
New Enum Values for Domestic Shipments in the Germany Amazon Store


Amazon Web Services (AWS) started with a handful of foundational infrastructure services such as Amazon Simple Storage Service (Amazon S3), Amazon Elastic Compute Cloud (Amazon EC2), and Amazon Simple Queue Service (Amazon SQS), so that anyone with an idea could start building. As the world’s largest companies and governments adopted AWS, they asked for features to optimize their configuration for a range of global business contexts, security requirements, and operational needs. To meet these needs, AWS expanded globally through new Regions and added breadth and depth of services in security, networking, governance, and cost controls, so those customers could operate wherever they needed and at the scale they require. That combination of global reach, breadth, and depth remains essential for those customers, but if you are at the start of a new idea, every configuration option is effort standing in the way of shipping your dream product fast.
Today, we’re announcing a new simplified experience on AWS for builders who are working at the pace of AI. Instead of having to complete configuration tasks before you can work on your project, you start with sensible defaults and simple administration. You sign up using an existing identity from providers including Google, GitHub, and Apple. For most new customers, no credit card is required to start and you receive $100 in free credits as part of the AWS Free Tier. You can build immediately in your first project. As you continue to work, you can invite collaborators with just an email address, without learning about AWS Identity and Access Management (IAM) or AWS IAM Identity Center. When your project grows beyond the free credits, you can set a spend limit so you stay within your budget on the paid plan. If you grow to need additional customization, you can activate advanced AWS features to access the full breadth and depth of AWS without migrating.
How it works
When you sign up, AWS organizes your work in a project. A project contains an AWS account, where you create resources, and settings for sharing with team members. AWS creates that structure for you and applies additional security controls so you can start building your idea. After signing in, you get a prompt to paste into your coding agent that configures it to work with your new AWS environment. From there, your agent can deploy resources, run workloads, and iterate on your application following best practices for working with AWS.
You can create another project with a click. When you want to work with an additional team member, you send an invitation to their email address. Identity permissions are handled for you, so there are no IAM users to create; each person you invite only gets access to the projects you specify. Console workflows and coding agents also configure permissions between supported services and resources automatically, so you do not have to set up or troubleshoot resource permissions by hand.
When you’re ready to move beyond free credits, you can upgrade to a paid plan by entering your payment method. You can set a monthly spend limit on a project based on your usage trends, starting at $20 per month. The spend limit is the ceiling for that project’s costs, and you pay for what you actually use up to that amount. For example, if you set a $50 spend limit and your project incurs $32 in charges that month, you pay $32 (plus taxes). AWS will suggest a spend limit based on your usage, and you can accept that recommendation or set a custom amount if you are planning to further scale your usage. If your project approaches the limit, you first receive notifications. If spend reaches the limit, AWS pauses your project rather than accumulating charges, and you can resume working on it when you raise the limit. Each project has its own spend limit so you can give a larger budget to a workload that is gaining traction while keeping a smaller budget on an experimental idea.
Let’s try it out
To get started, I went to aws.amazon.com and chose Create account. I signed in with my Google account and within seconds had a new project ready to go, as shown in the following screenshot.

The Sign up for AWS page, with options to continue with email or sign in using Google, GitHub, Apple, or Amazon.
The first thing I saw was a prompt to configure my coding agent. I copied the prompt and pasted it into my agent. The agent set up the AWS Command Line Interface (AWS CLI) and the Agent Toolkit for AWS, logged me into AWS, and created a CLAUDE.md file in my project with guidance for the new experience.

The Setup Agent Toolkit for AWS dialog, with a prompt to copy and paste into your coding agent.
With the agent connected, I gave it a short prompt: build an API that returns a new unique sequential ID on every request. The agent created an AWS Lambda function, an Amazon DynamoDB table, and an Amazon API Gateway API, then deployed them for me. I did not have to configure resource permissions by hand. Within a few minutes I had a public endpoint that returned a newly minted ID on each request. My project started with $100 in free credits, and I received an additional $20 when the Lambda function was deployed.

A coding agent prompt to build an API that returns a unique sequential ID on every request.

The coding agent presents architecture options for the sequential ID API, with AWS Lambda and Amazon DynamoDB selected.

The coding agent confirms the API is live and lists the Amazon DynamoDB table, AWS Lambda function, and Amazon API Gateway API it deployed.
From the project, I could manage settings, invite team members by email, and monitor billing, as shown in the following screenshots.

