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).

The post AWS reimagines the getting started experience appeared first on The NOKIA Blog.

In my last Week in Review post, I shared what I’d been hearing from customers in the AI-Driven Development Lifecycle (AI-DLC) workshops I’ve been delivering. Last week I was back at it, this time in Denver for a two-day AI-DLC workshop, where I helped facilitate 17 teams to deliver nearly 20 separate use cases in just two days. The pace of acceleration that AI-DLC unlocks—especially when paired with tools like Claude Code on Amazon Bedrock—is fundamentally changing how businesses operate. Traditional roles within software development teams are collapsing into smaller, AI-augmented squads, and the paradigm shift is beginning to take place right in front of us. To learn more about how to utilize various AI tools, visit the GitHub repository of AI-DLC workflow.

This shift is also reshaping how AWS account teams (solutions architects, customer solutions managers, and technical account managers) collaborate with customers. It’s becoming less about handing off advisory design documents and more about building alongside them in real time. It’s a genuinely exciting moment to be in the middle of the change, and this week’s headline launch — Anthropic’s most capable model yet, now on AWS — is going to push that pace even further.

Now, let’s get into this week’s AWS news…

Headlines

Claude Opus 4.8 on AWS — Anthropic’s most capable generally available model is now accessible through both Amazon Bedrock and the Claude Platform on AWS. Opus 4.8 is built for agentic coding, knowledge work, and extended autonomous task execution — it sustains longer autonomous sessions with deeper reasoning, recovers from errors, and synthesizes information across lengthy documents. For coding workloads, it reads codebases like an engineer, plans before it edits, and holds context across long sessions. On Amazon Bedrock, you get AWS-managed features like Guardrails, Knowledge Bases, and data residency; on the Claude Platform on AWS, you get Anthropic’s native APIs unified with AWS billing. To learn more, visit the deep-dive blog post.

Last week’s launches

Here are some launches and updates from this past week that caught my attention:

• Introducing the next generation of AWS Resilience Hub — A reimagined Resilience Hub gives SREs and developers a unified framework to define resilience standards, evaluate applications against them, and demonstrate compliance across an entire portfolio. It introduces modular resilience policies (covering service-level objectives (SLOs), multi-AZ/Region DR, and data recovery), business-oriented application modeling, generative AI-powered assessments aligned with the Well-Architected and Resilience Analysis Frameworks, and automatic dependency discovery via DNS query log analysis. Integration with AWS Organizations enables organization-wide resilience management from a single delegated administrator account.
• Introducing the next generation of Amazon OpenSearch Serverless for building agentic AI applications — Amazon OpenSearch Serverless is now a fully managed search and vector engine purpose-built for agentic AI applications. It scales from zero to thousands of requests per second—roughly 20x faster than the prior generation—delivers up to 60% cost savings versus peak-provisioned clusters, and adds GPU acceleration plus new SEARCH and VECTORSEARCH collection types. Native integrations with Vercel, Kiro, Claude Code, and Cursor through OpenSearch Agent Skills make it straightforward to plug into your agent stack.
• New assessment capabilities in AWS Transform — AWS Transform expands with new tools to help you build migration business cases and evaluate TCO before moving workloads to AWS. You can ingest data from RVTools exports, CMDB data, the AWS Transform discovery tool, and third-party discovery tools, then run what-if scenarios across region, utilization, and service mapping for EC2, FSx, S3, SQL Server on EC2, and virtual desktops. The release also adds Agentic Readiness Analysis (ARA) and Modernization Analysis (MODA), which scan code repositories in 5 to 30 minutes per repo to surface severity-tagged findings with file-level evidence and AWS-mapped remediation guidance.
• Amazon Aurora MySQL with Kiro Powers — Aurora MySQL now integrates with Kiro Powers, drawing from a curated repository of pre-packaged MCP servers, steering files, and hooks validated by Kiro partners. Developers can execute both data plane tasks (queries, schema management) and control plane tasks (cluster management) in natural language, with dynamic guidance for Aurora MySQL Serverless scaling, RDS-to-Aurora migration, and replication setup. The companion Database Blog post explains how the agent produces the API calls, SQL, and configuration for you to review and run — available via one-click install from the Kiro IDE or webpage.
• Amazon WorkSpaces Applications now supports Windows Desktop OS — You can now bring your own Windows Desktop licenses to Amazon WorkSpaces Applications and stream full Windows desktops and applications from AWS-hosted dedicated hardware. BYOL eliminates OS fees (you pay only for compute and streaming infrastructure), supports eligible Microsoft 365 Apps for enterprise, and gives users a matching experience between local and remote environments — same workflows, shortcuts, and navigation in both.

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:

• Meet our newest AWS Heroes — May 2026 — An AWS Builder Center post introducing the latest cohort of AWS Heroes recognized for their contributions to the global AWS community.
• AI-native, full-stack web apps with Vercel and AWS databases — Database blog post on the new Vercel and AWS Databases integration, which lets you provision Aurora PostgreSQL, DynamoDB, or Aurora DSQL directly from the Vercel dashboard or via v0. The post also highlights the H0 hackathon with $160,000 in prizes for building full-stack apps on this stack.
• Introducing US-based, US citizen 24/7 technical support for AWS GovCloud (US) customers: Your mission never sleeps. Neither do we. — Public Sector blog post announcing that all AWS GovCloud (US) technical support cases are now automatically routed to US-based, US citizen engineers around the clock — no opt-in required — for government agencies, contractors, nonprofits, and academic institutions running mission-critical workloads.

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 as well as 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’s all for this week. Check back next Monday for another Weekly Roundup!

-Micah

The post AWS Weekly Roundup: Claude Opus 4.8 on AWS, Aurora MySQL with Kiro Powers, and more (June 1, 2026) appeared first on The NOKIA Blog.

Today, we’re announcing the next generation of AWS Resilience Hub with a significantly expanded experience that brings together a new application model, dependency discovery assessment, generative AI-powered failure mode analysis, modular resilience policies, and organization-wide reporting.

Organizations running hundreds of applications share a common challenge: availability is a top concern, yet there is no consistent way to set resilience goals, measure progress, or prove compliance across a portfolio. Teams set different standards, use different tools, and struggle to exchange information about whether applications actually meet expectations.

The next generation of AWS Resilience Hub changes this by giving Site Reliability Engineers (SREs) and development teams a structured way to align on resilience policy expectations, help application teams achieve them, and demonstrate compliance through testing. With integration into AWS Organizations, teams can now evaluate resilience at scale, identify failure modes, discover hidden dependencies, and report on progress across the enterprise.

The next generation of Resilience Hub walks you through your resilience journey and to help you there are the following concepts built into it.

• Resilience policy: You can define your resilience expectations through modular, composable requirements. Rather than choosing a single rigid policy type, you construct policies by selecting the requirements that matter to your application, such as service level objective (SLO), multi-AZ and multi-Region disaster recovery, and data recovery requirements.
• Business-level understanding: You can use new application modeling through critical end-user paths that map directly to business outcomes. Systems represent a business application, user journeys describe critical business paths, and services are the deployable units comprising AWS resources, code, and observability. Resilience Hub automatically discovers and maps them into a topology showing how resources connect.
• AI failure mode assessments: You can run generative AI-powered assessments that analyze your services against your defined resilience policies, AWS Well-Architected best practices, and the AWS Resilience Analysis Framework. These assessments identify potential failure modes and provide actionable recommendations.
• Dependency discovery assessment: You can automatically discover AWS services, internal endpoints, and third-party endpoints that your services depend on. This dependency assessment uses DNS query log analysis to identify dependencies you may not know about—including unexpected cross-region calls or critical third-party dependencies.

