Amazon MSK Connect is now available in ten additional AWS Regions: Asia Pacific (Jakarta), Asia Pacific (Hong Kong), Asia Pacific (Osaka), Asia Pacific (Melbourne), Europe (Milan), Europe (Zurich), Middle East (Bahrain), Middle East (UAE), Africa (Cape Town), and Israel (Tel Aviv). MSK Connect enables you to run fully managed Kafka Connect clusters with Amazon Managed Streaming for Apache Kafka (Amazon MSK). With a few clicks, MSK Connect allows you to easily deploy, monitor, and scale connectors that move data in and out of Apache Kafka and Amazon MSK clusters from external systems such as databases, file systems, and search indices. MSK Connect eliminates the need to provision and maintain cluster infrastructure. Connectors scale automatically in response to increases in usage and you pay only for the resources you use. With full compatibility with Kafka Connect, it is easy to migrate workloads without code changes. MSK Connect will support both Amazon MSK-managed and self-managed Apache Kafka clusters. You can get started with MSK Connect from the Amazon MSK console or the Amazon CLI. Visit the AWS Regions page for all the regions where Amazon MSK is available. To get started visit, the MSK Connect product page, pricing page, and the Amazon MSK Developer Guide.

Today, Amazon Web Services (AWS) announces the general availability of Volume Clones for Amazon Elastic Block Store (Amazon EBS), our high-performance block storage service. This new capability allows you to instantly create and access point-in-time copies of EBS volumes within the same Availability Zone (AZ), accelerating software development workflows and enhancing operational agility. Customers use Amazon EBS volumes as durable block storage attached to Amazon EC2 instances. With Amazon EBS Volume Clones, you can instantly create copies of volumes and access the copied volumes with single-digit millisecond latency. Amazon EBS Volume Clones enables rapid creation of test and development environments from production volumes, eliminating manual copy workflows. Additionally, Volume Clones integrates with the Amazon EBS Container Storage Interface (CSI) driver, simplifying storage management for containerized applications. Amazon EBS Volume Clones is available in all AWS Commercial Regions and AWS GovCloud (US) Regions. You can access Volume Clones through the AWS Console, AWS Command Line Interface (CLI), AWS SDKs, and AWS CloudFormation. This capability supports all EBS volume types and works for volume copies within the same account and AZ. For detailed pricing information, please visit the EBS pricing page. To explore how Volume Clones can accelerate your software development processes and improve operational efficiency, visit the AWS documentation.

Amazon AppStream 2.0 now offers Microsoft applications with licenses included, providing customers with the flexibility to run these applications on AppStream 2.0 fleets. As part of this launch, AppStream 2.0 provides Microsoft Office, Visio, and Project 2021/2024 in both Standard and Professional editions. Each is available in both 32-bit and 64-bit versions for On-Demand and Always-On fleets. Administrators can dynamically control applications availability by adding or removing applications from AppStream 2.0 images and fleets. End users benefit from a seamless experience, accessing Microsoft applications that are fully integrated with their business applications within their AppStream 2.0 sessions. This helps in ensuring that users can work efficiently with both Microsoft and business applications in a unified environment, eliminating the need for switching between different platforms or services. To get started, create an AppStream custom image by launching an image builder with a Windows Server operating system image. Select the desired set of applications to be installed. Then connect to the image builder and complete image creation by following the Amazon AppStream 2.0 Administration Guide. You must use an AppStream 2.0 Image Builder that uses an AppStream 2.0 agent released on or after October 2, 2025 Or, your image must use managed AppStream 2.0 image updates released on or after October 3, 2025. This functionality is generally available in all regions where AppStream 2.0 is offered. Customers are billed per hour for the AppStream streaming resources, and per-user per-month (non-prorated) for Microsoft applications. Please see Amazon AppStream 2.0 Pricing for more information.