The Projects page, showing remaining free-plan days, credits, and a project.

The project Members page, with the option to invite a new team member by email.

The Billing page, showing a $0.00 balance on the free plan, remaining credits, and cost by project.
Activating advanced features
If you reach the point where you need multiple Regions, or governance features like custom policies in AWS Organizations, you can activate advanced features at no additional cost. You’ll find yourself in a fully configured AWS Organization built according to best practices, with no migration and no downtime. Everything you configured previously is preserved and reflected in the underlying AWS services.
Now rolling out
We’ve heard from builders that they do not want to spend their first hours configuring an AWS environment. They want to build what they came to build, and we listened. AWS began as a place where anyone with an idea could start building, and this new simplified experience brings that starting point back, with sensible defaults so you can begin immediately, and with the global reach, breadth, and depth of AWS still there when your idea needs it. We are gradually rolling this experience out to new customers. We cannot wait to see what you build, and we want your feedback on the experience.
To try the new experience, create a new AWS account. To learn more, see Sign up for AWS (new).
There’s a particular energy to mid-September in New York. Pumpkin spice lattes are flowing, temperatures are dropping, and it’s nearly sweater weather. The city is back at full speed, and so is the AWS launch calendar. This week that energy showed up in a new frontier model on Amazon Bedrock, a desktop app for Amazon Quick, and a reminder that the developers seeing the biggest gains from AI agents aren’t just using better tools — they’re working differently.
Let’s dive in.
Headlines
OpenAI GPT-6 Astra is now generally available on Amazon Bedrock – GPT-6 Astra is OpenAI’s latest and most capable model to date, and you can now run it on Amazon Bedrock. It brings deeper reasoning and judgment, professional-quality writing and design, and advanced computer and browser use to demanding business workflows. The model supports a context window of up to 1 million input tokens, so you can send it large codebases, long contracts, or extensive document collections and ask it to reconcile competing inputs.

You can call GPT-6 Astra through supported Amazon Bedrock APIs, or configure ChatGPT Work and Codex to use the model on Amazon Bedrock. Alongside the launch, OpenAI is introducing new enterprise plugins for ChatGPT Work that extend Astra’s browser-use capabilities across common business applications. Established AWS controls help you secure workloads, govern access, and audit model invocation activity, and your inference data isn’t used for model training. Read more
Last week’s launches
Here are some launches and updates from this past week that caught my attention:
For a full list of AWS announcements, be sure to keep an eye on the What’s New with AWS page.
Other AWS news
Here are some additional posts and resources that you might find interesting:
pnpm create @aws/nx-workspace and point your coding agent at the included MCP server.For a full list of AWS blog posts, be sure to keep an eye on the AWS Blogs page.
Upcoming AWS events
Check your calendar and sign up for upcoming AWS events:
Join the AWS Builder Center to connect with builders, share solutions, and access content that supports your development. Browse here for upcoming AWS-led in-person and virtual events and developer-focused events.
That’s all for this week. Check back next Monday for another Weekly Roundup!
— Micah
This post is part of our Weekly Roundup series. Check back each week for a quick roundup of interesting news and announcements from AWS!
Last year, we introduced Volume Clones of Amazon Elastic Block Store (Amazon EBS), a new capability that lets you create instant point-in-time copies of your EBS volumes within the same Availability Zone.
Today, we are extending Volume Clones with cross-account copy, so you can create copies of your EBS volumes into other AWS accounts and optionally re-encrypt them with an AWS Key Management Service (AWS KMS) key in the target account.
With this new feature, you can use your latest application data to develop, test, and experiment in a secondary environment, while protecting and isolating the information in the production environment. For example, you can create copies of a production environment to refresh test and development environments set up in separate accounts with the desired EBS encryption.
Copy EBS volumes across AWS accounts in action
To create a copy of an EBS volume across accounts, the owners of the volume can first grant the target account access to their volume in AWS Resource Access Manager (RAM), which provides a way to share resources across AWS accounts or within an AWS Organization. Then, from the target account, they can locate the volume they have access to create a copy of it.
To get started, choose Share volume for the volume you want to share with the target account in the Amazon EBS console.

Share the volume with other AWS accounts by adding it to existing resource shares, or create a new resource share in the AWS RAM console. For more details, refer to the AWS RAM User Guide.

You can now see confirmation that the volume has been shared in the Volume sharing tab of the volume detail page.

A target account must accept the resource share on the RAM console.