The next generation of AWS Resilience Hub in action

To get started, you configure a resilience policy, set up your first system and service, run a failure mode assessment, review the results, and implement the findings.

Before you begin, you should set up the invoker IAM role, which grants Resilience Hub read-only access to your AWS resources, cross-account roles (if not using AWS Organizations), or service-linked roles (SLRs) with AWS Organizations. Resilience Hub also integrates with AWS Organizations to enable organization-wide resilience management from a single delegated administrator account. This eliminates the need to log in to individual accounts to assess resilience posture across your enterprise. To learn more, visit For prerequisite details in the AWS Resilience Hub User Guide.

To configure a resilience policy, choose Create policy in the Policies menu through the AWS Resilience Hub console. Enter a policy name, description, and choose resilience requirements. For example, you can create a reusable policy for multi-Region disaster recovery used in financial applications—including 99.95% availability SLO, 15-minutes RTO, 5-minutes RPO for multi-Region disaster recovery, and disaster recovery approach that aligns with your RTO and RPO requirements.

If you choose data recovery requirements, you can define the data recovery time objective for restoring from backups for each service associated with this policy.

To create your first system representing your business application, choose Create a system in the Systems menu. Optionally, you can enable AWS Organizations account access for this system.

Now you can create a service that represents a deployable unit, like one of your microservices, and associate it with your system, and tell Resilience Hub where to find your resources. Enter a service name, for example, stock-exchange-service, choose your resilience policy and invoker AWS IAM role name. You can choose service Regions, service resources such as your resource tags, AWS CloudFormation stack, Terraform state file location, or Amazon EKS cluster and namespace.

When you enable dependency discovery for this service, AWS examines your VPC query logs for the VPCs associated with the resources in your service. You can disable this feature anytime from the dependency discovery settings in the service details page.

Now, you can run your first assessment with the service creation complete and a policy applied. Choose Run failure mode assessment in your service page and wait for the assessment to complete.

During the assessment, Resilience Hub assumes your invoker role, reads resources from your configured input sources, identifies parent-child relationships, queries the application topology service to map connections between resources, and builds a topology showing data flow, containment, and permissions.

By choosing Service topology, you can see service resources grouped by service functions in the graph, table, or JSON format.

By choosing Failure mode guidance, you can add assertions used to guide the agents while performing the failure mode assessment. Assertions are either generated by the agent or added by users. You can update them to improve assessment accuracy.

Once the assessment is complete, you can review findings and recommendations in the Assessment tab of your service page. Each finding tells you what the failure mode is, why it matters for your architecture, how to fix it, and which policy requirement it relates to.

You can choose Mark as resolved to implement the recommendation or Mark as irrelevant if the finding doesn’t apply to your use case.

If you’re an existing Resilience Hub customer, Resilience Hub provides migration APIs to simplify the transition of your previous applications. These APIs convert your previous assessment policies to new resilience policies, map your previous applications to the new model, such as multiple related applications to one system with multiple services.

For more information about new features, visit the AWS Resilience Hub User Guide.

Now available

The next generation of AWS Resilience Hub is now generally available in AWS commercial Regions where Resilience Hub is available. For Regional availability and the future roadmap, visit the AWS Capabilities by Region.

Resilience Hub uses a new service-based pricing model. Pricing includes two failure mode assessments per month for services, and optionally automated dependency assessment. You can try AWS Resilience Hub free. For pricing details, visit the AWS Resilience Hub pricing page.

Give the new AWS Resilience Hub a try in the Resilience Hub console and send feedback to AWS re:Post for Resilience Hub or through your usual AWS Support contacts.

— Channy

The post Introducing the next generation of AWS Resilience Hub for generative AI-based SRE resilience journey appeared first on The NOKIA Blog.

Today, we’re announcing the general availability of cross-account safeguards in Amazon Bedrock Guardrails, a new capability that enables centralized enforcement and management of safety controls across multiple AWS accounts within an organization.

With this new capability, you can specify a guardrail in a new Amazon Bedrock policy within the management account of your organization that automatically enforces configured safeguards across all member entities for every model invocation with Amazon Bedrock. This organization-wide implementation supports uniform protection across all accounts and generative AI applications with centralized control and management. This capability also offers flexibility to apply account-level and application-specific controls depending on use case requirements in addition to organizational safeguards.

• Organization-level enforcements apply a single guardrail from your organization’s management account to all entities within the organization through policy settings. This guardrail automatically enforces filters across all member entities, including organizational units (OUs) and individual accounts, for all Amazon Bedrock model invocations.
• Account-level enforcement enables automatic enforcement of configured safeguards across all Amazon Bedrock model invocations in your AWS account. The configured safeguards in the account-level guardrail apply to all inference API calls.

You can now establish and centrally manage dependable, comprehensive protection through a single, unified approach. This supports consistent adherence to corporate responsible AI requirements while significantly reducing the administrative burden of monitoring individual accounts and applications. Your security team no longer needs to oversee and verify configurations or compliance for each account independently.

Getting started with centralized enforcement in Amazon Bedrock Guardrails

You can get started with account-level and organization-level enforcement configuration in the Amazon Bedrock Guardrails console. Before the enforcement configuration, you need to create a guardrail with a particular version to support the guardrail configuration remains immutable and cannot be modified by member accounts and complete prerequisites for using the new capability such as resource-based policies for guardrails.

To enable account-level enforcement, choose Create in the section of Account-level enforcement configurations.

You can choose the guardrail and version to automatically apply to all Bedrock inference calls from this account in this Region. With general availability, we introduce the new feature defining which models will be affected by the enforcement with either Include or Exclude behavior.

You can also configure selective content guarding controls for system prompts and user prompts with either Comprehensive or Selective.

• Use Comprehensive when you want to enforce guardrails on everything, regardless of what the caller tags. This is the safer default when you don’t want to rely on callers to correctly identify sensitive content.
• Use Selective when you trust callers to tag the right content and want to reduce unnecessary guardrail processing. This is useful when callers handle a mix of pre-validated and user-generated content, and only need guardrails applied to specific portions.

After creating the enforcement, you can test and verify enforcement using a role in your account. The account-enforced guardrail should automatically apply to both prompts and outputs.

Check the response for guardrail assessment information. The guardrail response will include enforced guardrail information. You can also test by making a Bedrock inference call using InvokeModel, InvokeModelWithResponseStream, Converse, or ConverseStream APIs.

To enable organization-level enforcement, go to AWS Organizations console and choose Policies menu. You can enable the Bedrock policies in the console.

You can create a Bedrock policy that specifies your guardrail and attach it to your target accounts or OUs. Choose Bedrock policies enabled and Create policy. Specify your guardrail ARN and version and configure the input tags setting for in the AWS Organizations. To learn more, visit Amazon Bedrock policies in AWS Organizations and Amazon Bedrock policy syntax and examples.

After creating the policy, you can attach the policy to your desired organizational units, accounts, root in the Targets tab.

Search and select your organization root, OUs, or individual accounts to attach your policy, and choose Attach policy.

