, technical documentation and AWS News Blog. You can get started by visiting the technical launch blog that details all the new features launching in the next generation of Amazon OpenSearch Serverless.

Amazon DynamoDB Streams now supports AWS PrivateLink for FIPS (Federal Information Processing Standard) endpoints in AWS GovCloud (US) Regions. DynamoDB Streams captures time-ordered sequences of item-level modifications in DynamoDB tables, enabling real-time data processing and event-driven architectures. This enhancement allows government agencies and organizations with federal compliance requirements to establish private connectivity between their VPCs and DynamoDB Streams FIPS endpoints without exposing traffic to the public internet. This capability helps customers meet strict federal compliance and regulatory requirements while simplifying their network architecture. By keeping all traffic within the AWS network infrastructure, organizations can securely process real-time data streams, implement compliant change data capture (CDC) solutions, and build event-driven architectures that adhere to federal security standards. Government agencies operating in GovCloud regions can now leverage DynamoDB Streams for secure data streaming applications while maintaining the enhanced security and privacy that AWS PrivateLink provides. AWS PrivateLink support for DynamoDB Streams FIPS endpoints is available in AWS GovCloud (US-East) and AWS GovCloud (US-West) Regions, as well as US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Canada (Central), and Canada West (Calgary).  To learn more, visit the Amazon DynamoDB Streams PrivateLink documentation and the AWS PrivateLink page.

Amazon WorkSpaces Applications now supports the ability to set up streaming resources powered by Windows Desktop operating systems using Bring Your Own License (BYOL). Customers can now bring their existing Windows Desktop licenses to support their eligible Microsoft 365 Apps for enterprise, delivering a consistent and familiar desktop experience as users move between on-premises and virtual desktop environments. With BYOL support on WorkSpaces Applications, the operating system is hosted on hardware dedicated to the customer’s AWS account, enabling customers to stream Windows desktop applications and full desktop experiences at scale. Customers benefit from cost savings by bringing their existing Windows Desktop OS licenses, eliminating OS fees so they only pay for compute and streaming infrastructure. When the local device and the streaming session both run the same Windows Desktop OS, users apply the same workflows, shortcuts, and navigation in both environments. This removes the cognitive overhead of adapting to a different desktop experience when switching between local and remote work, reducing onboarding time. Windows Desktop for WorkSpaces Applications is available in multiple AWS Regions. For the list of supported regions, see Amazon WorkSpaces Applications BYOL documentation. To take advantage of BYOL on WorkSpaces Applications, organizations must meet Microsoft’s licensing requirements and commit to running a minimum number of streaming resources in a given AWS Region each month. To learn more about eligibility requirements and getting started, see the Amazon WorkSpaces Applications documentation and FAQs.

AWS IoT Core now supports the ability to send point-to-point messages to any connected device, providing better visibility into message delivery and lower messaging cost. AWS IoT Core is a fully managed service that securely connects IoT devices to the AWS cloud, and enables bi-directional messaging between IoT devices and cloud services. Previously, sending messages to a single IoT device required publishing to a topic subscribed by the device, with no built-in way to confirm delivery from the receiving device. With the SendDirectMessage API, you can send a message directly to any device connected to AWS IoT Core, and opt-in to receive delivery acknowledgement from the device. AWS IoT Core also uses the delivery acknowledgement to provide detailed API response codes and emit Amazon CloudWatch Logs, giving you visibility into message delivery status and failure reasons. Direct messaging is available in all AWS Regions where AWS IoT Core is available, including Amazon China and AWS GovCloud (US). To get started, see the direct messaging developer guide. For pricing details, visit the AWS IoT Core pricing page.

Today, AWS announces an enhancement to the opportunity deal sizing capability in AWS Partner Central, by allowing Partners to estimate deals using total contract value (TCV). Partners can now submit the TCV from the deal with the customer, and deal sizing capability instantly converts the TCV to a forecasted monthly recurring revenue (MRR), eliminating manual MRR estimation so partners submit opportunities faster and with more accurate forecasts. When creating or updating opportunities, partners choose an MRR estimation method — Forecast MRR from TCV, Forecast MRR, AWS Pricing Calculator, or Manual entry. With Forecast MRR from TCV, partners enter the total contract value in USD or EUR and the contract duration in months, then review the forecasted MRR before submitting. The forecasted MRR improves pipeline accuracy, so partner sales teams accelerate deal velocity. Deal sizing using TCV is available in AWS Partner Central worldwide. The feature is accessible through both AWS Partner Central and the AWS Partner Central API for Selling, which is available in the US East (N. Virginia) Region. To get started, log in to AWS Partner Central in the console to create or update opportunities. To learn more about deal sizing, visit the Partner Central Sales Guide. For API integration with your CRM system, see the AWS Partner Central API Documentation.

Amazon Connect Customer Assistant is now integrated within the UI builder, enabling contact center managers to create and modify views using natural language. Managers describe what they need, such as “Create a feedback form with rating and comment fields,” and the assistant generates the corresponding UI components for review before publishing. This reduces the time and expertise needed to build Views for Step-by-Step Guides and Workspace pages by up to 70%. Managers can use conversational prompts to create views, configure layouts with conditional UIs, set component properties, and apply styling without manual work. The assistant recommends components, explains options, and troubleshoots issues to accelerate builds. 