Once they accept the resource share, they can see the volumes in the EBS volume page of the target account. Choose Copy volume for any shared volume.

To share and copy EBS volumes across AWS accounts programmatically, including calling APIs and searching documentation, try the AWS MCP Server and plugins with your preferred AI coding tool. To learn more, visit the Amazon EBS User Guide.
Things to know
Let me share some important technical details that I think you’ll find useful.
SharedVolumeCopyInitiated through AWS CloudTrail event in your account. You will also receive events in Amazon EventBridge at the start of the copy operation when the state of the copied volume is initializing, and at the end of the operation when the state of the copied volume changes to completed. You can see the shared volume ID, consuming account ID, and event time.use1-az1) to identify the same physical location across accounts.Now available
Cross-account volume clones for Amazon EBS are available in all AWS Regions that support Amazon EBS Volume Clones. For Regional availability and a future roadmap, visit the AWS Capabilities by Region.
Give this feature a try in the Amazon EC2 console today and send feedback to AWS re:Post for Amazon EBS or through your usual AWS Support contacts.
— Channy

Last week, Claude Fable 5.1 became available on AWS. According to Anthropic, Claude Fable 5.1 delivers frontier intelligence for ambitious tasks across coding, scientific research, and enterprise workflows. Claude Fable 5.1 is built for long-running, high-stakes work that runs for hours and spans many applications. It can own more of a software project on its own, handling features across an entire codebase, code review, and performance work over extended sessions.