You can test that the guardrail is being enforced on member accounts and verify which guardrail is enforced. From a member account attached, you should see the organization enforced guardrail under the section Organization-level enforcement configurations.

The underlying safeguards within the specified guardrail are then automatically enforced for every model inference request across all member entities, ensuring consistent safety controls. To accommodate varying requirements of individual teams or applications, you can attach different policies with associated guardrails to different member entities through your organization.

Things to know

Here are key considerations to know about GA features:

• You can now choose to include or exclude specific models in Bedrock for inference, enabling centralized enforcement on model invocation calls. You can also choose to safeguard partial or complete system prompts and input prompts. To learn more, visit Apply cross-account safeguards with Amazon Bedrock Guardrails enforcement.
• Ensure you are specifying the accurate guardrail Amazon Resource Names (ARN) in the policy. Specifying an incorrect or invalid ARN will result in policy violations, non-enforcement of safeguards, and the inability to use the models in Amazon Bedrock for inference. To learn more, visit Best practices for using Amazon Bedrock policies.
• Automated Reasoning checks are not supported with this capability.

Now available

Cross-account safeguards in Amazon Bedrock Guardrails is generally available today in the all AWS commercial and GovCloud Regions where Bedrock Guardrails is available. For Regional availability and a future roadmap, visit the AWS Capabilities by Region. Charges apply to each enforced guardrail according to its configured safeguards. For detailed pricing information on individual safeguards, visit Amazon Bedrock Pricing page.

Give this capability a try in the Amazon Bedrock console and send feedback to AWS re:Post for Amazon Bedrock Guardrails or through your usual AWS Support contacts.

— Channy

The post Amazon Bedrock Guardrails supports cross-account safeguards with centralized control and management appeared first on The NOKIA Blog.

As many of you are, I’m a parent. And like you, I think about the world I’m building for my children. That’s part of why today’s launch matters for many of us. I’m excited to announce the launch of the AWS Sustainability console, a standalone service that consolidates all AWS sustainability reporting and resources in one place.

With the The Climate Pledge, Amazon set a goal in 2019 to reach net-zero carbon across our operations by 2040. That commitment shapes how AWS builds its data centers and services. In addition, AWS is also committed to helping you measure and reduce the environmental footprint of your own workloads. The AWS Sustainability console is the latest step in that direction.

The AWS Sustainability console builds on the Customer Carbon Footprint Tool (CCFT), which lives inside the AWS Billing console, and introduces a new set of capabilities for which you’ve been asking.

Until now, accessing your carbon footprint data required billing-level permissions. That created a practical problem: sustainability professionals and reporting teams often don’t have (and shouldn’t need) access to cost and billing data. Getting the right people access to the right data meant navigating permission structures that weren’t designed with sustainability workflows in mind. The AWS Sustainability console has its own permissions model, independent of the Billing console. Sustainability professionals can now get direct access to emissions data without requiring billing permissions to be granted alongside it.

The console includes Scope 1, 2, and 3 emissions attributed to your AWS usage and shows you a breakdown by AWS Region, service, such as Amazon CloudFront, Amazon Elastic Compute Cloud (Amazon EC2), and Amazon Simple Storage Service (Amazon S3). The underlying data and methodology haven’t changed with this launch; these are the same as the ones used by the CCFT. We changed how you can access and work with the data.

As sustainability reporting requirements have grown more complex, teams need more flexibility accessing and working with their emissions data. The console now includes a Reports page where you can download preset monthly and annual carbon emissions reports covering both market-based method (MBM) and location-based method (LBM) data. You can also build a custom comma-separated values (CSV) report by selecting which fields to include, the time granularity, and other filters.

If your organization’s fiscal year doesn’t align with the calendar year, you can now configure the console to match your reporting period. When that is set, all data views and exports reflect your fiscal year and quarters, which removes a common friction point for finance and sustainability teams working in parallel.

You can also use the new API or the AWS SDKs to integrate emissions data into your own reporting pipelines, dashboards, or compliance workflows. This is useful for teams that need to pull data for a specific month across a large number of accounts without setting up a data export or for organizations that need to establish custom account groupings that don’t align with their existing AWS Organizations structure.

You can read about the latest features released and methodology updates directly on the Release notes page on the Learn more tab.

Lets see it in action

To show you the Sustainability console, I opened the AWS Management Console and searched for “sustainability” in the search bar at the top of the screen.

The Carbon emissions section gives an estimate on your carbon emissions, expressed in metric tons of carbon dioxide equivalent (MTCO2e). It shows the emissions by scope, expressed in the MBM and the LBM. On the right side of the screen, you can adjust the date range or filter by service, Regions, and more.

For those unfamiliar: Scope 1 includes direct emissions from owned or controlled sources (for example, data center fuel use); Scope 2 covers indirect emissions from the production of purchased energy (with MBM accounting for energy attribute certificates and LBM using average local grid emissions); and Scope 3 includes other indirect emissions across the value chain, such as server manufacturing and data center construction. You can read more about this in our methodology document, which was independently verified by Apex, a third-party consultant.

I can also use API or AWS Command Line Interface (AWS CLI) to programmatically pull the emissions data.

aws sustainability get-estimated-carbon-emissions 
     --time-period='{"Start":"2025-03-01T00:00:00Z","End":"2026-03-01T23:59:59.999Z"}'

{
    "Results": [
        {
            "TimePeriod": {
                "Start": "2025-03-01T00:00:00+00:00",
                "End": "2025-04-01T00:00:00+00:00"
            },
            "DimensionsValues": {},
            "ModelVersion": "v3.0.0",
            "EmissionsValues": {
                "TOTAL_LBM_CARBON_EMISSIONS": {
                    "Value": 0.7,
                    "Unit": "MTCO2e"
                },
                "TOTAL_MBM_CARBON_EMISSIONS": {
                    "Value": 0.1,
                    "Unit": "MTCO2e"
                }
            }
        },
...

The combination of the visual console and the new API gives you two additional ways to work with your data, in addition to the Data Exports still available. You can now explore and identify hotspots on the console and automate the reporting you want to share with stakeholders.

The Sustainability console is designed to grow. We plan to continue to release new features as we grow the console’s capabilities alongside our customers.

Get started today

The AWS Sustainability console is available today at no additional cost. You can access it from the AWS Management Console. Historical data is available going back to January 2022, so you can start exploring your emissions trends right away.

Get started on the console today. If you want to learn more about the AWS commitment to sustainability, visit the AWS Sustainability page.

— seb

The post Announcing the AWS Sustainability console: Programmatic access, configurable CSV reports, and Scope 1–3 reporting in one place appeared first on The NOKIA Blog.

Twenty years ago this past week, Amazon S3 launched publicly on March 14, 2006. While Amazon Simple Storage Service is often considered the foundational storage service that defined cloud infrastructure, what began as a simple object storage service has grown into something far larger in scope and scale.

As of March 2026, S3 stores more than 500 trillion objects, serves more than 200 million requests per second globally across hundreds of exabytes of data, and the price has dropped to just over 2 cents per gigabyte — an approximately 85% reduction since launch. My colleague Sébastien Stormacq wrote a detailed look at the engineering and the road ahead in Twenty years of Amazon S3 and building what’s next, and if you want to read about those earliest customers and how they shaped what AWS became, I recommend How three startups helped Amazon invent cloud computing and paved the way for AI. Twenty years is worth pausing to celebrate.