Amazon Connect now provides configurable thresholds for schedule adherence, giving you more flexibility in how you track agent performance. You can define thresholds for how early or late agents start or end their shifts, as well as for individual activities. For example, agents can start their shift 5 minutes early and end 10 minutes late, or end their breaks 3 minutes late, without negatively impacting their adherence scores. You can further customize these thresholds for individual teams. For example, teams that handle contacts with long handle times can be given more flexibility in when they start their breaks. This launch enables managers to focus on true adherence violations and eliminates the impact of minor schedule deviations on agent performance, thus improving manager productivity and agent satisfaction. This feature is available in all AWS Regions where Amazon Connect agent scheduling is available. To learn more about Amazon Connect agent scheduling, click here.

AWS Transfer Family SFTP connectors can now connect to remote SFTP servers through your Amazon Virtual Private Cloud (VPC). This enables you to transfer files between Amazon S3 and any SFTP server, whether privately or publicly hosted, while leveraging the security controls and network configurations already defined in your VPC. By utilizing your NAT Gateways' bandwidth for file transfers over SFTP, you can achieve improved transfer performance and ensure compatibility with remote firewalls. AWS Transfer Family provides fully managed file transfers over SFTP, FTP, FTPS, AS2 and web-browser based interfaces. You can now use Transfer Family SFTP connectors to connect with SFTP servers that are only accessible from your VPC, including on-premises systems, external servers shared over private networks, or in-VPC servers. You can present the IP addresses from your VPC’s CIDR range for compatibility with IP controls, and achieve higher bandwidth for large-scale transfers via your NAT gateways when connecting over the internet. All connections are routed through your VPC’s existing networking and security controls, such as AWS Transit Gateway, centralized firewalls and traffic inspection points, helping you meet data security mandates. SFTP connectors support for VPC-based connectivity is available in select AWS Regions. To get started, visit the AWS Transfer Family console, or use AWS CLI/SDK. To learn more, read the AWS News Blog or visit the Transfer Family User Guide.

Amazon Route 53 Profiles now supports AWS PrivateLink. Customers can now access and manage their Profiles privately, without going through the public internet. AWS PrivateLink provides private connectivity between VPCs, AWS services, and on-premises applications, securely over the Amazon network. When Route 53 Profiles is accessed via AWS PrivateLink, all operations, such as creating, deleting, editing, and listing of Profiles, can be handled via the Amazon private network.  Route 53 Profiles allows you to define a standard DNS configuration, in the form of a Profile, that may include Route 53 private hosted zone (PHZ) associations, Route 53 Resolver rules, and Route 53 Resolver DNS Firewall rule groups, and apply this configuration to multiple VPCs in your account. Profiles can also be used to enforce DNS settings for your VPCs, with configurations for DNSSEC validations, Resolver reverse DNS lookups, and the DNS Firewall failure mode. You can share Profiles with AWS accounts in your organization using AWS Resource Access Manager (RAM). Customers can use Profiles with AWS PrivateLink in regions where Route 53 Profiles is available today, including the AWS GovCloud (US) Regions. For more information about the AWS Regions where Profiles is available, see here. To learn more about configuring Route 53 Profiles, please refer to the service documentation.

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M7i instances powered by custom 4th Gen Intel Xeon Scalable processors (code-named Sapphire Rapids) are available in the Europe (Milan) region. These custom processors, available only on AWS, offer up to 15% better performance over comparable x86-based Intel processors utilized by other cloud providers. M7i deliver up to 15% better price-performance compared to M6i. M7i instances are a great choice for workloads that need the largest instance sizes or continuous high CPU usage, such as gaming servers, CPU-based machine learning (ML), and video-streaming. M7i offer larger instance sizes, up to 48xlarge, and two bare metal sizes (metal-24xl, metal-48xl). These bare-metal sizes support built-in Intel accelerators: Data Streaming Accelerator, In-Memory Analytics Accelerator, and QuickAssist Technology that are used to facilitate efficient offload and acceleration of data operations and optimize performance for workloads. To learn more, visit Amazon EC2 M7i Instances. To get started, see the AWS Management Console.