Anthropic has designated Fable 5.1 a Covered Model, a category of Claude models that carry additional data retention, safety review, and access policies wherever they’re offered. Claude Fable 5.1 is subject to data retention for up to 30 days and human review by Amazon personnel, with a new aws_review data retention mode. In this mode, AWS retains your prompts and outputs for human safety review within the AWS boundary. The provider_data_share mode is legacy, and Amazon Bedrock does not share your data with the model provider. In addition, Enterprise Frontier Safeguards (EFS), built in partnership between AWS and Anthropic, will let eligible customers use Covered Models while keeping their data in a cloud environment they control.
You have two ways to access Claude Fable 5.1: Amazon Bedrock and Claude Platform on AWS. To learn more, see the Claude Fable 5.1 model card on Amazon Bedrock and Claude Platform on AWS.
Last week’s launches
Here are some launches that got my attention:
For a full list of AWS announcements, be sure to keep an eye on the What’s New with AWS page.
Other AWS news
Here are some additional projects and news items you may find interesting:
For a full list of AWS blog posts, be sure to keep an eye on the AWS Blogs page.
Learn more about AWS, browse and join upcoming AWS-led in-person and virtual events, startup events, and developer-focused events including AWS re:Invent, AWS Summits, and AWS Community Days. Join the AWS Builder Center to connect with builders, share solutions, and access content that supports your development.
That is all for this week. Check back next Monday for another Weekly Roundup!
— Channy
Today, Amazon EC2 R9g and R9gd instances are generally available, powered by AWS Graviton5 processors. R9g instances are memory-optimized and deliver up to 25% better compute performance compared to Graviton4-based R8g instances, powered by the most energy efficient processor AWS has ever built.
R9g instances are ideal for memory-intensive workloads including databases, in-memory caches (Valkey, Redis, MemCached), real-time big data analytics, Linux-based workloads including containerized and micro-service-based applications (e.g. Kubernetes, Docker, EKS, ECS), as well as applications written in popular programming languages such as C/C++, Rust, Go, Java, Python, .NET Core, Node.js, Ruby, and PHP.
R9gd instances include local NVMe-based SSD block-level storage, ideal for memory-intensive workloads requiring fast, low-latency local storage such as open-source databases, distributed real-time big data analytics, large in-memory databases, and large caching workloads.
If you’re running workloads on R8g instances today, R9g gives you more performance per vCPU with faster memory, higher network and Amazon EBS bandwidth, and a larger L3 cache, all while using less energy.
What makes R9g different
Graviton5 processors bring several hardware improvements over Graviton4:
R9g and R9gd instances support Instance Bandwidth Configuration (IBC), which lets you adjust the allocation of bandwidth between Amazon EBS and Amazon VPC networking by 25%. This helps optimize performance for workloads with specific bandwidth requirements such as databases and caching.
All R9g and R9gd instances run on the AWS Nitro System, which offloads virtualization, storage, and networking to dedicated hardware. This gives your applications near-bare-metal performance while maintaining strong security isolation between instances.
R9g and R9gd instances feature the Nitro Isolation Engine (NIE), the same enhancement to the Nitro System introduced with C9g and M9g instances earlier this year, which enforces isolation of instances and harnesses formal verification to provide assurances of isolation with mathematical precision. Nitro Isolation Engine is a purpose-built component that is responsible for enforcing isolation between virtual machines, including mediation of all access to virtual machine memory, CPU register state, and I/O devices through a minimal set of APIs. Nitro Isolation Engine leverages formal verification, a technique to mathematically demonstrate that the hardware or software behaves as intended, and not just in specific test cases. This intensive verification technique establishes Nitro as the first formally verified cloud hypervisor, pioneering a new standard for mathematically proven cloud security. To learn more about the Nitro Isolation Engine, visit the blog post. For details on the formal verification results, including scope and assumptions, see the technical white paper.
EC2 R9g and R9gd instance specifications
R9g and R9gd instances are each available in 11 sizes, from medium to metal-48xl. The following tables show the full specifications for each size.
| Instance size | vCPUs | Memory (GiB) | Instance Storage | Network Bandwidth (Gbps) | EBS Bandwidth (Gbps) |
| r9g.medium | 1 | 8 | EBS-Only | Up to 15 | Up to 12 |
| r9g.large | 2 | 16 | EBS-Only | Up to 15 | Up to 12 |
| r9g.xlarge | 4 | 32 | EBS-Only | Up to 15 | Up to 12 |
| r9g.2xlarge | 8 | 64 | EBS-Only | Up to 17 | Up to 12 |
| r9g.4xlarge | 16 | 128 | EBS-Only | Up to 17 | Up to 12 |
| r9g.8xlarge | 32 | 256 | EBS-Only | 17 | 12 |
| r9g.12xlarge | 48 | 384 | EBS-Only | 25 | 18 |
| r9g.16xlarge | 64 | 512 | EBS-Only | 34 | 24 |
| r9g.24xlarge | 96 | 768 | EBS-Only | 50 | 36 |
| r9g.48xlarge | 192 | 1536 | EBS-Only | 100 | 72 |
| r9g.metal‑48xl | 192 | 1536 | EBS-Only | 100 | 72 |
R9gd instances offer the same compute and networking performance as R9g, with the addition of local NVMe-based SSD storage for workloads that need fast, low-latency scratch space or temporary caches.
| Instance size | vCPUs | Memory (GiB) | Instance Storage (NVMe SSD) | Network Bandwidth (Gbps) | EBS Bandwidth (Gbps) |
| r9gd.medium | 1 | 8 | 1 x 59 GB | Up to 15 | Up to 12 |
| r9gd.large | 2 | 16 | 1 x 118 GB | Up to 15 | Up to 12 |
| r9gd.xlarge | 4 | 32 | 1 x 237 GB | Up to 15 | Up to 12 |
| r9gd.2xlarge | 8 | 64 | 1 x 474 GB | Up to 17 | Up to 12 |
| r9gd.4xlarge | 16 | 128 | 1 x 950 GB | Up to 17 | Up to 12 |
| r9gd.8xlarge | 32 | 256 | 1 x 1900 GB | 17 | 12 |
| r9gd.12xlarge | 48 | 384 | 3 x 950 GB | 25 | 18 |
| r9gd.16xlarge | 64 | 512 | 1 x 3800 GB | 34 | 24 |
| r9gd.24xlarge | 96 | 768 | 3 x 1900 GB | 50 | 36 |
| r9gd.48xlarge | 192 | 1536 | 3 x 3800 GB | 100 | 72 |
| r9gd.metal‑48xl | 192 | 1536 | 3 x 3800 GB | 100 | 72 |
Getting started
You can launch R9g and R9gd instances from the Amazon EC2 console using any supported Arm-based AMI. R9g instances support Amazon Linux 2023, Amazon Linux 2, Ubuntu 22.04+, RHEL 8.4+, SUSE Linux Enterprise Server 15 SP3+, Debian 12+, and other major Linux distributions.
If you’re migrating from R8g, no code changes are required for most applications. Select the equivalent R9g instance size and your application runs with better performance. For containerized workloads, R9g works with Amazon EKS, Amazon ECS, and standard Kubernetes deployments. Multi-arch container images built for Arm64 run without changes.
Several resources help you get started: the AWS Graviton Getting Started Guide covers how to build, run, and optimize workloads on Graviton-based instances. The Graviton Savings Dashboard helps you track cost savings. AWS Transform automates code transformations for migrating Java applications from x86 to Graviton. To learn more, visit AWS Graviton Processors or Level up your compute with AWS Graviton.
Pricing and availability
Amazon EC2 R9g and R9gd instances are available in US East (N. Virginia, Ohio), US West (Oregon), and Europe (Frankfurt) Regions.
R9g and R9gd instances are available for purchase through Savings Plans, On-Demand, Spot Instances, Dedicated Instances, or Dedicated Hosts. For detailed pricing, visit the Amazon EC2 pricing page.
Ready to get started? Launch R9g instances from the Amazon EC2 console. For more details, visit the Amazon EC2 R9g instances page.
If you want to call APIs, search documentation, find regional availability, and check troubleshooting about this feature, try using the AWS MCP Server and plugins with your preferred AI tool. Share your feedback on AWS re:Post for Amazon EC2 or reach out through your usual AWS Support contacts.
— Daniel Abib
The news that interested me the most last week was the DuckLabs acquisition. AWS has signed a definitive agreement to acquire DuckLabs, the Amsterdam-based company behind DuckDB, the popular open source analytical database that runs in-process and executes SQL directly against files like Parquet, CSV, and JSON. DuckDB stays open source under its independent foundation and the MIT license, and over time AWS plans to combine its speed at everyday queries with the enterprise scale of services like Amazon S3, Amazon Redshift, and Amazon Athena.