Alongside the 20th anniversary of S3, Channy Yun also wrote about a new S3 feature this week: Account regional namespaces for Amazon S3 general purpose buckets. With this feature, you can create general purpose buckets in your own account regional namespace by appending your account’s unique suffix to your requested bucket name, ensuring your desired names are always reserved exclusively for your account. You can enforce adoption across your organization using AWS IAM policies and AWS Organizations service control policies with the new s3:x-amz-bucket-namespace condition key. Read Channy’s post to learn more about account regional namespaces for Amazon S3 general purpose buckets.

This week’s featured launch is one I have a personal connection to: the general availability of Amazon Route 53 Global Resolver. I wrote about the preview of this capability back in December at re:Invent 2025, and I had a great time putting that post together, so I am happy to hear that it’s generally available now.

Amazon Route 53 Global Resolver is an internet-reachable anycast DNS resolver that provides DNS resolution for authorized clients from any location. It is now generally available across 30 AWS Regions, with support for both IPv4 and IPv6 DNS query traffic. Route 53 Global Resolver gives authorized clients in your organization anycast DNS resolution of public internet domains and private domains associated with Route 53 private hosted zones — from any location, not just from within a specific VPC or Region. It also provides DNS query filtering to block potentially malicious domains, domains that are not safe for work, and domains associated with advanced DNS threats such as DNS tunneling and Domain Generation Algorithms (DGA). Centralized query logging is included as well. With general availability, Global Resolver adds protection against Dictionary DGA threats.

Last week’s launches

Here are some of the other announcements from last week:

• Amazon Bedrock AgentCore Runtime now supports stateful MCP server features — Amazon Bedrock AgentCore Runtime now supports stateful Model Context Protocol (MCP) server features, enabling developers to build MCP servers that use elicitation, sampling, and progress notifications alongside existing support for resources, prompts, and tools. With stateful MCP sessions, each user session runs in a dedicated microVM with isolated resources, and the server maintains session context across multiple interactions using an Mcp-Session-Id header. Elicitation enables server-initiated, multi-turn conversations to gather structured input from users during tool execution. Sampling allows servers to request LLM-generated content from the client for tasks such as personalized recommendations. Progress notifications keep clients informed during long-running operations. To learn more, see the Amazon Bedrock AgentCore documentation.
• Amazon WorkSpaces now supports Microsoft Windows Server 2025 — New bundles powered by Microsoft Windows Server 2025 are now available for Amazon WorkSpaces Personal and Amazon WorkSpaces Core. These bundles include security capabilities such as Trusted Platform Module 2.0 (TPM 2.0), Unified Extensible Firmware Interface (UEFI) Secure Boot, Secured-core server, Credential Guard, Hypervisor-protected Code Integrity (HVCI), and DNS-over-HTTPS. Existing Windows Server 2016, 2019, and 2022 bundles remain available. You can use the managed Windows Server 2025 bundles or create a custom bundle and image. This support is available in all AWS Regions where Amazon WorkSpaces is available. For more information, visit the Amazon WorkSpaces FAQs.
• AWS Builder ID now supports Sign in with GitHub and Amazon — AWS Builder ID now supports two additional social login options: GitHub and Amazon. These options join the existing Google and Apple sign-in capabilities. With this update, developers can access their AWS Builder ID profile — and services including AWS Builder Center, AWS Training and Certification, and Kiro — using their existing GitHub or Amazon account credentials, without managing a separate set of credentials. To learn more and get started, visit the AWS Builder ID documentation.
• Amazon Redshift introduces reusable templates for COPY operations — Amazon Redshift now supports templates for the COPY command, allowing you to store and reuse frequently used COPY parameters. Templates help maintain consistency across data ingestion operations, reduce the effort required to execute COPY commands, and simplify maintenance by applying template updates automatically to all future uses. Support for COPY templates is available in all AWS Regions where Amazon Redshift is available, including the AWS GovCloud (US) Regions. To get started, see the documentation or read the Standardize Amazon Redshift operations using Templates blog.

For a full list of AWS announcements, be sure to keep an eye on our News Blog channel the What’s New with AWS page.

Upcoming AWS events

Check your calendar and sign up for upcoming AWS events:

AWS Summits – Join AWS Summits in 2026, free in-person events where you can explore emerging cloud and AI technologies, learn best practices, and network with industry peers and experts. Upcoming Summits include Paris (April 1), London (April 22), and Bengaluru (April 23–24).

AWS Community Days – Community-led conferences where content is planned, sourced, and delivered by community leaders, featuring technical discussions, workshops, and hands-on labs. Upcoming events include Pune (March 21), San Francisco (April 10), and Romania (April 23-24).

AWS at NVIDIA GTC 2026 — Join us at our AWS sessions, booths, demos, and ancillary events in NVIDIA GTC 2026 on March 16 – 19, 2026 in San Jose. You can receive 20% off event passes through AWS and request a 1:1 meeting at GTC.

AWS Community GameDay Europe — Taking place on March 17, 2026, AWS Community GameDay Europe is a team-based, hands-on AWS challenge event running simultaneously across 50+ cities in Europe. Your team is dropped into a broken AWS environment — misconfigured services, failing architectures, and security gaps — and has two hours to fix as much as possible. Find your nearest city and sign up at awsgameday.eu.

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!

— Esra

This post is part of our Weekly Roundup series. Check back each week for a quick roundup of interesting news and announcements from AWS!

The post AWS Weekly Roundup: Amazon S3 turns 20, Amazon Route 53 Global Resolver general availability, and more (March 16, 2026) appeared first on The NOKIA Blog.

Today, we’re announcing a new feature of Amazon Simple Storage Service (Amazon S3) you can use to create general purpose buckets in your own account regional namespace simplifying bucket creation and management as your data storage needs grow in size and scope. You can create general purpose bucket names across multiple AWS Regions with assurance that your desired bucket names will always be available for you to use.

With this feature, you can predictably name and create general purpose buckets in your own account regional namespace by appending your account’s unique suffix in your requested bucket name. For example, I can create the bucket mybucket-123456789012-us-east-1-an in my account regional namespace. mybucket is the bucket name prefix that I specified, then I add my account regional suffix to the requested bucket name: -123456789012-us-east-1-an. If another account tries to create buckets using my account’s suffix, their requests will be automatically rejected.

Your security teams can use AWS Identity and Access Management (AWS IAM) policies and AWS Organizations service control policies to enforce that your employees only create buckets in their account regional namespace using the new s3:x-amz-bucket-namespace condition key, helping teams adopt the account regional namespace across your organization.

Create your S3 bucket with account regional namespace in action

To get started, choose Create bucket in the Amazon S3 console. To create your bucket in your account regional namespace, choose Account regional namespace. If you choose this option, you can create your bucket with any name that is unique to your account and region.

This configuration supports all of the same features as general purpose buckets in the global namespace. The only difference is that only your account can use bucket names with your account’s suffix. The bucket name prefix and the account regional suffix combined must be between 3 and 63 characters long.

Using the AWS Command Line Interface (AWS CLI), you can create a bucket with account regional namespace by specifying the x-amz-bucket-namespace:account-regional request header and providing a compatible bucket name.

$ aws s3api create-bucket --bucket mybucket-123456789012-us-east-1-an 
   --bucket-namespace account-regional 
   --region us-east-1

You can use the AWS SDK for Python (Boto3) to create a bucket with account regional namespace using CreateBucket API request.

import boto3

class AccountRegionalBucketCreator:
    """Creates S3 buckets using account-regional namespace feature."""
    
