4/24/2026, 12:00:00 AM ~ 4/27/2026, 12:00:00 AM (UTC)
Recent Announcements
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.\n 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 Managed Streaming for Apache Kafka (MSK) ESM or self-managed Kafka ESM by provisioning and auto-scaling between a minimum and maximum number of polling resources called event pollers. With this launch, this feature is now available in three additional regions.
You can activate Provisioned Mode for MSK ESM or self-managed Kafka ESM by configuring a minimum and maximum number of event pollers in the ESM API, AWS Console, AWS CLI, AWS SDK, and AWS CloudFormation. You pay for the usage of event pollers, along a billing unit called Event Poller Unit (EPU). To learn more, read the Lambda ESM documentation and AWS Lambda pricing.
Amazon Quick now integrates with Visier’s Vee agent for workforce intelligence
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.\n 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 is available in all AWS Regions where Amazon Quick is available.
To get started with Amazon Quick, visit the website. To learn more about the Visier integration, read the Visier integration guide, see the blog, and explore more integrations on the integrations page.
Amazon Bedrock AgentCore Gateway and Identity support VPC egress
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.\n 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 resources across Gateway and Identity.
AgentCore Gateway and Identity are available in fourteen 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).
Learn more about VPC egress capabilities through AgentCore Gateway documentation, and AgentCore Identity documentation. Get started with the AgentCore CLI.
Amazon EC2 High Memory U7i instances now available in additional regions
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.\n 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, 200 Gbps of network bandwidth, and ENA Express. U7i instances are ideal for customers running mission-critical in-memory databases like SAP HANA, Oracle, and SQL Server.
To learn more about U7i instances, visit the High Memory instances page.
Amazon Connect now provides eight new metrics to measure and improve AI agent performance
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. \n 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 Connect Administrator Guide. To learn more about Amazon Connect, an AI-native solution that turns every customer interaction into a moment worth remembering, visit the Amazon Connect website
AWS Marketplace Management Portal now supports bank account deletion
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.\n 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 custom scripting for job submission workflows
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.\n 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 shared studio-wide directory using an environment variable, making it easy for pipeline teams to enforce standards across all artists. Each script receives job metadata automatically and supports configurable timeouts. To get started, visit the Deadline Cloud Client documentation.
AWS Blogs
AWS Japan Blog (Japanese)
- AUMOVIO enhances software development with an agent-based coding assistant powered by Amazon Bedrock
- AI for Science — A new era of research brought about by AI
- AWS Weekly Roundup: Claude Opus 4.7 on Amazon Bedrock, GA on AWS Interconnect, etc. (April 20, 2026)
Artificial Intelligence
Networking & Content Delivery
AWS Security Blog
AWS Storage Blog
- Migrate to Amazon S3 account regional namespaces
- Enabling AI-powered analytics on enterprise file data: Configuring S3 Access Points for Amazon FSx for NetApp ONTAP with Active Directory