Tag: SysAdmin

Knowledge Bases for Amazon Bedrock (KB) securely connects foundation models (FMs) to internal company data sources for Retrieval Augmented Generation (RAG), to deliver more relevant and accurate responses. We are excited to announce Guardrails for Amazon Bedrock is integrated with Knowledge Bases. Guardrails allow you to instrument safeguards customized to your RAG application requirements, and responsible AI policies, leading to a better end user experience. Guardrails provides a comprehensive set of policies to protect your users from undesirable responses and interactions with a generative AI application. First, you can customize a set of denied topics to avoid within the context of your application. Second, you can filter content across prebuilt harmful categories such as hate, insults, sexual, violence, misconduct, and prompt attacks. Third, you can define a set of offensive and inappropriate words to be blocked in their application. Finally, you can filter user inputs containing

Amazon Relational Database Service (RDS) for MySQL announces Amazon RDS Extended Support minor version 5.7.44-RDS.20240408. We recommend that you upgrade to this version to fix known security vulnerabilities and bugs in prior versions of MySQL. Learn more about upgrading your database instances, including minor and major version upgrades, in the Amazon RDS User Guide. Amazon RDS Extended Support provides you more time, up to three years, to upgrade to a new major version to help you meet your business requirements. During Extended Support, Amazon RDS will provide critical security and bug fixes for your MySQL and PostgreSQL databases on Aurora and RDS after the community ends support for a major version. You can run your MySQL databases on Amazon RDS with Extended Support for up to three years beyond a major version’s end of standard support date. Learn more about Extended Support in the Amazon RDS User Guide and the Pricing FAQs. Amazon RDS for MySQL makes it simple to set

Today, AWS has announced that Bottlerocket, the Linux-based operating system purpose-built for containers, now supports NVIDIA Fabric Manager, enabling users to harness the power of multi-GPU configurations for their AI and machine learning workloads. With this integration, Bottlerocket users can now seamlessly leverage their connected GPUs as a high-performance compute fabric, enabling efficient and low-latency communication between all the GPUs in each of their P4/P5 instances. The growing sophistication of deep learning models has led to an exponential increase in the computational resources required to train them within a reasonable timeframe. To address this increase in computational demands, customers running AI and machine learning workloads have turned to multi-GPU implementations, leveraging NVIDIA's NVSwitch and NVLink technologies to create a unified memory fabric across connected GPUs. The Fabric Manager support in the Bottlerocket NVIDIA variants allows users to configure

AWS HealthImaging now supports retrieval of DICOM Part 10 data, enabling customers to download instance-level binaries. The retrieve DICOM instance API is built in conformance to the DICOMweb WADO-RS standard for web-based medical imaging. With this feature launch, customers taking advantage of HealthImaging’s cloud-native interfaces can better interoperate with systems that utilize DICOM Part 10 binaries. You can retrieve a DICOM instance from a HealthImaging data store by specifying the Series, Study, and Instance UIDs associated with the resource. You can also provide an optional image set ID as a query parameter to specify the image set from which the instance resource should be retrieved. Customers can specify the Transfer Syntax, such as uncompressed (ELE) or compressed (High-throughput JPEG 2000). To learn more about how to retrieve DICOM P10 binaries, see the AWS HealthImaging Developer Guide.  AWS HealthImaging is a HIPAA-eligible service that empowers healthcare provid

Amazon Managed Streaming for Apache Kafka (Amazon MSK) now supports removing brokers from MSK provisioned clusters. Administrators can optimize costs of their Amazon MSK clusters by reducing broker count to meet the changing needs of their streaming workloads, while maintaining cluster performance, availability, and data durability. Customers use Amazon MSK as the core foundation to build a variety of real-time streaming applications and high-performance event driven architectures. As their business needs and traffic patterns change, they often adjust their cluster capacity to optimize their costs. Amazon MSK Provisioned provides flexibility for customers to change their provisioned clusters by adding brokers or changing the instance size and type. With broker removal, Amazon MSK Provisioned now offers an additional option to right-size cluster capacity. Customers can remove multiple brokers from their MSK provisioned clusters to meet the varying needs of their streaming workloads with

We are excited to announce that Knowledge Bases for Amazon Bedrock (KB) now lets you configure inference parameters to have greater control over personalizing the responses generated by a foundation model (FM).  With this launch you can optionally set inference parameters to define parameters such randomness and length of the response generated by the foundation model. You can control how random or diverse the generated text is by adjusting a few settings, such as temperature and top-p. The temperature setting makes the model more or less likely to choose unusual or unexpected words. A lower value for temperature generates expected and more common word choices. The top-p setting limits how many word options the model considers. Reducing this number restricts the consideration to a smaller set of word choices makes the output more conventional. In addition to randomness and diversity, you can restrict the length of the foundation model output, through maxTokens, and stopsequences.

Amazon WorkSpaces Core now offers new bundles powered by Windows Server 2019 and Windows Server 2022. With these bundles, customers and partners can take advantage of the latest license included Windows Server instances. This new feature will allow customers to minimize getting started time by providing staged images. In addition, this feature enables customers and partners to run multi-session VDI workloads on WorkSpaces Core desktops. You can get started using the managed Windows Server 2019 and Windows Server 2022 WorkSpaces Core bundle or create your own custom bundle and image tailored to your requirements. For more information on Amazon WorkSpaces Core’s new Windows Server Bundles, visit Amazon WorkSpaces Core FAQs. The new WorkSpaces Core Windows Server 2019 and Windows Server 2022 support is available in all AWS Regions where Amazon WorkSpaces Core is available. For pricing information, visits Amazon WorkSpaces Core pricing page.

Amazon Managed Service for Prometheus now supports inline editing of rules and alert manager configuration directly from the AWS console. Amazon Managed Service for Prometheus is a fully managed Prometheus-compatible monitoring service that makes it easy to monitor and alarm on operational metrics at scale. Prometheus is a popular Cloud Native Computing Foundation open-source project for monitoring and alerting on metrics from compute environments such as Amazon Elastic Kubernetes Service. Previously, customers could define alerting and recording rules, or alert manager definition, by importing respective configuration defined in a YAML file, via the AWS console. Now, they can import, preview, and edit existing rules or alert manager configurations from YAML files or create them directly from the AWS console. The inline editing experience allows customers to preview their rules and alert manager configuration prior to setting them. This feature is now available in all regions where Ama

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 additional AWS region South America (São Paulo). 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 Serverless. There is no need to choose node types, node count, workload management, scal

Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service provides customers advanced search capabilities, such as fuzzy search, cross-collection search and multilingual search, on their Amazon DocumentDB documents using the OpenSearch API. With a few clicks in the AWS Console, customers can now seamlessly synchronize their data from Amazon DocumentDB to Amazon OpenSearch Service, eliminating the need to write any custom code to extract, transform, and load the data. This integration extends the existing text search and vector search capabilities in Amazon DocumentDB, providing customers greater flexibility for searching their JSON-based documents. This zero-ETL integration uses Amazon OpenSearch Ingestion to synchronize the data from Amazon DocumentDB collections to Amazon OpenSearch Service. Amazon OpenSearch Ingestion is able to automatically understand the format of the data in Amazon DocumentDB collections and maps the data to your index mapping templates in Amazon Ope