    ACCOUNT_REGIONAL_SUFFIX = "-an"
    
    def __init__(self, s3_client, sts_client):
        self.s3_client = s3_client
        self.sts_client = sts_client
    
    def create_account_regional_bucket(self, prefix):
        """
        Creates an account-regional S3 bucket with the specified prefix.
        Resolves caller AWS account ID using the STS GetCallerIdentity API.
        Format: ---an
        """
        account_id = self.sts_client.get_caller_identity()['Account']
        region = self.s3_client.meta.region_name
        bucket_name = self._generate_account_regional_bucket_name(
            prefix, account_id, region
        )
        
        params = {
            "Bucket": bucket_name,
            "BucketNamespace": "account-regional"
        }
        if region != "us-east-1":
            params["CreateBucketConfiguration"] = {
                "LocationConstraint": region
            }
        
        return self.s3_client.create_bucket(**params)
    
    def _generate_account_regional_bucket_name(self, prefix, account_id, region):
        return f"{prefix}-{account_id}-{region}{self.ACCOUNT_REGIONAL_SUFFIX}"


if __name__ == '__main__':
    s3_client = boto3.client('s3')
    sts_client = boto3.client('sts')
    
    creator = AccountRegionalBucketCreator(s3_client, sts_client)
    response = creator.create_account_regional_bucket('test-python-sdk')
    
    print(f"Bucket created: {response}")

You can update your infrastructure as code (IaC) tools, such as AWS CloudFormation, to simplify creating buckets in your account regional namespace. AWS CloudFormation offers the pseudo parameters, AWS::AccountId and AWS::Region, making it easy to build CloudFormation templates that create account regional namespace buckets.

The following example demonstrates how you can update your existing CloudFormation templates to start creating buckets in your account regional namespace:

BucketName: !Sub "amzn-s3-demo-bucket-${AWS::AccountId}-${AWS::Region}-an"
BucketNamespace: "account-regional"

Alternatively, you can also use the BucketNamePrefix property to update your CloudFormation template. By using the BucketNamePrefix, you can provide only the customer defined portion of the bucket name and then it automatically adds the account regional namespace suffix based on the requesting AWS account and Region specified.

BucketNamePrefix: 'amzn-s3-demo-bucket'
BucketNamespace: "account-regional"

Using these options, you can build a custom CloudFormation template to easily create general purpose buckets in your account regional namespace.

Things to know

You can’t rename your existing global buckets to bucket names with account regional namespace, but you can create new general purpose buckets in your account regional namespace. Also, the account regional namespace is only supported for general purpose buckets. S3 table buckets and vector buckets already exist in an account-level namespace and S3 directory buckets exist in a zonal namespace.

To learn more, visit Namespaces for general purpose buckets in the Amazon S3 User Guide.

Now available

Creating general purpose buckets in your account regional namespace in Amazon S3 is now available in 37 AWS Regions including the AWS China and AWS GovCloud (US) Regions. You can create general purpose buckets in your account regional namespace at no additional cost.

Give it a try in the Amazon S3 console today and send feedback to AWS re:Post for Amazon S3 or through your usual AWS Support contacts.

— Channy

The post Introducing account regional namespaces for Amazon S3 general purpose buckets appeared first on The NOKIA Blog.

Today we’re expanding Amazon CloudWatch capabilities to unify and manage log data across operational, security, and compliance use cases with flexible and powerful analytics in one place and with reduced data duplication and costs.

This enhancement means that CloudWatch can automatically normalize and process data to offer consistency across sources with built-in support for Open Cybersecurity Schema Framework (OCSF) and Open Telemetry (OTel) formats, so you can focus on analytics and insights. CloudWatch also introduces Apache Iceberg compatible access to your data through Amazon Simple Storage Service (Amazon S3) Tables, so that you can run analytics, not only locally but also using Amazon Athena, Amazon SageMaker Unified Studio, or any other Iceberg-compatible tool.

You can also correlate your operational data in CloudWatch with other business data from your preferred tools to correlate with other data. This unified approach streamlines management and provides comprehensive correlation across security, operational, and business use cases.

Here are the detailed enhancements:

• Streamline data ingestion and normalization – CloudWatch automatically collects AWS vended logs across accounts and AWS Regions, integrating with AWS Organizations from AWS services including AWS CloudTrail, Amazon Virtual Private Cloud (Amazon VPC) Flow Logs, AWS WAF access logs, Amazon Route 53 resolver logs, and pre-built connectors for third-party sources such as endpoint (CrowdStrike, SentinelOne), identity (Okta, Entra ID), cloud security (Wiz), network security (Zscaler, Palo Alto Networks), productivity and collaboration (Microsoft Office 365, Windows Event Logs, and GitHub), along with IT service manager with ServiceNow CMBD. To normalize and process your data as they are being ingested, CloudWatch offers managed OCSF conversion for various AWS and third-party data sources and other processors such as Grok for custom parsing, field-level operations, and string manipulations.
• Reduce costly log data management – CloudWatch consolidates log management into a single service with built-in governance capabilities without storing and maintaining multiple copies of the same data across different tools and data stores. The unified data store of CloudWatch eliminates the need for complex ETL pipelines and reduces your operational costs and management overhead needed to maintain multiple separate data stores and tools.
• Discover business insights from log data – You can run queries in CloudWatch using natural language queries and popular query languages such as LogsQL, PPL, and SQL through a single interface, or query your data using your preferred analytics tools through Apache Iceberg-compatible tables. The new Facets interface gives you intuitive filtering by source, application, account, region, and log type, which you can use to run queries across log groups of multiple AWS accounts and Regions with intelligent parameter inference.

In the next sections we explore the new log management and analytics features of the CloudWatch Logs!

1. Data discovery and management by data sources and types

You can see a high-level overview of logs and all data sources with a new Logs Management View in the CloudWatch console. To get started, go to the CloudWatch console and choose Log Management under the Logs menu in the left navigation pane. In the Summary tab, you can observe your logs data sources and types, insights into how your log groups are doing across ingestion, and anomalies.

Choose the Data sources tab to find and manage your log data by data sources, types, and fields. CloudWatch ingests and automatically categorizes data sources by AWS services, third-party, or custom sources such as application logs.

Choose the Data source actions to integrate S3 Tables to make future logs for selected data sources. You have the flexibility to analyze the logs through Athena and Amazon Redshift and other query engines such as Spark using Iceberg compatible access patterns. With this integration, logs from CloudWatch are available in a read-only aws-cloudwatch S3 Tables bucket.

When you choose a specific data source such as CloudTrail data, you can view the details of the data source that includes information regarding data format, pipeline, facets/field indexes, S3 Tables association, and the number of logs with that data source. You can observe all log groups included in this data source and type and edit a source/type field index policy using the new schema support.

To learn more about how to manage your data sources and index policy, visit Data sources in the Amazon CloudWatch Logs User Guide.

2. Ingestion and transformation using CloudWatch pipelines

You can create pipelines to streamline collecting, transforming, and routing telemetry and security data while standardizing data formats to optimize observability and security data management. The new pipeline feature of CloudWatch connects data from a catalogue of data sources, so that you can add and configure pipeline processors from a library to parse, enrich, and standardize data.

