AWS

Amazon Connect now supports nine additional languages for forecasting, capacity planning, and scheduling. New languages now supported include: Canadian French, Chinese (Simplified and Traditional), French, German, Italian, Japanese, Korean, Portuguese (Brazilian), and Spanish.

These new languages are available in all AWS Regions where Amazon Connect forecasting, capacity planning, and scheduling are available. To learn more about Amazon Connect agent scheduling, click here.
 

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UltraWarm is a fully managed, warm storage tier that’s designed to deliver cost savings on the Amazon OpenSearch Service. With OpenSearch 2.17+ domains, you can now store k-NN (vector) indexes on UltraWarm storage reducing the cost of serving infrequently access k-NN indexes through warm and cold storage tiers. With UltraWarm storage, you can further cost optimize vector search workloads on the OpenSearch vector engine. To learn more, refer to the documentation.

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AWS B2B Data Interchange now supports all X12 transactions for versions 4010, 4030, 4050, 4060, and 5010. Versions 4050 and 4060 are new to the service and were not previously available. Each of these transactions and versions are supported for both inbound and outbound use cases, enabling you to migrate a greater number of your bi-directional EDI workloads to AWS.

This launch especially benefits customers in the manufacturing, logistics, and financial services industries by enabling them to validate, parse, and transform a wider range of X12 transactions exchanged with their trading partners. Among these new transaction sets supported are those used to reserve shipment capacity, apply for mortgage insurance benefits, and to acknowledge purchase orders, deliveries, and returns.

These new X12 transaction sets and versions are available in all AWS Regions that offer B2B Data Interchange. A full list of these transactions, along with their descriptions and categories, can be found in the documentation. To learn more about building and running your bi- directional EDI workflows with B2B Data Interchange, take the self-paced workshop.

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Amazon CloudFront introduces Anycast Static IPs, providing customers with a dedicated list of IP addresses for connecting to all CloudFront edge locations worldwide.

Typically, CloudFront uses rotating IP addresses to serve traffic. Customers implementing Anycast Static IPs will receive a dedicated list of static IP addresses for their workloads. CloudFront Anycast Static IPs enables customers to provide a dedicated list of IP addresses to partners and their customers for enhancing security and simplifying network management across various use cases. For example, a common use case is allow-listing the static IP addresses in network firewalls.

CloudFront supports Anycast Static IPs from all edge locations. This excludes Amazon Web Services China (Beijing) region, operated by Sinnet, and the Amazon Web Services China (Ningxia) region, operated by NWCD. CloudFormation support will be coming soon. Learn more about Anycast Static IPs here and for more information, please refer to the Amazon CloudFront Developer Guide. For pricing, please see CloudFront Pricing.

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AWS Compute Optimizer now provides recommendations for Amazon Aurora DB instances. These recommendations help you identify idle database instances and choose the optimal DB instance class, so you can reduce costs for unused resources and increase the performance of under-provisioned workloads.

AWS Compute Optimizer automatically analyzes Amazon CloudWatch metrics such as CPU utilization, network throughput, and database connections to generate recommendations for your DB instances running Amazon Aurora MySQL-Compatible Edition and Aurora PostgreSQL-Compatible Edition engines. If you enable Amazon RDS Performance Insights on your DB instances, Compute Optimizer will analyze additional metrics such as DBLoad and out-of-memory counters to give you more insights to choose the optimal DB instance configuration. With this launch, AWS Compute Optimizer now supports recommendations for Amazon RDS for MySQL, Amazon RDS for PostgreSQL, and Amazon Aurora database engines.

This new feature is available in all AWS Regions where AWS Compute Optimizer is available except the AWS GovCloud (US) and the China Regions. To learn more about the new feature updates, please visit Compute Optimizer’s product page and user guide.

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Today, AWS has announced new AMIs for Bottlerocket that are preconfigured to use FIPS 140-3 validated cryptographic modules, including the Amazon Linux 2023 Kernel Crypto API and AWS-LC. Bottlerocket is a Linux-based operating system purpose-built for running containers, with a focus on security, minimal footprint, and safe updates.