Co-founded by Hannes Mühleisen and Mark Raasveldt, DuckDB runs locally or on Amazon S3, which makes it remarkably fast for the everyday queries (a terabyte or less) that make up the bulk of real-world analytics. It also happens to pair beautifully with AI agents, which “poke” and experiment their way through data much like humans do. The co-founders will continue leading its technical direction while AWS combines DuckDB’s speed with analytics services like Amazon EMR, AWS Glue, and Amazon SageMaker. For the bigger picture on why this matters, Andy Warfield, Vice President and Distinguished Engineer shared his thoughts on the post DuckDB and the changing physics of analytics on All Things Distributed.
Now, let’s get into this week’s AWS news…
Last week’s launches
Here are some launches and updates from this past week that caught my attention:
AGENT_CONNECTIVITY health event across AWS Fargate, Amazon ECS Managed Instances, and Amazon ECS on EC2. On Fargate and Managed Instances, ECS handles recovery automatically, draining tasks, launching replacements, and deregistering the impaired instance. On EC2, you can wire the event into your own workflow. Available at no additional cost in all AWS Commercial and AWS GovCloud (US) Regions.For a full list of AWS announcements, be sure to keep an eye on the What’s New with AWS page.
Other AWS news
Here are some additional posts and resources that you might find interesting:
m1.small instance type in one Region to more than 1,200 instance types across 39 Regions, along with the custom silicon journey from the first Graviton to Graviton5 and Trainium3. A fun and worthwhile read on the service that still underpins so much of AWS – including Amazon ECS, Amazon EKS, AWS Lambda, Amazon SageMaker, and Amazon Bedrock.aws configure agent-toolkit) now equips AI coding agents like Kiro, Claude Code, Codex, and Cursor with curated, up-to-date AWS knowledge and a secure connection to thousands of AWS APIs through the AWS MCP Server. If you build with an AI coding assistant, this helps it choose the right services, use modern APIs, and follow security best practices – so it gets AWS code right more often the first time.Upcoming AWS events
Check your calendar and sign up for upcoming AWS events:
Join the AWS Builder Center to connect with builders, share solutions, and access content that supports your development. Browse here for upcoming AWS-led in-person and virtual events and developer-focused events.
That’s all for this week. Check back next Monday for another Weekly Roundup!
— Daniel Abib
This post is part of our Weekly Roundup series. Check back each week for a quick roundup of interesting news and announcements from AWS!