We are pleased to announce general availability of Amazon EC2 P6-B200 instances in AWS US East (N. Virginia) on SageMaker notebook instances. Amazon EC2 P6-B200 instances are powered by 8 NVIDIA Blackwell GPUs with 1440 GB of high-bandwidth GPU memory and 5th Generation Intel Xeon processors (Emerald Rapids). These instances deliver up to 2x better performance compared to P5en instances for AI training. Customers can use P6-B200 instances to interactively develop and fine-tune large foundation models, including LLMs, mixture of experts models, and multi-modal reasoning models. These instances enable efficient experimentation with larger models directly in JupyterLab or CodeEditor environments for generative AI applications such as enterprise copilots and content generation across text, images, and video. Visit developer guides for instructions on setting up and using JupyterLab and CodeEditor applications on SageMaker Studio and SageMaker notebook instances.

We are pleased to announce general availability of Amazon EC2 P4de instances in Asia Pacific (Tokyo) on SageMaker notebook instances. Amazon EC2 P4de instances are powered by 8 NVIDIA A100 GPUs with 80GB high-performance HBM2e GPU memory, 2X higher than the GPUs in our current P4d instances. The new P4de instances provide a total of 640GB of GPU memory, which provide up to 60% better ML training performance along with 20% lower cost to train when compared to P4d instances. The improved performance will allow customers to reduce model training times and accelerate time to market. Increased GPU memory on P4de will also benefit workloads that need to train on large datasets of high-resolution data. Visit developer guides for instructions on setting up and using JupyterLab and CodeEditor applications on SageMaker Studio and SageMaker notebook instances.

We are pleased to announce general availability of Amazon EC2 P5.48xl instances in Asia Pacific (Tokyo) on SageMaker notebook instances. Amazon EC2 P5.48xl instances are powered by NVIDIA H100 Tensor Core GPUs and deliver high performance in Amazon EC2 for deep learning (DL) and high performance computing (HPC) applications. They help you accelerate your time to solution by up to 4x compared to previous-generation GPU-based EC2 instances, and reduce cost to train ML models by up to 40%. Customers can use P5 instances for training and deploying complex large language models (LLMs) and diffusion models powering generative AI applications. These applications include question answering, code generation, video and image generation, and speech recognition. Visit developer guides for instructions on setting up and using JupyterLab and CodeEditor applications on SageMaker Studio and SageMaker notebook instances.

Amazon Bedrock is a fully managed service that provides secure, enterprise-grade access to high-performing foundation models from leading AI companies, enabling you to build and scale generative AI applications. Amazon Bedrock customers can now view inference quotas for the bedrock-mantle endpoint through AWS Service Quotas. This gives customers a familiar, consistent way to track limits for this endpoint, the same way they already do for the bedrock-runtime endpoint and other AWS services, and gives them clear visibility into the limits that apply to their workloads. The bedrock-mantle endpoint supports the OpenAI Responses API, OpenAI Chat Completions API, and the Anthropic Messages API, letting customers run existing OpenAI or Anthropic based applications on Amazon Bedrock with minimal code changes. AWS Service Quotas now exposes per-model input-tokens-per-minute and output-tokens-per-minute quotas for supported models on the endpoint. With this launch, customers gain visibility into how much limits they have on the bedrock-mantle endpoint and can proactively plan for production scale. To get started, open the AWS Service Quotas console, choose Amazon Bedrock, and search for “Bedrock Mantle” to view your current quotas. To request an increase to any of these quotas, follow the standard Amazon Bedrock limit increase process. Service Quotas support for the bedrock-mantle endpoint is available in all AWS Regions where the endpoint is offered: US East (N. Virginia, Ohio), US West (Oregon), Asia Pacific (Mumbai, Tokyo, Sydney, Jakarta), Europe (Frankfurt, Ireland, London, Milan, Stockholm), and South America (São Paulo). To learn more, see Quotas for Amazon Bedrock. 

AWS Elemental Inference now supports smart subtitles, a new AI-powered feature that automatically generates real-time subtitles for live video streams. Smart subtitles use advanced speech recognition to transcribe spoken audio and deliver Timed Text Markup Language (TTML)-formatted subtitles with low latency, helping broadcasters and streamers provide accessible content to viewers without manual captioning workflows or third-party services. With Smart subtitles, you can add live subtitling for content that is English (United States, Great Britain, and Australian), French, German, Italian, Portuguese, and Spanish to your broadcasts by enabling the feature through the native integration with AWS Elemental MediaLive. You can improve transcription accuracy for specialized content—such as sports commentary with athlete names or technical terminology—by creating custom dictionaries through the AWS Elemental Inference API or console. Smart subtitles work alongside existing Elemental Inference features like smart cropping for vertical video and clip generation, and you benefit from the same non-linear pricing that reduces per-feature costs when using multiple features simultaneously on the same content. To learn more, visit the AWS Elemental Inference documentation, MediaLive documentation,  and the AWS Elemental Inference pricing page.

We are pleased to announce general availability of Amazon EC2 P5.4xl instances on SageMaker notebook instances. Amazon EC2 P5.4xl instances are powered by NVIDIA H100 Tensor Core GPUs and deliver high performance in Amazon EC2 for deep learning (DL) and high performance computing (HPC) applications. They help you accelerate your time to solution by up to 4x compared to previous-generation GPU-based EC2 instances, and reduce cost to train ML models by up to 40%. Customers can use P5 instances for training and deploying complex large language models (LLMs) and diffusion models powering generative AI applications. These applications include question answering, code generation, video and image generation, and speech recognition. Amazon EC2 P5.4xl instances are available on SageMaker notebook instances in the AWS US East (N. Virginia and Ohio), US West (Oregon), Asia Pacific (Mumbai, Tokyo, Jakarta) and South America (São Paulo) regions. Visit developer guides for instructions on setting up and using JupyterLab and CodeEditor applications on SageMaker Studio and SageMaker notebook instances.