In the Pipeline tab, choose Add pipeline. It shows you the pipeline configuration wizard. This wizard guides you through five steps where you can choose the data source and other source details such as log source types, configure destination, configure up to 19 processors to perform an action on your data (such as filtering, transforming, or enriching), and finally review and deploy the pipeline.

You also have the option to create pipelines through the new Ingestion experience in CloudWatch. To learn more about how to set up and manage the pipelines, visit Pipelines in the Amazon CloudWatch Logs User Guide.

3. Enhanced analytics and querying based on data sources

You can enhance analytics with support for Facets and querying based on data sources. Facets enable interactive exploration and drill-down into logs and their values are automatically extracted based on the selected time period.

Choose the Facets tab in the Log Insights under the Logs menu in the left navigation pane. You can view available facets and values that appear in the panel. Choose one or more facets and values to interactively explore your data. I choose Facets regarding a VPC Flow Logs group and action, query to list the five most frequent patterns in my VPC Flow Logs through the AI query generator, and get the result patterns.

You can save your query with the selected Facets and values that you have specified. When you next choose your saved query, the logs to be queried have the pre-specified facets and values. To learn more about Facet management, visit Facets in the CloudWatch Logs User Guide.

As I previously noted, you can integrate data sources into S3 Tables and query together. For example, using a Query Editor in Athena, you can query correlates network traffic with AWS API activity from a specific IP range (174.163.137.*) by joining VPC Flow Logs with CloudTrail logs based on matching source IP addresses.

This type of integrated search is particularly valuable for security monitoring, incident investigation, and suspicious behavior detection. You can view if an IP that’s making network connections is also performing sensitive AWS operations such as creating users, modifying security groups, or accessing data.

To learn more, visit S3 Tables integration with CloudWatch in the CloudWatch Logs User Guide.

Now available

New log management features of Amazon CloudWatch are available today in all AWS Regions except the AWS GovCloud (US) Regions and China Regions. For Regional availability and future roadmap, visit the AWS Capabilities by Region. There are no upfront commitments or minimum fees, and you pay for the usage of existing CloudWatch Logs for data ingestion, storage, and queries. To learn more, visit the CloudWatch pricing page.

Give it a try in the CloudWatch console. To learn more, visit the CloudWatch product page and send feedback to AWS re:Post for CloudWatch Logs or through your usual AWS Support contacts.

— Channy

The post Amazon CloudWatch introduces unified data management and analytics for operations, security, and compliance appeared first on The NOKIA Blog.

Today, we’re announcing a Controls Dedicated experience in AWS Control Tower. With this feature, you can use Amazon Web Services (AWS) managed controls without the need to set up resources you don’t need, which means you get started faster if you already have an established multi-account environment and want to use AWS Control Tower only for its managed controls. The Controls Dedicated experience gives you seamless access to the comprehensive collection of managed controls in the Control Catalog to incrementally enhance your governance stance.

Until now, customers were required to adopt and configure many recommended best practices which meant implementing a full AWS landing zone at the time of setting up a multi-account environment. This setup included defining the prescribed organizational structure, required services, and more, in AWS Control Tower to start using landing zone. This approach is helpful to ensure a well-architected multi-account environment, however, for customers who already have an established, well-architected multi-account environment and only want to use AWS managed controls, it was more challenging for them to adopt AWS Control Tower. The new Controls Dedicated experience provides a faster and more flexible way of using AWS Control Tower.

How it works

Here’s how I define managed controls using the Controls Dedicated experience in AWS Control Tower in one of my accounts.

I start by choosing Enable AWS Control Tower on the AWS Control Tower landing page.

I have the option to set up a full environment, or only set up controls using the Controls Dedicated experience. I opt to set up controls by choosing I have an existing environment and want to enable AWS Managed Controls. Next, I set up the rest of the information, such as choosing the Home Region from the dropdown list so that AWS Control Tower resources are provisioned in this Region during enablement. I also select Turn on automatic account enrollment for AWS Control Tower to enroll accounts automatically when I move them into a registered organization unit. The rest of the information is optional; I choose Enable AWS Control Tower to finalize the process, and the landing zone setup begins.

The dashboard gives a summary of the environment such as the organizational units that were created, the shared accounts, the selected IAM configuration, the preventive controls to enforce policies, and detective controls to detect configuration violations.

I choose View enabled controls for a list of all controls that were installed during this process.

The setup is completed, and now I have all the infrastructure required to use the controls in this account.

Good to know

Usually, an existing AWS Organizations account is required before you can use AWS Control Tower. If you’re using the console to create controls and don’t already have an Organizations account, one will be set up on your behalf.

Now available

Controls Dedicated experience in AWS Control Tower is available today in all AWS Regions where AWS Control Tower is available.

To learn more, visit our AWS Control Tower page. For more information related to pricing, refer to AWS Control Tower pricing. Send feedback to AWS re:Post for AWS Control Tower or through your usual AWS Support contacts.

– Veliswa.

The post AWS Control Tower introduces a Controls Dedicated experience appeared first on The NOKIA Blog.

Today, we’re announcing the general availability of Billing Transfer, a new capability to centrally manage and pay bills across multiple organizations by transferring payment responsibility to other billing administrators, such as company affiliates and Amazon Web Services (AWS) Partners. This feature provides customers operating across multiple organizations with comprehensive visibility of cloud costs across their multi-organization environment, but organization administrators maintain security management autonomy over their accounts.

Customers use AWS Organizations to centrally administer and manage billing for their multi-account environment. However, when they operate in a multi-organization environment, billing administrators must access the management account of each organization separately to collect invoices and pay bills. This decentralized approach to billing management creates unnecessary complexity for enterprises managing costs and paying bills across multiple AWS organizations. This feature also will be useful for AWS Partners to resell AWS products and solutions, and assume the responsibility of paying AWS for the consumption of their multiple customers.

With Billing Transfer, customers operating in multi-organization environments can now use a single management account to manage aspects of billing— such as invoice collection, payment processing, and detailed cost analysis. This makes billing operations more efficient and scalable while individual management accounts can maintain complete security and governance autonomy over their accounts. Billing Transfer also helps protect proprietary pricing data by integrating with AWS Billing Conductor, so billing administrators can control cost visibility.

Getting started with Billing Transfer

To set up Billing Transfer, an external management account sends a billing transfer invitation to a management account called a bill-source account. If accepted, the external account becomes the bill-transfer account, managing and paying for the bill-source account’s consolidated bill, starting on the date specified on the invitation.

To get started, go to the Billing and Cost Management console, choose Preferences and Settings in the left navigation pane and choose Billing transfer. Choose Send invitation from a management account you’ll use to centrally manage billing across your multi-organization environment.

Now, you can send a billing transfer invitation by entering the email address or account ID of the bill-source accounts for which you want to manage billing. You should choose the monthly billing period for when invoicing and payment will begin and a pricing plan from AWS Billing Conductor to control the cost data visible to the bill-source accounts.

When you choose Send invitation, the bill-source accounts will get a billing transfer notice in the Outbound billing tab.

Choose View details, review the invitation page, and choose Accept.

After the transfer is accepted, all usage from the bill-source accounts will be billed to the bill-transfer account using its billing and tax settings, and invoices will no longer be sent to the bill-source accounts. Any party (bill-source accounts and bill-transfer account) can withdraw the transfer at any time.

After your billing transfer begins, the bill-transfer account will receive a bill at the end of the month for each of your billing transfers. To view transferred invoices reflecting the usage of the bill-source accounts, choose the Invoices tab in the Bills page.