AWS for Fluent Bit announces version 3.0.0, based on Fluent Bit version 4.1.0 and Amazon Linux 2023. Container logging using AWS for Fluent Bit is now more performant and more feature-rich for AWS customers, including those using Amazon Elastic Container Services (Amazon ECS) and Amazon Elastic Kubernetes Service (Amazon EKS). AWS for Fluent Bit enables Amazon ECS and Amazon EKS customers to collect, process, and route container logs to destinations including Amazon CloudWatch Logs, Amazon Data Firehose, Amazon Kinesis Data Streams, and Amazon S3 without changing application code. AWS for Fluent Bit 3.0.0 upgrades the Fluent Bit version to 4.1.0, and upgrades the base image to Amazon Linux 2023. These updates deliver access to the latest Fluent Bit features, significant performance improvements, and enhanced security. New features include native OpenTelemetry (OTel) support for ingesting and forwarding OTLP logs, metrics, and traces with AWS SigV4 authentication—eliminating the need for additional sidecars. Performance improvements include faster JSON parsing, processing more logs per vCPU with lower latency. Security enhancements include TLS min version and cipher controls, which enforce your TLS policy on outputs from AWS for Fluent Bit for stronger protocol posture. You can use AWS for Fluent Bit 3.0.0 on both ECS and EKS. On ECS, update the FireLens log-router container image in your task definition to the 3.0.0 tag from the Amazon ECR Public Gallery. On EKS, upgrade by either updating the Helm release or setting the DaemonSet image to the 3.0.0 version. The AWS for Fluent Bit image is available in the Amazon ECR Public Gallery and in the Amazon ECR repository. You can also find it on GitHub for source code and additional guidance.

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M8g instances are available in AWS Europe (Paris), Asia Pacific (Osaka), AWS Canada (Central), and AWS Middle East (Bahrain) regions. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 M8g instances are built for general-purpose workloads, such as application servers, microservices, gaming servers, midsize data stores, and caching fleets. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads. AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. These instances offer larger instance sizes with up to 3x more vCPUs and memory compared to Graviton3-based Amazon M7g instances. AWS Graviton4 processors are up to 40% faster for databases, 30% faster for web applications, and 45% faster for large Java applications than AWS Graviton3 processors. M8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). To learn more, see Amazon EC2 M8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.

AWS Config now supports 3 additional AWS resource types. This expansion provides greater coverage over your AWS environment, enabling you to more effectively discover, assess, audit, and remediate an even broader range of resources. With this launch, if you have enabled recording for all resource types, then AWS Config will automatically track these new additions. The newly supported resource types are also available in Config rules and Config aggregators. You can now use AWS Config to monitor the following newly supported resource types in all AWS Regions where the supported resources are available: Resource Types: AWS::ApiGatewayV2::Integration AWS::CloudTrail::EventDataStore AWS::Config::StoredQuery

AWS now provides immediate access to resource search capabilities in all accounts through AWS Resource Explorer. With this launch, you no longer need to activate Resource Explorer to discover your resources in a Region. To start searching, you need, at minimum, permissions in the AWS Resource Explorer Read Only Access or AWS Read Only Access managed policies. You can discover resources in the AWS Resource Explorer console, Unified Search, and AWS CLI and SDKs. To search the full inventory of supported resources, including historical backfill and automatic updates, complete Resource Explorer setup. This requires additional permissions to create a Service-Linked Role, so that Resource Explorer can automatically complete setup in each Region where you search. You can also enable cross-Region search to discover resources across all Regions in your AWS account with one-click in the Console, or with a single API call using the new CreateResourceExplorerSetup API. This feature is available at no additional cost in all AWS Regions where Resource Explorer is supported. To start searching for your resources, visit the AWS Resource Explorer console. Read about getting started in the AWS Resource Explorer documentation, or explore the AWS Resource Explorer product page.