Twenty years ago today, Jeff Barr wrote a blog post that launched the Amazon EC2 Beta. That single post introduced resizable Linux virtual servers in the cloud, billed by the hour, with one instance type (m1.small) in one Region (US East). It was minimal yet useful, and it changed how the world thinks about computing infrastructure.
In 2021, Jeff covered the fifteen years of EC2 with the backstory and memorable EC2 launches. Over the last five years, AWS has continued to push the boundaries of what cloud computing can deliver, building custom silicon for general-purpose and AI workloads and expanding EC2 into new form factors and deployment models that our customers in 2006 could not have imagined.
The 20 years in brief
In his 15th anniversary post, Jeff chose important milestones of EC2 that established the foundational building blocks that customers still rely on today. Amazon Elastic Block Store (2008) provided persistent block storage. Elastic Load Balancing, Auto Scaling, and Amazon CloudWatch (2009) made applications scalable and highly available. Amazon Virtual Private Cloud (2009) gave customers logically isolated networks. AWS Nitro System (2017) enabled faster innovation and enhanced security. AWS Graviton processors (2018) were designed for cost-sensitive scale-out workloads.
Over 20 years, EC2 grew from one to over 1,200 instance types to meet customer needs across general-purpose, compute-, memory-, and storage-optimized, accelerated computing, and high-performance computing families. These instances expanded from one AWS Region to 39 Regions globally. AWS also extended EC2 beyond the Region boundary with AWS Outposts (2018) running EC2 instances locally, AWS Local Zones (2019) place globally, and AWS Wavelength (2019) inside global 5G telecommunications carrier networks.

While I hate to play favorites, I want to choose some of my favorite EC2 launches of the past five years:
The foundation underneath it all
Despite two decades of innovation, the fundamental value proposition of Amazon EC2 has not changed. Customers use it to get secure, resizable compute capacity in minutes, pay only for what they consume, and scale on demand without long-term commitments. That same flexibility now extends to AI workloads at a scale no one anticipated in 2006.
EC2 remains the foundational compute layer of AWS. Amazon ECS, Amazon EKS, AWS Lambda, AWS Fargate, AWS Batch, Amazon EMR, Amazon SageMaker AI, and Amazon Bedrock ultimately run on EC2 capacity. Every architectural pattern customers have built over the past twenty years, from simple web servers to trillion-parameter foundation model training clusters, starts with a decision to launch an instance.
We made strong foundational decisions in 2006, and we left room for the service to grow. Twenty years later, that strategy of creating services that are minimal-yet-useful, launching quickly, and iterating rapidly in response to your feedback continues to guide how we build. The next twenty years of cloud computing will demand capabilities we have not yet imagined. Amazon EC2 will continue to be the foundation where your workloads run.
To learn more about Amazon EC2, visit the Amazon EC2 product page or check out what’s new with EC2.
— Channy
During my time at AWS, I have always looked for opportunities to work with students. I have delivered over 50 talks at universities across the region, and watching the potential in the room is always a strong motivator. It reminds me of why I do this work, and that the students I meet today may well become our customers and collaborators tomorrow. That is why I am happy to open this week with Student Rewards on AWS Builder Center.

Rick Suttles published Introducing Student Rewards on AWS Builder Center, a new benefit for verified higher education students. When you verify your enrollment through SheerID and complete your Builder Center profile, you unlock 12 months of premium AWS Skill Builder access (900+ courses, hands-on labs, certification exam prep, and game-based learning). From there, you earn badges through actions on Builder Center: publishing articles, commenting, and maintaining engagement. At 7 badges, you unlock $10 in AWS Credits. At 14 badges, another $20 in credits. At 21 badges, you earn an AWS Foundational Certification exam voucher ($100 value).
This represents a commitment of over $500 million in resources during this back-to-school season, providing students with the training, tools, and certification needed to start building their careers in cloud and AI. Student Rewards is available to students 18 years or older and enrolled at accredited higher education institutions worldwide, subject to verification and applicable terms.
Verify your student status and start learning, earning badges, and unlocking rewards!
Last week’s launches
Here’s what else happened this week.
TerminateInstanceInAutoScalingGroup API to terminate them as a batch, reducing the number of API calls needed to scale down your Auto Scaling groups. Batch termination is designed for workloads that need to rapidly scale down, such as AI/ML training jobs, container orchestrators, or event-driven architectures that spin up large fleets temporarily.For a full list of AWS announcements, be sure to keep an eye on the What’s New with AWS page.
Other AWS news
Here are some additional posts you may find useful:
For a full list of AWS blog posts, be sure to keep an eye on the AWS Blogs page.
Upcoming AWS events
Check your calendar and sign up for upcoming AWS events:
Visit the AWS Builder Center to meet other builders, contribute solutions, and find resources that help you keep building.
Summer is slowly coming to an end, and I am already planning a few days off in the coming months to keep me motivated through the rainy autumn ahead. I hope you are doing the same. Come back next week for more!
— Esra