With these FIPS-enabled Bottlerocket AMIs, the host software uses only FIPS-approved cryptographic algorithms for TLS connections. This includes connectivity to AWS services such as EC2 and Amazon Elastic Container Registry (ECR). Additionally, in regions where FIPS endpoints are available, the AMIs automatically use FIPS-compliant endpoints for these services by default, streamlining secure configurations for containerized workloads.

The FIPS-enabled Bottlerocket AMIs are now available in all commercial and AWS GovCloud (US) Regions. To see the regions where FIPS-endpoints are supported, visit the AWS FIPS 140-3 page.

To get started with Bottlerocket, see the Bottlerocket User Guide. You can also visit the Bottlerocket product page and explore the Bottlerocket GitHub repository for more information.

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AWS announces a “1-click move to managed” feature for Amazon Relational Database Service (Amazon RDS) that enables you to easily and seamlessly migrate your self-managed MySQL, PostgreSQL, or MariaDB databases to an equivalent Amazon RDS or Amazon Aurora database.

Using the 1-click move to managed functionality on the Amazon RDS console, you can migrate your self-managed databases running on an Amazon EC2 server to a managed Amazon RDS or Aurora database. This feature eliminates the infrastructure set up burden and makes it easy and seamless to re-platform your application’s database workload to Amazon RDS. Amazon RDS leverages Data Migration Service (DMS) homogeneous migration APIs to abstract and automate the entire process, including networking and system configuration, required to initiate and complete the migration. The process is flexible, scalable, and cost effective because the entire migration is performed using a temporary environment and using native database tools.

The RDS 1-click move to managed feature is now available on the RDS console in AWS commercial regions where homogeneous data migrations are supported. Get started today by visiting the Amazon RDS Console. Refer the RDS user guide or Aurora user guide to learn more.

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Today, AWS re:Post Private announces its integration with Amazon Bedrock, ushering in a new era of contextualized knowledge management for customer organizations. This feature transforms traditional organizational knowledge practices into a dynamic system of collaborative intelligence, where human expertise and AI capabilities complement each other to build collective wisdom.

At the heart of this integration is re:Post Agent for re:Post Private, an AI-powered assistant that delivers highly contextual technical answers to customer questions, drawing from a rich repository of curated knowledge resources. re:Post Agent for re:Post Private uniquely combines customer-specific private knowledge with AWS’s vast public knowledge base, ensuring responses are not only timely but also tailored to each organization’s specific context and needs.

By adopting re:Post Private with this new integration, organizations can now harness the full potential of collaborative intelligence. This powerful alliance between human insight and AI efficiency opens up new avenues for problem-solving, innovation, and knowledge sharing within enterprises. Unlock the transformative possibilities of collaborative intelligence and elevate your organization’s knowledge management capabilities with re:Post Private.

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Today, AWS announces that AWS Compute Optimizer now supports recommendations to help you identify idle AWS resources. With this new recommendation type, you will be able to identify resources that are un-used and may be candidates for turning off or deleting, resulting in cost savings.

With the new idle resource recommendation, you will be able to identify idle EC2 instances, EC2 Auto Scaling groups, EBS volumes, ECS services running on Fargate, and RDS instances. You can view the total savings potential of stopping or deleting these idle resources. Compute Optimizer analyzes 14 consecutive days of utilization history to validate if resources are idle to provide trustworthy savings opportunities. You can also view idle resource recommendation across all AWS accounts in your organization through the Cost Optimization Hub, with de-duplicated estimated savings with other recommendations on the same resources.

For more information about the AWS Regions where Compute Optimizer is available, see AWS Region table.

For more information about Compute Optimizer, visit our product page and documentation. You can start using AWS Compute Optimizer through the AWS Management Console, AWS CLI, and AWS SDK.

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CloudWatch RUM, which captures real-time data on web application performance and user interactions, helping you quickly detect and resolve issues impacting the user experience, now supports percentile aggregation of web vital metrics and simplified events based troubleshooting directly from the web vitals anomaly.