Starting today, Amazon EC2 High Memory U7i instances with 12TB of memory (u7i-12tb.224xlarge) are now available in the Asia Pacific (Mumbai) region. U7i-12tb instances are part of AWS 7th generation and are powered by custom fourth generation Intel Xeon Scalable Processors (Sapphire Rapids). U7i-12tb instances offer 12TiB of DDR5 memory enabling customers to scale transaction processing throughput in a fast-growing data environment. U7i-12tb instances offer 896 vCPUs, support up to 100Gbps Elastic Block Storage (EBS) for faster data loading and backups, deliver up to 100Gbps of network bandwidth, and support ENA Express. U7i instances are ideal for customers using 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 Relational Database Service (Amazon RDS) for SQL Server now supports the latest General Distribution Release (GDR) updates for Microsoft SQL Server. This release includes support for Microsoft SQL Server 2016 SP3+GDR KB5065226 (RDS version 13.00.6470.1.v1), SQL Server 2017 CU31+GDR KB5065225 (RDS version 14.00.3505.1.v1), SQL Server 2019 CU32+GDR KB5065222 (RDS version 15.00.4445.1.v1) and SQL Server 2022 CU21 KB5065865 (RDS version 16.00.4215.2.v1). The GDR updates address vulnerabilities described in CVE-2025-47997, CVE-2025-55227, CVE-2024-21907. For additional information on the improvements and fixes included in these updates, see Microsoft documentation for KB5065226, KB5065225, KB5065222 and KB5065865. We recommend that you upgrade your Amazon RDS for SQL Server instances to apply these updates using Amazon RDS Management Console, or by using the AWS SDK or CLI. You can learn more about upgrading your database instance in the Amazon RDS SQL Server User Guide for upgrading your RDS Microsoft SQL Server DB engine.

Vector search for Amazon ElastiCache is now generally available. Customers can now use ElastiCache to index, search, and update billions of high-dimensional vector embeddings from popular providers like Amazon Bedrock, Amazon SageMaker, Anthropic, and OpenAI with latency as low as microseconds and up to 99% recall. Key use cases include semantic caching for large language models (LLMs) and multi-turn conversational agents, which significantly reduce latency and cost by caching semantically similar queries. Vector search for ElastiCache also powers agentic AI systems with Retrieval Augmented Generation (RAG) to ensure highly relevant results and consistently low latency across multiple retrieval steps. Additional use cases include recommendation engines, anomaly detection, and other applications that require efficient search across multiple data modalities. Vector search for ElastiCache is available with Valkey version 8.2 on node-based clusters in all AWS Regions at no additional cost. To get started, create a Valkey 8.2 cluster using the AWS Management Console, AWS Software Development Kit (SDK), or AWS Command Line Interface (CLI). You can also use vector search on your existing clusters by upgrading from any version of Valkey or Redis OSS to Valkey 8.2 in a few clicks with no downtime. To learn more about vector search for ElastiCache for Valkey read this blog and for a list of supported commands see the ElastiCache documentation.

Amazon CloudWatch announces the general availability of generative AI observability, helping you monitor all components of AI applications and workloads, including agents deployed and operated with Amazon Bedrock AgentCore. This release expands beyond runtime monitoring to include complete observability across AgentCore's Built-in Tools, Gateways, Memory, and Identity capabilities. DevOps teams and developers can now get an out-of-the-box view into latency, token usage, errors, and performance across all components of their AI workloads, from model invocations to agent operations. This feature is compatible with popular generative AI orchestration frameworks such as Strands Agents, LangChain, and LangGraph, offering flexibility with your choice of framework. With this new feature, CloudWatch enalbes developers to analyzes telemetry data across components of a generative AI application. Customers can monitor code execution patterns in Built-in Tools, track API transformation success rates through Gateways, analyze memory storage and retrieval patterns, and ensure secure agent behavior through Identity observability. The connected view helps developers quickly identify issues - from gaps in VectorDB to authentication failures - using end-to-end prompt tracing, curated metrics, and logs. Developers can monitor their entire agent fleet through the "AgentCore" section in the CloudWatch console, which integrates seamlessly with other CloudWatch capabilities including Application Signals, Alarms, Sensitive Data Protection, and Logs Insights. This feature is now available in US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Ireland), Asia Pacific (Mumbai), Asia Pacific (Tokyo), Asia Pacific (Singapore), and Asia Pacific (Sydney). To learn more, visit documentation. There is no additional pricing for Gen AI Observability, existing CloudWatch pricing for underlying telemetry data applies.

