Tag: Internet

Amazon Neptune Database now supports Graviton3-based R7g and Graviton4-based R8g instances for Amazon Neptune engine versions 1.4.5 or above, in Asia Pacific (Hong Kong), Asia Pacific (Osaka), Asia Pacific (Singapore), Canada (Central) and US West (N. California). R7g and R8g instances are priced -16% vs R6g. Graviton3-based R7g are the first AWS database instances to feature the latest DDR5 memory, enabling high-speed access to data in memory. R7g database instances offer up to 30Gbps enhanced networking bandwidth and up to 20 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). Graviton4-based R8g instances offer larger instance sizes, up to 48xlarge and features an 8:1 ratio of memory to vCPU, and the latest DDR5 memory. AWS Graviton4 processors are up to 40% faster for databases than AWS Graviton3 processors. You can launch R7g and R8g instances for Neptune using the

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) X8aedz instances are available in Asia Pacific (Mumbai) and Asia Pacific (Seoul) regions. These instances are powered by 5th Gen AMD EPYC processors (formerly code named Turin). These instances offer the highest maximum CPU frequency, 5GHz in the cloud. X8aedz instances are built using the latest sixth generation AWS Nitro Cards and are ideal for electronic design automation (EDA) workloads such as physical layout and physical verification jobs, and relational databases that benefit from high single-threaded processor performance and a large memory footprint. The combination of 5 GHz processors and local NVMe storage enables faster processing of memory-intensive backend EDA workloads such as floor planning, logic placement, clock tree synthesis (CTS), routing, and power/signal integrity analysis. X8aedz instances feature a 32:1 ratio of memory to vCPU and are a

Amazon Connect Cases now supports AWS CloudFormation, enabling you to model, provision, and manage case resources as infrastructure as code. With this launch, administrators can create CloudFormation templates to programmatically deploy and update their Cases configuration—such as templates, fields, and layouts—across Amazon Connect instances, reducing manual setup time and minimizing configuration errors. Amazon Connect Cases is available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Canada (Central), Europe (Frankfurt), Europe (London), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), and Africa (Cape Town). To learn more and get started, visit the Amazon Connect Cases webpage and documentation.

Amazon Lex now offers a neural automatic speech recognition (ASR) model for English that delivers improved recognition accuracy for your voice bots. Trained on data from multiple English locales, the model excels at recognizing conversational speech patterns across diverse speaking styles, including non-native English speakers and regional accents. This reduces the need for end-customers to repeat themselves and improves self-service success rates. To enable this feature, select "Neural" as the speech recognition option in your bot's locale settings. This feature is available in all AWS commercial regions where Amazon Connect and Lex operate. To learn more, visit the Amazon Lex documentation or explore the Amazon Connect website to learn how Amazon Connect and Amazon Lex deliver seamles

Amazon MSK Connect is now available in three additional AWS Regions: Asia Pacific (New Zealand), AWS GovCloud (US-East), and AWS GovCloud (US-West). 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. With thi

Amazon SageMaker HyperPod console now validates service quotas for your AWS account before initiating cluster creation, enabling you to confirm sufficient quota availability before provisioning begins. SageMaker HyperPod helps you provision resilient clusters for running AI/ML workloads and developing state-of-the-art models such as large language models (LLMs), diffusion models, and foundation models (FMs). When creating large-scale AI/ML clusters, you need to ensure your account has sufficient quotas for instances, storage, and networking resources, but quota validation previously required manual checks across multiple AWS services, often resulting in failed cluster creation attempts and wasted time if you miss requesting quota limit increases. The new quota validation capability in the SageMaker HyperPod console automatically checks your account-level quotas against your cluster configuration, including instance type limits, EBS volume sizes, and VPC-related quotas

Amazon Lex now provides three VAD sensitivity levels that can be configured for each bot locale: Default, High, and Maximum. The Default setting is suitable for most environments with typical background noise levels. High is designed for environments with consistent but moderate noise levels, such as busy offices or retail spaces. Maximum provides the highest tolerance for very noisy environments such as manufacturing floors, construction sites, or outdoor locations with significant ambient noise. You can configure VAD sensitivity when creating or updating a bot locale in the Amazon Connect's Conversational AI designer. This feature is available in all AWS commercial regions where Amazon Connect and Lex operate. To learn more, visit the Amazon Lex documentation or explore the Amazon Connect we

Amazon Connect now offers customers the ability to view status of agent screen recordings in near real time in CloudWatch using Amazon EventBridge. With screen recording, supervisors can identify areas for agent coaching (e.g., non-compliance with business processes) by not only listening to customer calls or reviewing chat transcripts, but also watching agents’ actions while handling a contact (i.e., a voice call, chat and task). Using Amazon EventBridge, customers can see status of each agent screen recording including success/failure, failure codes with description, installed client version, agent web browser version, agent operating system, screen recording start and end times from CloudWatch. Customers can start using Amazon Connect screen recording status tracking by subscribing to Screen Recording Status Changed event type in Amazon EventBridge event bus. Screen recording status tracking is available in all the

Amazon Redshift Serverless, which allows you to run and scale analytics without having to provision and manage data warehouse clusters, is now generally available in the AWS Asia Pacific (New Zealand) region. With Amazon Redshift Serverless, all users, including data analysts, developers, and data scientists, can use Amazon Redshift to get insights from data in seconds. Amazon Redshift Serverless automatically provisions and intelligently scales data warehouse capacity to deliver high performance for all your analytics. You only pay for the compute used for the duration of the workloads on a per-second basis. You can benefit from this simplicity without making any changes to your existing analytics and business intelligence applications. With a few clicks in the AWS Management Console, you can get started with querying data using the Query Editor V2 or your tool of choice with Amazon Redshift

Amazon Inspector scanning for Lambda functions and Elastic Container Registry (ECR) images now supports Java Gradle inventory and vulnerability scanning. This release also adds coverage for MySQL, MariaDB, PHP, Jenkins-core, 7zip (on Windows), Elasticsearch, and Curl/LibCurl. This update enhances Amazon Inspector's ability to detect vulnerabilities and misconfigurations across a broader range of applications and environments. Amazon Inspector is an automated vulnerability management service that continually scans AWS workloads for software vulnerabilities and unintended network exposure, helping organizations improve their security posture and meet compliance requirements. The new Java Gradle support allows Inspector to scan Java dependencies based on gradle.lockfile content, providing comprehensive vulnerability assessments for Java applications. When you use Inspector to scan Lambda functions and ECR images, you will now see findings for MySQL, MariaDB, PHP, Jenkins-core,