8/19/2024, 12:00:00 AM ~ 8/20/2024, 12:00:00 AM (UTC)
Recent Announcements
AWS CodeBuild now supports Mac builds
Starting today, you can build applications on macOS with AWS CodeBuild. You can build artifacts on managed Apple M2 instances that run on macOS 14 Sonoma. AWS CodeBuild is a fully managed continuous integration service that compiles source code, runs tests, and produces ready-to-deploy software packages.\n Building, testing, signing, and distributing applications for Apple systems (iOS, iPadOS, watchOS, tvOS, and macOS) requires the use of Xcode which runs exclusively on macOS. You can provision a fleet of managed CodeBuild Mac instances which offer native integration with AWS, including Amazon VPC, AWS Secrets Manager, and IAM. You can use CodeBuild’s prepackaged build environment with common tools and frameworks, or you can bring your own Amazon EC2 AMI to provision the Mac instances in your fleet. Mac builds are available in US East (Ohio), US East (N. Virginia), US West (Oregon), Europe (Frankfurt), and Asia Pacific (Sydney). For a full list of AWS Regions where AWS CodeBuild is available, please visit our region table. To get started setup a reserved capacity macOS fleet, and see CodeBuild’s blog post for creating a project to run builds on your fleet.
Amazon S3 no longer charges for several HTTP error codes
Amazon S3 has completed a change so unauthorized requests that customers did not initiate are free of charge. With this change, bucket owners will never incur request or bandwidth charges for requests that return an HTTP 403 (Access Denied) error response if initiated from outside their individual AWS account or AWS Organization. To see the full list of error codes that are free of charge, visit Billing for Amazon S3 error responses. This billing change requires no changes to customer applications and applies to all S3 buckets.\n This change was first announced on May 13, 2024, and was applied to most S3 APIs within several weeks. Now, this change is effective across all S3 APIs in all AWS Regions, including the AWS GovCloud (US) Regions and AWS China Regions. To learn more, visit Billing for Amazon S3 error responses and Error Responses in the S3 User Guide.
Introducing browser-based SSH/RDP support for IPv6-only instances bundles on Lightsail
Amazon Lightsail now extends support for browser-based SSH/RDP connections, also known as Lightsail Connect, to IPv6-only instances. Now, you can connect to your Linux or Windows IPv6-only instance directly from Lightsail Console in browser.\n Previously, you would need to add a public IPv4 address to your IPv6-only instance to use Lightsail Connect. With the launch of IPv6 support, you can use Lightsail’s browser-based client that provides a quick and convenient way to connect to your instance and does not require any software installation. You can use this feature on the Lightsail Console (accessed from AWS Console) in all AWS Regions supporting Lightsail. To learn more about connecting to your instance from the Lightsail console, please refer to documentation.
We are excited to announce that Amazon EMR on EC2 now supports two new allocation strategies for Instance Fleets - prioritized for On-Demand instances and capacity-optimized-prioritized for Spot instances. Allocation strategies let you determine how EMR selects from your list of specified instance types and Availability Zones to fulfill your desired capacity. These new strategies give you more control and flexibility when provisioning instances for your EMR workloads.\n With today’s launch, you can use a prioritized list to determine the order in which EMR should attempt to provision your compute capacity. This new feature allows you to specify a priority for each instance type in your instance fleet configuration. For On-Demand instances, EMR will first attempt to fulfill capacity using the highest priority instance type. If EMR cannot fulfill the entire capacity using that instance type, it will then launch instances with the next highest priority, and so on. For Spot instances, EMR will optimize for capacity first, but will honor instance type priorities on a best-effort basis. This is great for workloads where the possibility of disruption must be minimized, but preferences for certain instance types matter. This feature is available for all EMR 5.x and later releases (excluding 5.0.0 and 5.0.3) in all AWS Regions, including the AWS GovCloud (US) Regions, where Amazon EMR on EC2 is available. Customers can easily configure these strategies through the EMR API, CLI, SDK, console, and CloudFormation. Review our allocation strategy for instance fleet documentation to learn more.
Amazon SageMaker Pipelines now provides a drag-and-drop UI to easily create ML workflows
Today, we are excited to announce the general availability of a drag-and-drop user interface (UI) for Amazon SageMaker Pipelines. Data scientists and Machine Learning (ML) engineers can now quickly create an end-to-end AI/ML workflow to train, fine-tune, evaluate, and deploy models without writing code.\n Customers use Amazon SageMaker Pipelines to automate thousands of ML workflows, such as continuous fine-tuning or experimentation of foundation models that power Generative AI workloads. With this launch, data scientists and ML engineers can accelerate the journey of such ML workflows from prototype to production because they don’t need to write code to author and configure Amazon SageMaker Pipelines. They can simply drag and drop various steps (e.g. Notebook Jobs, LLM fine-tuning jobs, inference endpoints) and connect them together in the UI to compose an ML workflow. Users who have already created a pipeline using the Amazon SageMaker Python SDK can now edit it within the UI.. This Amazon SageMaker Pipelines capability enables users to rapidly iterate on ML workflows and execute them at scale in production tens of thousands of times. Data scientists and ML engineers can also monitor and debug all the ML jobs orchestrated via the workflows within the same UI. The drag-and-drop UI for Amazon SageMaker Pipelines is available in all regions where Amazon SageMaker is available except China Regions and GovCloud (US) Regions. To get started, refer to Amazon SageMaker Pipelines developer guide.
AWS Blogs
AWS Japan Blog (Japanese)
- New Employee Project Generation Virtual Summit Assistant Exhibition Implementation Report Using AI @ AWS Summit Japan 2024
- How AWS enhanced Prime Day 2024 to achieve new sales records
- AWS Weekly Roundup: Mithra, Amazon Titan Image Generator v2, AWS GenAI Lofts, etc. (2024/8/12)
- A demonstration of the multi-site factory group equipment failure prediction and maintenance dashboard by Amazon Monitron was exhibited at AWS Summit 2024 Japan (Part 2: Service Explanation)
- Weekly Generative AI with AWS — Week of 2024/8/12
- Game development experience classes realized with AWS — Industry-academia collaboration between Capcom and Kindai University
- AWS Weekly — 2024/8/12
- Introducing the generative AI usage example “SQL correction proposal function using Amazon Bedrock” by Insight Technology Co., Ltd.
AWS News Blog
- Add macOS to your continuous integration pipelines with AWS CodeBuild
- AWS Weekly Roundup: G6e instances, Karpenter, Amazon Prime Day metrics, AWS Certifications update and more (August 19, 2024)
AWS Big Data Blog
- Unlock scalable analytics with a secure connectivity pattern in AWS Glue to read from or write to Snowflake
- Embed Amazon OpenSearch Service dashboards in your application
AWS Contact Center
AWS Database Blog
Desktop and Application Streaming
AWS for Industries
AWS Machine Learning Blog
Networking & Content Delivery
AWS Security Blog
- Making sense of secrets management on Amazon EKS for regulated institutions
- Announcing AWS KMS Elliptic Curve Diffie-Hellman (ECDH) support