You can identify the transferred invoices by bill-source account IDs. You can also find the payments for the bill-source accounts invoices in the Payments menu. These appear only in the bill-transfer account.

The bill-transfer account can use billing views to access the cost data of the bill-source accounts in AWS Cost Explorer, AWS Cost and Usage Report, AWS Budgets and Bills page. When enabling billing view mode, you can choose your desired billing view for each bill-source account.

The bill-source accounts will experience these changes:

• Historical cost data will no longer be available and should be downloaded before accepting
• Cost and Usage Reports should be reconfigured after transfer

Transferred bills in the bill-transfer account always use the tax and payment settings of the account to which they’re delivered. Therefore, all the invoices reflecting the usage of the bill-source accounts and the member accounts in their AWS Organizations will contain taxes (if applicable) calculated on the tax settings determined by the bill-transfer account.

Similarly, the seller of record and payment preferences are also based on the configuration determined by the bill-transfer account. You can customize the tax and payments settings by creating the invoice units available in the Invoice Configuration functionality.

To learn more about details, visit Billing Transfer in the AWS documentation.

Now available

Billing Transfer is available today in all commercial AWS Regions. To learn more, visit the AWS Cloud Financial Management Services product page.

Give Billing Transfer a try today and send feedback to AWS re:Post for AWS Billing or through your usual AWS Support contacts.

— Channy

The post New: AWS Billing Transfer for centrally managing AWS billing and costs across multiple organizations appeared first on The NOKIA Blog.

Today, I’m happy to announce Amazon EC2 Capacity Manager, a centralized solution to monitor, analyze, and manage capacity usage across all accounts and AWS Regions from a single interface. This service aggregates capacity information with hourly refresh rates and provides prioritized optimization opportunities, streamlining capacity management workflows that previously required custom automation or manual data collection from multiple AWS services.

Organizations using Amazon Elastic Compute Cloud (Amazon EC2) at scale operate hundreds of instance types across multiple Availability Zones and accounts, using On-Demand Instances, Spot Instances, and Capacity Reservations. This complexity means customers currently access capacity data through various AWS services including the AWS Management Console, Cost and Usage Reports, Amazon CloudWatch, and EC2 describe APIs. This distributed approach can create operational overhead through manual data collection, context switching between tools, and the need for custom automation to aggregate information for capacity optimization analysis.

EC2 Capacity Manager helps you overcome these operational complexities by consolidating all capacity data into a unified dashboard. You can now view cross-account and cross-Region capacity metrics for On-Demand Instances, Spot Instances, and Capacity Reservations across all commercial AWS Regions from a single location, eliminating the need to build custom data collection tools or navigate between multiple AWS services.

This consolidated visibility can help you discover cost savings by highlighting underutilized Capacity Reservations, analyzing usage patterns across instance types, and providing insights into Spot Instance interruption patterns. By having access to comprehensive capacity data in one place, you can make more informed decisions about rightsizing your infrastructure and optimizing your EC2 spending.

Let me show you the capabilities of EC2 Capacity Manager in detail.

Getting started with EC2 Capacity Manager
On the AWS Management Console, I navigate to Amazon EC2 and select Capacity Manager from the navigation pane. I enable EC2 Capacity Manager through the service settings. The service aggregates historical data from the previous 14 days during initial setup.

The main Dashboard displays capacity utilization across all instance types through a comprehensive overview section that presents key metrics at a glance. The capacity overview cards for Reservations, Usage, and Spot show trend indicators and percentage changes to help you identify capacity patterns quickly. You can apply filtering through the date filter controls, which include date range selection, time zone configuration, and interval settings.

You can select different units to analyze data by vCPUs, instance counts, or estimated costs to understand resource consumption patterns. Estimated costs are based on published On-Demand rates and do not include Savings Plans or other discounts. This pricing reference helps you compare the relative impact of underutilized capacity across different instance types—for example, 100 vCPU hours of unused p5 reservations represents a larger cost impact than 100 vCPU hours of unused t3 reservations.

The dashboard includes detailed Usage metrics with both total usage visualization and usage over time charts. The total usage section shows the breakdown between reserved usage, unreserved usage, and Spot usage. The usage over time chart provides visualization that tracks capacity trends over time, helping you identify usage patterns and peak demand periods.

Under Reservation metrics, Reserved capacity trends visualizes used and unused reserved capacity across the selected period, showing the proportion of reserved vCPU hours that remain unutilized compared with those actively consumed, helping you track reservation efficiency patterns and identify periods of consistent low utilization. This visibility can help you reduce costs by identifying underutilized reservations and helping you to make informed decisions about capacity adjustments.

The Unused capacity section lists underutilized capacity reservations by instance type and Availability Zone combinations, displaying specific utilization percentages and instance types across different Availability Zones. This prioritized list helps you identify potential savings with direct visibility into unused capacity costs.

The Usage tab provides detailed historical trends and usage statistics across all AWS Regions for Spot Instances, On-Demand Instances, and Capacity Reservations. Dedicated Hosts usage is not included. The Dimension filter helps you group by and filter capacity data by Account ID, Region, Instance Family, Availability Zone, and Instance Type, creating custom views that reveal usage patterns across your accounts and AWS Organizations. This helps you analyze specific configurations and compare performance across accounts or Regions.

The Aggregations section provides a comprehensive usage table across EC2 and Spot Instances. You can select different units to analyze data by vCPUs, instance counts, or estimated costs to understand resource consumption patterns. The table shows instance family breakdowns with total usage statistics, reserved usage hours, unreserved usage hours, and Spot usage data. Each row includes a View breakdown action for a detailed analysis.

The Capacity usage or estimated cost trends section visualizes usage trends, reserved usage, unreserved usage, and Spot usage. You can filter the displayed data and adjust the unit of measurement to view historical patterns. These filtering and analysis tools help you identify usage trends, compare costs across dimensions, and make informed decisions for capacity planning and optimization.

When you choose View breakdown from the Aggregations table, you access detailed Usage breakdown based on the dimension filters you selected. This breakdown view shows usage patterns for individual instance types within the selected family and Availability Zone combinations, helping you identify specific optimization opportunities.

The Reservations tab displays capacity reservation utilization with automated analysis capabilities that generate prioritized lists of optimization opportunities. Similar to the Usage tab, you can apply dimension filters by Account ID, Region, Instance Family, Availability Zone, and Instance Type along with additional options related to the reservation details. On each of the tabs you can drill down to see data for individual line items. For reservations specifically, you can view specific reservations and access detailed information about On-Demand Capacity Reservations (ODCRs), including utilization history, configuration parameters, and current status. When the ODCR exists in the same account as Capacity Manager, you can modify reservation parameters directly from this interface, eliminating the need to navigate to separate EC2 console sections for reservation management.

The Statistics section provides summary metrics, including total reservations count, overall utilization percentage, reserved capacity totals, used and unused capacity volumes, average scheduled reservations, and counts of accounts, instance families, and Regions with reservations.

This consolidated view helps you understand reservation distribution and utilization patterns across your infrastructure. For example, you might discover that your development accounts consistently show 30% reservation utilization while production accounts exceed 95%, indicating an opportunity to redistribute or modify reservations. Similarly, you could identify that specific instance families in certain Regions have sustained low utilization rates, suggesting candidates for reservation adjustments or workload optimization. These insights help you make data-driven decisions about reservation purchases, modifications, or cancellations to better align your reserved capacity with actual usage patterns.