Amazon SageMaker AI Projects now supports provisioning custom machine learning (ML) project templates from Amazon S3. Administrators can now manage ML templates in SageMaker AI studio so data scientists can create standardized ML projects to meet their organizational needs. Data scientists can use Amazon SageMaker AI Projects to create standardized ML projects that meet organizational requirements and automate ML development workflows. Administrators define standardized ML project templates that include end-to-end development patterns. By provisioning custom templates from Amazon S3, administrators can define standardized project templates and provide access to these templates directly in the SageMaker AI studio for data scientists, ensuring all ML projects follow organizational standards. SageMaker AI Projects custom template S3 provisioning is available in all AWS Regions where SageMaker AI Projects is available. To learn more, visit SageMaker AI Projects documentation, and SageMaker AI Studio.

After careful consideration, we’re announcing availability changes for a select group of AWS services and features. These changes fall into three lifecycle categories: Services and Capabilities moving to Maintenance Services moving to maintenance will no longer be accessible to new customers starting Nov 7, 2025. Current customers can continue using the service or feature while exploring alternative solutions. Amazon Cloud Directory Amazon CodeCatalyst Amazon CodeGuru Reviewer Amazon Fraud Detector Amazon Glacier Amazon S3 Object Lambda Amazon Workspaces Web Access Client for PCoIP (STXHD) AWS Application Discovery Service AWS HealthOmics - Variant and Annotation Store AWS IoT SiteWise Edge Data Processing Pack AWS IoT SiteWise Monitor AWS Mainframe Modernization Service AWS Migration Hub AWS Snowball Edge Compute Optimized AWS Snowball Edge Storage Optimized AWS Systems Manager - Change Manager AWS Systems Manager - Incident Manager AWS Thinkbox Deadline 10 .NET Modernization Tools Services Entering Sunset The following services are entering sunset, and we are announcing the date upon which we will end operations and support of the service. Customers using these services should click on the links below to understand the sunset timeline (typically 12 months), and begin planning migration to alternatives as recommended in the updated service web pages and documentation. Amazon FinSpace Amazon Lookout for Equipment AWS IoT Greengrass v1 AWS Proton Services Reaching End of Support The following services have reached end of support and are no longer available as of October 7, 2025. AWS Mainframe Modernization App Testing For customers affected by these changes, we've prepared comprehensive migration guides and our support teams are ready to assist with your transition. Visit AWS Product Lifecycle Page to learn more. or contact AWS Support.

Amazon Quick Sight now supports font customization for data labels and axes. Authors can now customize fonts for data labels and axes in supported charts, in addition to the previously supported font customization for visual titles, subtitles, and legend, as well as tables and pivot tables headers. Authors can set the font size (in pixels), font family, color, and styling options like bold, italics, and underline across analysis, including dashboards, reports and embedded scenarios. With this update, you can further align your dashboard's fonts with your organization's branding guidelines, creating a more cohesive and visually appealing experience. Additionally, the expanded font customization options help improve readability, especially when viewing visualizations on large screens. This is now available in all supported Amazon Quick Suite regions. To learn more about this, visit Amazon Quick Suite Visual formatting guide.

