8/29/2024, 12:00:00 AM ~ 8/30/2024, 12:00:00 AM (UTC)

Recent Announcements

Amazon RDS for MySQL announces Extended Support minor 5.7.44-RDS.20240808

Amazon Relational Database Service (RDS) for MySQL announces Amazon RDS Extended Support minor version 5.7.44-RDS.20240808. We recommend that you upgrade to this version to fix known security vulnerabilities and bugs in prior versions of MySQL. Learn more about the bug fixes and patches in this version in the Amazon RDS User Guide.\n 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 RDS for MySQL databases 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 up, operate, and scale MySQL deployments in the cloud. See Amazon RDS for MySQL Pricing for pricing details and regional availability. Create or update a fully managed Amazon RDS database in the Amazon RDS Management Console.

AWS Deadline Cloud now supports Windows Server 2022 in service-managed fleets

Today, AWS announces support for running Windows Server 2022 on workers in service-managed fleets in AWS Deadline Cloud. AWS Deadline Cloud is a fully managed service that simplifies render management for teams creating computer-generated 2D/3D graphics and visual effects for films, TV shows, commercials, games, and industrial design.\n Now you can build pipelines for 3D graphics and visual effects using digital content creation (DCC) software that requires Windows - like Adobe After Effects, and KeyShot - without having to set up, configure, or manage the worker infrastructure yourself. Deadline Cloud service-managed fleets can be set up in minutes to run either Windows or Linux, expanding the DCC software you can use within a fully managed render farm. Windows Server 2022 is supported in service-managed fleets in all AWS Regions where Deadline Cloud is available. For more information, please visit the Deadline Cloud product page, and see the Deadline Cloud pricing page for price details.

Announcing Validation API for AWS Step Functions

AWS Step Functions announces a new Validation API for your AWS Step Functions workflows. The Validation API enables you to perform semantic checks on your workflows as you author them, helping you find syntactical errors sooner, shortening development cycles. AWS Step Functions is a visual workflow service capable of orchestrating virtually any AWS service to automate business processes and data processing workloads.\n With the Validation API, you can perform semantic checks on your workflows before you run or deploy them to catch issues sooner. Simply validate a workflow by creating, updating, or directly calling the ValidateStateMachineDefinition API. Now with the Validation API you can catch common syntactical errors in workflows such as missing .$ on a field that uses a JSONPath or Intrinsic Function. We have also included suggestions for field names that are incorrect, but have a close match. For example, in the event of potential case sensitivity errors when calling AWS services such as Amazon Simple Notification Service, or Amazon Simple Queue Service, we will suggest the correct alphabetical case for a service name when a mismatch is detected, saving you time. You can get started with the Validation API in the AWS console, using the AWS-SDK, or the AWS Command Line Interface (CLI). To learn more, see the AWS Step Functions Developer Guide to get started.

AWS AppConfig now provides deletion protection for additional guardrails

Customers can now enable deletion protection on AWS AppConfig resources, including Configuration Profiles and Environments. AWS AppConfig helps engineers move faster and resolve issues more quickly with managed feature flags and dynamic configuration. However, deleting any configuration data, for application hygiene or compliance reasons, should always be done very carefully to avoid unexpected behavior. With AWS AppConfig deletion protection enabled, a customer’s account will not be allowed to delete a recently-used resource without explicitly bypassing deletion protection in the AWS Management Console, CLI, or API call. In addition, customers can set the amount of time that is considered “recently-used” to tailor to their organization’s workflows.\n AWS AppConfig already has many safety guardrails to be able to update feature flags and configuration data with confidence. With AWS AppConfig, customers can gradually deploy changes to measure and limit impact; customers can set up an alarm to automatically rollback an in-process deployment; customers can validate configuration data syntactically and semantically prior to pushing out updates. With deletion protection, customers now have an additional safety guardrail to ensure their use of feature flags and dynamic configuration is as expected. Deletion protection for AWS AppConfig resources is available in all AWS Regions, including the AWS GovCloud (US) Regions. To get started, use the AWS AppConfig Getting Started Guide, or learn about AWS AppConfig deletion protection.

Amazon OpenSearch Service now supports Graviton3 (C7g, M7g, R7g, R7gd) instances

Amazon OpenSearch Service now supports AWS Graviton3 instances, which deliver up to 25% better performance over Graviton2-based instances. The new instance types are compute optimized (C7g), general purpose (M7g), and memory optimized (R7g, R7gd) instances. You can update your domain to the new instances seamlessly through the OpenSearch Service console or APIs.\n AWS Graviton3 processors are custom-designed AWS Graviton processors that enable the best price performance for workloads in Amazon Elastic Compute Cloud (Amazon EC2). They offer up to 30 Gbps enhanced networking bandwidth and up to 20 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). To learn more about Graviton3 improvements, please see the blog. Amazon OpenSearch Service Graviton3 instances support all OpenSearch versions and Elasticsearch (open source) versions 7.9 and 7.10. One or more than one Graviton3 instance types are now available on Amazon OpenSearch Service across 21 regions globally: US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Asia Pacific (Hong Kong), Asia Pacific (Hyderabad), Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Milan), Europe (Paris), Europe (Spain), Europe (Stockholm), Middle East (Bahrain), South America and (São Paulo). To learn more about region specific instance type availability and their pricing, visit our pricing page. To learn more about Amazon OpenSearch Service, please visit the product page.