Google uses the 75th percentile (p75) of a web page’s Core Web Vitals—Largest Contentful Paint, First Input Delay, and Cumulative Layout Shift—to influence page ranking. With CloudWatch RUM, you can now monitor these p75 values of web page vitals and ensure that majority of your visitors experience optimal performance, minimizing the impact of outliers. You can also click on any point in the Web Vitals graph to view correlated page events, allowing you to quickly dive into event details such as browser, device, and geolocation to identify specific conditions causing performance issues. Additionally, you can track affected users and sessions for in-depth analysis and quickly troubleshoot issues without the added steps of applying filters to retrieve correlated events in CloudWatch RUM.

These enhancements are available in all regions where CloudWatch RUM is available at no additional cost to users.

See documentation to learn more about the feature, or see user guide or AWS One Observability Workshop to get started with real user monitoring using CloudWatch RUM.

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Amazon OpenSearch’s vector engine can now run modern search applications at a third of the cost on OpenSearch 2.17 domains. When you configure a k-NN (vector) index for disk mode, it becomes optimized for operating in a low memory environment. With disk mode on, the index is compressed using techniques like binary quantization and search quality (recall) is retained through a disk-optimized rescoring mechanism using full-precision vectors. Disk-mode is an excellent option for vector search workloads that require high accuracy, cost efficiency and are satisfied by low hundreds-of-milliseconds latency. It provides customers with a lower cost alternative to the existing in-memory mode when single-digit latency is unnecessary. To learn more, refer to the documentation.

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Amazon Keyspaces (for Apache Cassandra) is a scalable, serverless, highly available, and fully managed Apache Cassandra-compatible database service that offers 99.999% availability.

Today, Amazon Keyspaces added the capability to add Regions to existing Keyspaces. With this launch, you can convert an existing single-Region Keyspace to a multi-Region Keyspace or add a new Region to an existing multi-Region Keyspace without recreating the existing Keyspaces. As your application traffic and business needs evolve over time, you can easily add new Regions closest to your application to achieve lower read and write latencies. You can also improve the availability and resiliency of your workloads by adding Regions. Keyspaces fully manages all aspects of creating a new Region and populating it with the latest data from other Regions, enabling you to focus your resources on adding value for your customers rather than managing operational tasks. You can still perform read and write operations on your tables in the existing Region during the addition of a new Region. With this capability, you get the flexibility and ease to manage the regional footprint of your application based on your changing needs.

Support for adding Regions to existing Keyspaces is available in all AWS Regions where Amazon Keyspaces offers multi-Region Replication. For more information on multi-Region Replication, see documentation. If you’re new to Amazon Keyspaces, the Getting Started guide shows you how to provision a Keyspace and explore the query and scaling capabilities of Amazon Keyspaces.

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AWS Glue announces 19 new connectors for Enterprise applications to expand its connectivity portfolio. Now, customers can use AWS Glue native connectors to ingest data from Facebook Ads, Google Ads, Google Analytics 4, Google Sheets, Hubspot, Instagram Ads, Intercom, Jira Cloud, Marketo, Oracle NetSuite, SAP OData, Salesforce Marketing Cloud, Salesforce Marketing Cloud Account Engagement, ServiceNow, Slack, Snapchat Ads, Stripe, Zendesk and Zoho CRM.

As enterprises increasingly rely on data-driven decisions, they are looking for services making it easier to integrate with data from various Enterprise applications. With these 19 new connectors, customers can easily establish a connection to their Enterprise applications using AWS console or AWS Glue APIs without the need to learn application specific APIs. These connectors are scalable and performant with AWS Glue Spark engine and support for standard authorization and authentication method like OAuth 2.0. With these connectors, customers can test connection, validate their connection credential, browse metadata and preview data.

AWS Glue native connectors to Facebook Ads, Google Ads, Google Analytics 4, Google Sheets, Hubspot, Instagram Ads, Intercom, Jira Cloud, Marketo, Oracle NetSuite, SAP OData, Salesforce Marketing Cloud, Salesforce Marketing Cloud Account Engagement, ServiceNow, Slack, Snapchat Ads, Stripe, Zendesk and Zoho CRM are available in all AWS commercial regions.