The Spot tab focuses on Spot Instance usage and displays the amount of time your Spot instances run before being interrupted. This analysis of Spot Instance usage patterns helps you identify optimization opportunities for Spot Instance workloads. You can use Spot placement score recommendations to improve workload flexibility.

For organizations requiring data export capabilities, Capacity Manager includes data exports to Amazon Simple Storage Service (Amazon S3) buckets for capacity analysis. You can view and manage your data exports through the Data exports tab, which helps you create new exports, monitor delivery status, and configure export schedules to analyze capacity data outside the AWS Management Console.

Data exports extend your analytical capabilities by storing capacity data beyond the 90-day retention period available through the console and APIs. This extended retention enables long-term trend analysis and historical capacity planning. You can also integrate exported data with existing analytics workflows, business intelligence tools, or custom reporting systems to incorporate EC2 capacity metrics into broader infrastructure analysis and decision-making processes.

The Settings section provides configuration options for AWS Organizations integration, enabling centralized capacity management across multiple accounts. Organization administrators can enable enterprise-wide capacity visibility or delegate access to specific accounts while maintaining appropriate permissions and access controls.

Now available
EC2 Capacity Manager eliminates the operational overhead of collecting and analyzing capacity data from multiple sources. The service provides automated optimization opportunities, centralized multi-account visibility, and direct access to capacity management tools. You can reduce manual analysis time while improving capacity utilization and cost optimization across your EC2 infrastructure.

Amazon EC2 Capacity Manager is available at no additional cost. To begin using Amazon EC2 Capacity Manager, visit the Amazon EC2 console or access the service APIs. EC2 Capacity Manager is available in all commercial AWS Regions enabled by default.

To learn more, visit the EC2 Capacity Manager documentation.

— Esra

The post Monitor, analyze, and manage capacity usage from a single interface with Amazon EC2 Capacity Manager appeared first on The NOKIA Blog.

Summer has drawn to a close here in Utrecht, where I live in the Netherlands. In two weeks, I’ll be attending AWS Community Day 2025, hosted at the Kinepolis Jaarbeurs Utrecht on September 24. The single-day event will bring together over 500 cloud practitioners from across the Netherlands, featuring 25 breakout sessions across five technical tracks. The day will begin with virtual keynotes at 9:00 AM, followed by parallel breakout sessions focused on practical implementations of serverless architectures and container optimization strategies, providing valuable insights regardless of experience level.

Last year’s AWS Community Day Netherlands 2024 brought together a diverse group of cloud practitioners, speakers, and AWS enthusiasts who contributed to making the community-led conference a valuable knowledge-sharing platform. If you’re planning to attend, feel free to find me there to discuss AWS services or share your cloud implementation experiences!

Let’s look at last week’s new announcements.

Last week’s launches

AWS Transform assessments now includes detached storage analysis – AWS Transform has expanded its assessment capabilities to analyze on-premises detached storage infrastructure, helping customers determine migration total cost of ownership (TCO). The assessment now evaluates Storage Area Network (SAN), Network Attached Storage (NAS), file servers, object storage, and virtual environments, providing migration recommendations to appropriate AWS services including Amazon S3, Amazon EBS, and Amazon FSx. The tool delivers a comprehensive TCO comparison between current and AWS environments, along with performance and cost optimization recommendations. With storage accounting for up to 45% of total migration opportunities, this enhancement helps customers visualize various AWS migration options. AWS Transform assessment is available in US East (N. Virginia) and Europe (Frankfurt) Regions.

Amazon Bedrock introduces Global Cross-Region inference for Anthropic Claude Sonnet 4 – Anthropic’s Claude Sonnet 4 model in Amazon Bedrock now supports Global cross-Region inference, allowing inference requests to route to any supported commercial AWS Region for processing. This enhancement optimizes available resources and enables higher model throughput by distributing traffic across multiple Regions. Previously, you could select cross-Region inference profiles tied to specific geographies (US, EU, or APAC). The new Global cross-Region inference profile provides additional flexibility for generative AI use cases that don’t require geography-specific processing, helping manage unplanned traffic bursts and increase model throughput. For detailed implementation guidance, visit the Amazon Bedrock documentation.

Amazon Neptune Database adds Public Endpoints support – Amazon Neptune now supports Public Endpoints, enabling direct connections to Neptune databases from outside the VPC without complex networking configurations. This feature helps developers securely access their graph databases from development desktops without requiring VPN connections or bastion hosts, while maintaining security through IAM authentication, VPC security groups, and encryption in transit. Public Endpoints can be enabled for Neptune clusters running engine version 1.4.6 or above through the AWS Management Console, AWS CLI, or AWS SDK. The feature is available at no additional cost beyond standard Neptune pricing in all AWS Regions where Neptune Database is offered. Implementation details are available in the Amazon Neptune documentation.

ECS Exec now available in AWS Management Console – Amazon ECS now supports ECS Exec directly in the AWS Management Console, enabling secure, interactive shell access to running containers without requiring inbound ports or SSH key management. Previously available only through API, CLI, or SDKs, this feature streamlines troubleshooting by allowing container access directly from the console interface. You can enable ECS Exec when creating or updating services and standalone tasks, then connect to containers by selecting “Connect” on the task details page, which opens an interactive session through CloudShell. The console also displays the underlying AWS CLI command for use in local terminals. This feature is available in all AWS commercial Regions and documented in the ECS developer guide.

Organizational Notification Configurations for AWS User Notifications now generally available – AWS User Notifications now supports Organizational Notification Configurations, helping AWS Organizations users centrally configure and view notifications across their organization. Management accounts or delegated administrators can configure notifications for specific organizational units or all accounts in an organization. The service supports configuring notifications for any supported Amazon EventBridge event, such as console sign-ins without MFA, with notifications appearing in the admin’s Console Notifications Center and AWS Console Mobile Application. User Notifications supports up to five delegated administrators and is available in all AWS Regions where AWS User Notifications is offered. For implementation details, visit the AWS User Notifications user guide.

For a full list of AWS announcements, be sure to keep an eye on the What’s New at AWS page.

Upcoming AWS events
Check your calendar and sign up for upcoming AWS events.

AWS Summits – Join free online and in-person events that bring the cloud computing community together to connect, collaborate, and learn about AWS. Register in your nearest city: Zurich (September 11), Los Angeles (September 17), and Bogotá (October 9).

AWS re:Invent 2025 – Join us in Las Vegas between December 1–5 as cloud pioneers gather from across the globe for the latest AWS innovations, peer-to-peer learning, expert-led discussions, and invaluable networking opportunities. Don’t forget to explore the event catalog.

AWS Community Days – Join community-led conferences that feature technical discussions, workshops, and hands-on labs led by expert AWS users and industry leaders from around the world: Baltic (September 10), Aotearoa (September 18), South Africa (September 20), Bolivia (September 20), Portugal (September 27).

Browse all upcoming AWS led in-person and virtual events here.

That’s all for this week. Check back next Monday for another Weekly Roundup!

— Esra

This post is part of our Weekly Roundup series. Check back each week for a quick roundup of interesting news and announcements from AWS!

The post AWS Weekly Roundup: AWS Transform, Amazon Neptune, and more (September 8, 2025) appeared first on The NOKIA Blog.