Amazon Redshift Serverless is now available in the AWS Asia Pacific (Jakarta) region

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 (Jakarta) 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.\n 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, scaling, and other manual configurations. You can create databases, schemas, and tables, and load your own data from Amazon S3, access data using Amazon Redshift data shares, or restore an existing Amazon Redshift provisioned cluster snapshot. With Amazon Redshift Serverless, you can directly query data in open formats, such as Apache Parquet, in Amazon S3 data lakes. Amazon Redshift Serverless provides unified billing for queries on any of these data sources, helping you efficiently monitor and manage costs. To get started, see the Amazon Redshift Serverless feature page, user documentation, and API Reference.

Amazon SageMaker Projects now allows you to reuse names of previously deleted Projects

Amazon SageMaker Projects now allows you to reuse deleted project names. This launch enhances the project deletion process by removing the project names and metadata instead of only marking them as deleted. This capability is available via SageMaker Projects API, SageMaker Studio, and Amazon SageMaker Python SDK.\n Customers use SageMaker Projects to preconfigure and bootstrap all the resources required to run their ML workflow (e.g. code repositories, model training instances, ML Pipelines). This enhances the productivity of data scientists and accelerates the journey of generative AI and ML workflows from prototyping to production. With this launch, whenever customers delete a SageMaker Project all the metadata associated with it will be automatically deleted. They can reuse the name for new SageMaker Projects created in the future. This capability is available in all regions where Amazon SageMaker Projects is available. To learn more, see the SageMaker Projects Developer Guide

AWS Global Accelerator launches new edge location in Cairo, Egypt

AWS Global Accelerator now supports traffic through a new AWS edge location in Cairo, Egypt. With the addition of the edge location, Global Accelerator is now available through 121 Points of Presence globally and supports application endpoints in 29 AWS Regions.\n AWS Global Accelerator is a service that is designed to improve the availability, security, and performance of your internet-facing applications. By using the congestion-free AWS network, end-user traffic to your applications benefits from increased availability, DDoS protection at the edge, and higher performance relative to the public internet. Global Accelerator provides static IP addresses that act as fixed entry endpoints for your application resources in one or more AWS Regions, such as your Application Load Balancers, Network Load Balancers, Amazon EC2 instances, or Elastic IPs. Global Accelerator continually monitors the health of your application endpoints and offers deterministic fail-over for multi-region workloads without any DNS dependencies. To get started, visit the AWS Global Accelerator website and review its documentation.

Amazon Bedrock Knowledge Bases now supports Llama 3.1 405B, 70B, and 8B

Amazon Bedrock Knowledge Bases securely connects foundation models (FMs) to internal company data sources for Retrieval-Augmented Generation (RAG) to deliver relevant, context-specific, and accurate responses. Meta’s Llama 3.1 family of foundation models (405B, 70B, and 8B) is now generally available on Knowledge Bases.\n Llama 3.1 is the next generation of state-of-the-art models from Meta, supporting 128,000 tokens (roughly 96,000 words, or 192 pages of material) context length. Llama 3.1 models are well-suited for tasks that require complex reasoning, quick outputs, and RAG. Llama 3.1 is supported through the fully managed RetrieveAndGenerate API. Amazon Bedrock Knowledge Bases on Llama 3.1 405B, 70B, and 8B models is now generally available in the US West (Oregon) AWS Region. To learn more, read the AWS news blog launch and visit the Meta Llama in Amazon Bedrock page. To get started, refer to the Knowledge Bases for Amazon Bedrock documentation and visit the Amazon Bedrock console.

Research and Engineering Studio on AWS Version 2024.08 now available

Today we’re excited to announce Research and Engineering Studio (RES) on AWS Version 2024.08. This release adds new features such as Amazon S3 bucket mountpoints for Linux, allows creation of custom user roles and permission profiles, and offers the ability to adjust the list of Amazon EC2 instances available to launch as virtual desktops.\n Amazon S3 mountpoints allow Linux desktops to access S3 buckets as a file system. Amazon S3 buckets are created using the AWS Console or AWS CLI and onboarded to RES by administrators using the S3 Buckets page in the web portal. You can mount buckets in either Read Only or Read/Write mode. Read/Write buckets have an optional setting to restrict data access by project, or both project and user. RES can also mount S3 buckets from other AWS accounts with the proper permissions. Custom permission profiles allow administrators to create unique permissions and assign them to users or groups. Start by modifying the default Project Member and Project Owner roles or create your own permission set to adjust permissions for project and virtual desktop infrastructure management. The list of allowed instance types is also now configurable from the RES UI. You can adjust this list to define the instances available for virtual desktops in your environment. RES 2024.08 extends regional availability to Europe (Stockholm). See the regional availability page for a full list of regions where RES is available. Check out additional release notes on Github to get started and deploy RES 2024.08 today.

AWS Blogs

AWS Japan Blog (Japanese)

AWS Cloud Financial Management

AWS Cloud Operations & Migrations Blog

AWS Contact Center

AWS Database Blog

Desktop and Application Streaming

AWS for Industries

The Internet of Things on AWS – Official Blog

AWS Machine Learning Blog

AWS for M&E Blog

Networking & Content Delivery

Open Source Project

AWS CLI