To get started, create new AWS Glue connections with these connectors and use them as source in AWS Glue studio. To learn more, visit AWS Glue documentation for connectors.

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Today, AWS AppSync announced support for logging GraphQL data plane operations (query, mutation, and subscription operations and connect requests to your real-time WebSocket endpoint) using AWS CloudTrail, enabling customers to have greater visibility into GraphQL API activity in their AWS account for best practices in security and operational troubleshooting. AWS AppSync GraphQL is a serverless GraphQL service that gives application developers the ability to access data from multiple databases, micro-services, and AI models with a single GraphQL API request.

CloudTrail captures API activities related to AWS AppSync GraphQL APIs as events, including calls from the AWS console and calls made programmatically to the AWS AppSync GraphQL API endpoints. Using the information that CloudTrail collects, you can identify a specific request to an AWS AppSync GraphQL API, the IP address of the requester, the requester’s identity, and the date and time of the request. Logging AWS AppSync GraphQL APIs using CloudTrail helps you enable operational and risk auditing, governance, and compliance of your AWS account.

To opt-in for CloudTrail logging you can simply configure logging on your data stream using the AWS CloudTrail Console or by using CloudTrail APIs.

Logging data plane AWS AppSync GraphQL APIs using AWS CloudTrail is now available in all commercial AWS Regions where AppSync is available. To learn more about logging data plane APIs using AWS CloudTrail, see AWS Documentation. For more information about CloudTrail, see the AWS CloudTrail User Guide.

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Amazon OpenSearch Serverless has added support for Point in Time (PIT) search, enabling you to run multiple queries against a dataset fixed at a specific moment. This feature allows you to maintain consistent search results even as your data continues to change, making it particularly useful for applications that require deep pagination or need to preserve a stable view of data across multiple queries.

Point in time search supports both forward and backward navigation through search results, ensuring consistency even during ongoing data ingestion. This feature is ideal for e-commerce applications, content management systems, and analytics platforms that require reliable and consistent search capabilities across large datasets.

Point in time search on Amazon OpenSearch Serverless is now available in 15 regions globally: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Frankfurt), Europe (Ireland), Europe West (Paris), Europe West (London), Asia Pacific South (Mumbai), South America (Sao Paulo), Canada Central (Montreal), Asia Pacific (Seoul). and Europe (Zurich). Please refer to the AWS Regional Services List for more information about Amazon OpenSearch Service availability. To learn more about OpenSearch Serverless, see the documentation.

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Amazon Titan Text Embeddings V2 now supports Binary Embeddings. With Binary Embeddings, customers can reduce the storage cost for their Retrieval Augmented Generation (RAG) applications while maintaining similar accuracy of regular embeddings.

Amazon Titan Text Embeddings model generates semantic representations of documents, paragraphs, and sentences, as 1,024 (default), 512, or 256 dimensional vector. With Binary Embeddings, Titan Text Embeddings V2 will represent data as binary vectors with each dimension encoded as a single binary digit (0 or 1). This binary representation converts high-dimensional data into a more efficient format for storage in Amazon OpenSearch Serverless in Bedrock Knowledge Bases for cost-effective RAG applications.

Binary Embeddings is supported in Titan Text Embeddings V2, Amazon OpenSearch Serverless and Amazon Bedrock Knowledge Bases in all regions where Amazon Titan Text Embeddings V2 is supported. To learn more, visit the documentation for Binary Embeddings.

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AWS Chatbot announces general availability of AWS Support case management in Microsoft Teams and Slack. AWS customers can now use AWS Chatbot to monitor AWS support cases updates and respond to them from chat channels.

When troubleshooting issues, customers need to stay informed up-to-date on the latest support case updates in a place where they are collaborating. Previously, customers had to install a separate app or navigate to the Console to manage support cases. Now, customers can monitor and manage support cases from Microsoft Teams and Slack with AWS Chatbot.

To manage support cases from chat channels with AWS Chatbot, customers subscribe a chat channel to support case events published in EventBridge. As new case correspondences get added, AWS Chatbot sends the support case update notifications to the configured chat channels. Channel members can the use action buttons on the notifications to view the latest case updates and respond to them without leaving the chat channel.