Amazon Bedrock AgentCore is an agentic platform to build, deploy and operate highly capable agents securely at scale using any framework, model, or protocol. AgentCore lets you build agents faster, enable agents to take actions across tools and data, run agents securely with low-latency and extended runtimes, and monitor agents in production - all without any infrastructure management. With general availability, all AgentCore services now have Virtual Private Cloud (VPC) support, enabling secure, private agent deployment. AgentCore Runtime builds on its preview capabilities of industry-leading eight-hour execution windows and complete session isolation by adding support for the Agent-to-Agent (A2A) protocol, with broader A2A support coming soon across all AgentCore services. AgentCore Gateway now connects to existing Model Context Protocol (MCP) servers in addition to transforming APIs and Lambda functions into agent-compatible tools. Gateway provides a single, secure endpoint for agents to discover and use tools without the need for custom integrations. AgentCore Identity now offers identity-aware authorization, secure vault storage for refresh tokens, and native integration with additional OAuth-enabled services so agents can securely act on behalf of users or by themselves with enhanced access controls. AgentCore Observability now delivers complete visibility into end-to-end agent execution and operational metrics across all AgentCore services through dashboards powered by Amazon CloudWatch, and it is OTEL compatible, offering seamless integration with Amazon CloudWatch and external observability providers like Dynatrace, Datadog, Arize Phoenix, LangSmith, and Langfuse. AgentCore works with any open source framework (CrewAI, LangGraph, LlamaIndex, Google ADK, OpenAI Agents SDK) and any model in or outside Amazon Bedrock, giving you freedom to use your preferred frameworks and models, and innovate with confidence. Amazon Bedrock AgentCore is available in nine AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Frankfurt), and Europe (Ireland). Learn more about AgentCore through the blog, deep dive using the AgentCore resources, and get started with the AgentCore Starter Toolkit. AgentCore offers consumption-based pricing with no upfront costs.

AWS Client VPN now supports MacOS Tahoe client with version 5.3.1. You can now run the AWS supplied VPN client on the latest MacOS versions. AWS Client VPN desktop clients are available free of charge, and can be downloaded here. AWS Client VPN is a managed service that securely connects your remote workforce to AWS or on-premises networks. It supports desktop clients for MacOS, Windows x64, Windows Arm64 and Ubuntu-Linux. With client version 5.3.1 onwards, Client VPN now supports the MacOS Tahoe 26.0. It already supports Mac OS version 13.0, 14.0 and 15.0, Windows 10 (x64) and Windows 11 (Arm64 and x64), and Ubuntu Linux 22.04 and 24.04 LTS versions. To learn more about Client VPN: Visit the AWS Client VPN product page Read the AWS Client VPN documentation Read the AWS Client VPN user guide

Amazon EBS io2 Block Express volumes are now available in Amazon Web Services China (Beijing) Region, operated by Sinnet and Amazon Web Services China (Ningxia) Region, operated by NWCD. io2 Block Express leverage the latest generation of EBS storage server architecture designed to deliver consistent sub-millisecond latency and 99.999% durability. With a single io2 Block Express volume, you can achieve 256,000 IOPS, 4GiB/s throughput, and 64TiB storage capacity. You can also attach an io2 Block Express volume to multiple instances in the same Availability Zone, supporting shared storage fencing through NVMe reservations for improved application availability and scalability. With the lowest p99.9 I/O latency among major cloud providers, io2 Block Express is the ideal choice for the most I/O-intensive, mission-critical deployments such as SAP HANA, Oracle, SQL Server, and IBM DB2. Customers using io1 volumes can upgrade to io2 Block Express without any downtime using the ModifyVolume API to achieve 100x durability, consistent sub-millisecond latency, and significantly higher performance at the same or lower cost than io1. With io2 Block Express, you can drive up to 4x IOPS and 4x throughput at the same storage price as io1, and up to 50% cheaper IOPS cost for volumes over 32,000 IOPS. io2 Block Express is now available in all the Amazon Web Services regions. You can create and manage io2 Block Express volumes using the Amazon Web Services Management Console, Amazon Command Line Interface (CLI), or Amazon SDKs. For more information on io2 Block Express, see our tech documentation.