To interact with support cases in chat channels, you must have a Business, Enterprise On-Ramp, or Enterprise Support plan. The case management in chat applications is available at no additional cost in AWS Regions where AWS Chatbot is offered. Get started with AWS Chatbot by visiting the AWS Management Chatbot Console and by downloading the AWS Chatbot app from the Microsoft Teams marketplace or Slack App Directory. Visit the AWS Chatbot product page and Managing AWS Support cases from chat channels in AWS Chatbot documentation to learn more.
 

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Amazon EFS now supports cross-account Replication, allowing customers to replicate file systems between AWS accounts. EFS Replication enables you to easily maintain an up-to-date replica of your file system in the AWS Region of your choice. With this launch, EFS Replication customers can meet business continuity, multi-account disaster recovery, and compliance requirements by automatically keeping replicas of their file data in separate accounts.

Customers often use multiple AWS accounts to help isolate and manage business applications and data for operational excellence, security, and reliability. Starting today, you can use EFS Replication to replicate your file system to another account in any AWS region. This eliminates the need to set up custom processes to synchronize EFS data across accounts, enhancing resilience and reliability in distributed environments.

EFS cross-account Replication is available for all existing and new EFS file systems in all commercial AWS Regions. To learn more, visit the Amazon EFS Documentation and get started by configuring EFS Replication in just a few clicks using the Amazon EFS Console, AWS CLI, AWS CloudFormation, and APIs.
 

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Amazon EKS enhances visibility into the Kubernetes control plane by offering new intuitive dashboards in EKS console and providing a broader set of Kubernetes control plane metrics. This enables cluster administrators to quickly detect, troubleshoot, and remediate issues. All EKS clusters on Kubernetes version 1.28 and above will now automatically display a curated set of dashboards visualizing key control plane metrics within the EKS console, making it easy to observe the health and performance of the control plane. Additionally, a broader set of control plane metrics are made available in Amazon CloudWatch and in a Prometheus endpoint, providing customers with the flexibility to utilize their preferred monitoring solution — be it Amazon CloudWatch, Amazon Managed Service for Prometheus, or third-party monitoring tools.

Newly introduced pre-configured dashboards in the EKS console provide cluster administrators with visual representations of key control plane metrics, enabling rapid assessment of control plane health and performance. Additionally, the EKS console dashboards now integrate with Amazon CloudWatch Log Insights queries, surfacing critical insights from control plane logs directly within the console. Finally, customers now get access to Kubernetes control plane metrics from kube-scheduler and kube-controller-manager, in addition to the existing API server metrics.

The new set of dashboards and metrics are available at no additional charge in all AWS commercial regions and AWS GovCloud (US) Regions. To learn more, visit the launch blog post or EKS user guide.

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Amazon OpenSearch Service now enables you to scale a single cluster to 1000 data nodes (1000 hot nodes and/or 750 warm nodes) and enables you to manage 25 petabytes of data (10 Petabytes in hot nodes and further 15 Petabytes in warm nodes). You no longer need to setup multiple clusters for workloads that require more than 200 data nodes or more than 3 Petabytes of data.

Today, for workloads of more than 3 to 4 petabytes of data, you need to create multiple clusters in OpenSearch Service. This may have required you to refactor your applications or business logic to work with your workload split across multiple clusters. In addition, every cluster requires its own configuration, management, and monitoring, adding to the operational overhead. With this launch, you can scale a single cluster up to 1000 nodes, or 25 petabytes of data, removing the operational overhead that comes with managing multiple clusters.

To scale a cluster beyond 200 nodes, you have to request an increase through Service Quota, after which you can modify your cluster configuration using the AWS Console, AWS CLI, or the AWS SDK. Depending on the size of the cluster, OpenSearch Service will recommend configuration pre-requisites across data nodes, cluster manager nodes, and coordinator nodes. For more information, refer to the documentation.

The new limits are available to all OpenSearch Service clusters running OpenSearch 2.17 and above in all AWS regions where Amazon OpenSearch Service is available. Please refer to the AWS Region Table for more information about Amazon OpenSearch Service availability.

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