Amazon Connect now supports copy and bulk edit of agent scheduling configuration, making it easier to set up and maintain agent schedules. You can create new scheduling configurations by copying existing ones — for example, copy a weekday shift profile to create a weekend variant, or, copy scheduling configuration (time-zone, weekly working hours, days off, etc.) from an existing agent to multiple new hires. When bulk editing, you can select specific fields to update, such as update time-zone and start date for new hires without changing their weekly working hours. These updates reduce time spent by managers on configuration management, thus improving productivity and operational efficiency. This feature is available in all AWS Regions where Amazon Connect agent scheduling is available. To learn more about Amazon Connect agent scheduling, click here.

Amazon Connect now supports agent schedule adherence notifications, making it easier for you to proactively identify when agents aren't adhering to their scheduled activities. You can define rules to automatically send email or text notifications (via EventBridge) to supervisors when agents exceed adherence thresholds. For example, if agent adherence drops below 85% in a trailing 15-minute window, supervisors can receive an email alert. These automated notifications eliminate the need for continuous dashboard monitoring and enable proactive intervention before service levels decline, improving both supervisor productivity and customer satisfaction. This feature is available in all AWS Regions where Amazon Connect agent scheduling is available. To learn more about Amazon Connect agent scheduling, click here.

AWS Graviton4-based R8g database instances are now generally available for Amazon Aurora with PostgreSQL compatibility in the AWS Canada (Central), AWS Asia Pacific (Singapore) and AWS Asia Pacific (Seoul) regions. R8g instances offer larger instance sizes, up to 48xlarge and features an 8:1 ratio of memory to vCPU, and the latest DDR5 memory. Graviton4-based instances provide up to a 40% performance improvement and up to 29% price/performance improvement for on-demand pricing over Graviton3-based instances of equivalent sizes on Amazon Aurora PostgreSQL databases, depending on database engine, version, and workload. AWS Graviton4 processors are the latest generation of custom-designed AWS Graviton processors built on the AWS Nitro System. R8g DB instances are available with new 24xlarge and 48xlarge sizes. With these new sizes, R8g DB instances offer up to 192 vCPU, up to 50Gbps enhanced networking bandwidth, and up to 40Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). You can launch Graviton4 R8g database instances in the Amazon RDS Management Console or using the AWS CLI. Upgrading a database instance to Graviton4 requires a simple instance type modification. For more details, refer to the Aurora documentation. Amazon Aurora is designed for unparalleled high performance and availability at global scale with full PostgreSQL compatibility. It provides built-in security, continuous backups, serverless compute, up to 15 read replicas, automated multi-Region replication, and integrations with other AWS services. To get started with Amazon Aurora, take a look at our getting started page.

Amazon Neptune Analytics is now available in the AWS Canada (Central) and Australia (Sydney) Regions. You can now create and manage Neptune Analytics graphs in the AWS Canada (Central) and Australia (Sydney) Regions and run advanced graph analytics and vector similarity search. Neptune Analytics is a memory-optimized graph database engine for analytics. With Neptune Analytics, you can get insights and find trends by processing large amounts of graph data in seconds. To analyze graph data quickly and easily, Neptune Analytics stores large graph datasets in memory. It supports a library of optimized graph analytic algorithms, low-latency graph queries, and vector search capabilities within graph traversals. Neptune Analytics is an ideal choice for investigatory, exploratory, or data-science workloads that require fast iteration for data, analytical and algorithmic processing, or vector search on graph data. It complements Amazon Neptune Database, a popular managed graph database. To perform intensive analysis, you can load the data from a Neptune Database graph or snapshot into Neptune Analytics. You can also load graph data that's stored in Amazon S3. To get started, you can create a new Neptune Analytics graphs using the AWS Management Console, or AWS CLI. For more information on pricing and region availability, refer to the Neptune pricing page and AWS Region Table.