This week, the AWS IoT Device SDK for Swift reached general availability. As a member of the Swift Server Workgroup (SSWG), this one caught my attention. The SDK brings production-ready MQTT 5 connectivity, Device Shadow, Jobs, and fleet provisioning to Swift developers on macOS, iOS, tvOS, and Linux.

I’m curious to see what you will build with it. Swift on the server has matured over the past few years, and now it reaches IoT devices too. This connects to a broader trend of running Swift at the edge. WendyOS, for example, is an open-source operating system for physical AI that offers first-class Swift support for deploying apps to NVIDIA Jetson and Raspberry Pi hardware. Between server-side Swift, IoT, and edge computing, the language is showing up in places that would have surprised most people a few years ago.

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

Headlines
Amazon RDS for SQL Server supports Bring Your Own Media – Customers who migrate SQL Server applications from on-premises environments can now reuse their existing Microsoft SQL Server licenses, including Software Assurance, through Microsoft’s License Mobility program on Amazon RDS. BYOM is integrated with AWS License Manager for tracking license usage and compliance. Read more.

Amazon Cognito now supports multi-Region replication – You can now synchronize user and machine identity data, including credentials, user pool configurations, and federation setups, to a secondary user pool in a standby Region in near real-time. In the event of a disruption in the primary Region, signed-in users continue accessing their applications without re-authenticating, and registered users can sign in with their existing credentials. Multi-Region replication is available as an add-on for user pools in Essentials or Plus feature tiers across 16 Regions. Read more.

GPT-5.5, GPT-5.4, and Codex from OpenAI are now generally available on Amazon Bedrock – You can now use GPT-5.5 and GPT-5.4 in production workloads on Amazon Bedrock and build with Codex for AI-powered software development, with the same security, governance, and operational controls you already use across AWS. GPT-5.5 is the most capable model from OpenAI, excelling at agentic coding, data analysis, and multi-step autonomous tasks. Codex is available through the Codex App, the Codex CLI, and IDE integrations with Visual Studio Code, JetBrains, and Xcode. Pricing matches OpenAI first-party rates, and usage counts toward existing AWS commitments. Read more.

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

• Amazon Bedrock adds CloudWatch metrics for OpenAI- and Anthropic-compatible APIs – You can now monitor inference traffic to the bedrock-mantle endpoint with CloudWatch metrics, including inference counts, input and output token totals, and client error counts at account, project, model, and project-and-model granularity.
• Amazon Bedrock launches a redesigned console optimized for OpenAI- and Anthropic-compatible APIs – A refreshed console workflow with a model catalog, side-by-side comparison, project-based organization, and project-aware documentation with pre-filled code snippets.
• Amazon Bedrock AgentCore Identity now supports bring-your-own secrets with AWS Secrets Manager – Customers can now reference existing AWS Secrets Manager secret ARNs in AgentCore Identity Credential Providers, enabling full ownership of secrets governance including custom CMKs, tagging strategies, and automatic rotation.
• AWS Step Functions adds AgentCore-powered agentic reasoning step – You can now add AI agent reasoning steps to your Step Functions workflows through an integration with the managed harness in Amazon Bedrock AgentCore. Run multiple agents in parallel or sequence, add human approval, and trace every agent decision.
• Amazon EKS and Amazon EKS Distro now support Kubernetes version 1.36 – Kubernetes 1.36 promotes User Namespaces to GA, introduces Mutating Admission Policies, In-Place Pod-Level Resources Vertical Scaling, and Resource Health Status reporting. Available in all Regions where EKS is available.
• Amazon ECS Managed Instances now supports AWS Trainium and AWS Inferentia – You can now create an ECS Managed Instances capacity provider with Inferentia2, Trainium1, and Trainium2 instance types and have Amazon ECS automatically allocate all accelerator resources to your workload.
• Amazon Quick now supports VPC connectivity for MCP connections – Enterprise customers can now connect privately hosted Model Context Protocol (MCP) servers to Amazon Quick through VPC, enabling secure access to proprietary applications and internal tools without exposing them to the internet.
• AWS Cost and Usage Report 2.0 now supports Athena and Redshift integration – CUR 2.0 exports are automatically delivered in the optimal format for your chosen query engine, with supporting infrastructure templates, table definitions, and data loading instructions.
• Amazon Location Service announces public transit and intermodal routing – The Routes API now supports two new travel modes, Transit and Intermodal, to plan journeys combining public transportation with walking, driving, taxi, and rental segments across 13 Regions.

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

Upcoming AWS events
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!

— seb

Today, we’re announcing a new console experience in Amazon Bedrock for you to experiment, iterate, and scale with the latest AI models on Amazon Bedrock’s next-generation inference engine built for high performance, reliability, and security. This console has a refreshed workflow optimized for bedrock-mantle endpoint, which supports the latest GPT, Claude, and open-weight models with the OpenAI Responses API, OpenAI Chat Completions API, and the Anthropic Messages API.

The new console experience makes it simple to find the right model and move quickly from evaluation to production.

• New model card: You can browse the full model catalog, compare them side by side on capabilities, modality support, context window, and applicable service quotas in a single view, removing the need to stitch together documentation, and limit calculators.
• Project-based work: You can make a project to run evaluations and review usage insights in one streamlined workflow that mirrors the lifecycle of building a generative AI application.
• Live documentation: You can use project-aware live documentation: code samples, SDK snippets, and API references are automatically prefilled with your project variables. You can copy a snippet straight from the console into your application and run it without modification.

How to get started
You can try a new experience by choosing Try the new Bedrock Console from within the Amazon Bedrock console, or by using the new console link directly.

You can find a project-based dashboard to show inference requests and error by range of recent dates, recently used models, and the project list. You can create a project, assign models, configure API keys, and start making inference requests in minutes.

A new model catalog shows the latest GPT, Claude, and open-weight models that are supported on the bedrock-mantle engine. You can see the details of features, tokens, pricing, input/output, pricing information, and Regional availability. You can also compare up to 3 models in a single view.

When you choose the project dashboard, you can see the models used in the project, the distribution of your token usage such as total token usage, token usage per minute, inference requests per minute, and tokens per inference request. This can inform your model selection, prompt optimization, and workload consistency decisions.

You can select up to 3 models to start evaluating to compare responses side by side with the same prompt.

To build your application in the project, choose Getting started. You can migrate existing code, build a new app with the Anthropic or OpenAI SDK, or connect an AI coding assistant to Bedrock.

Choose the API & SDK, your SDK (either Anthropic or OpenAI), your preferred programming language, and your authentication method. It shows your environment code to run these in your terminal for a quick test, or save to a .env file for your application. You can also send your first request with sample code snippets to verify your setup.

When you choose Clients, you can select the AI coding agent source such as Claude Code, Cline, Codex, Cursor, or OpenCode that you want to connect to the bedrock-mantle engine. It provides instructions on how to install the AI agent, use your AWS IAM credentials or use a Bedrock API key, set environment variables, and route requests from each AI agent through Bedrock.

To learn about Anthropic- and OpenAI-compatible APIs, choose Live API docs. You can choose Anthropic API Protocol for access to Claude model features like the Messages API or OpenAI API Protocol for access to features like Responses API.

For example, when you choose OpenAI Response API, it retrieves a model response with the given model ID. These API references are automatically prefilled with the project’s selected model ID, Region, bedrock-mantle endpoint URL, and API key reference, and they update in place as you change models or settings.

You can also choose the existing Bedrock console to manage fully-managed features such as Agents, Knowledge Bases, Guardrails, fine-tuning, or the InvokeModel and Converse APIs to run on the bedrock-runtime endpoint.

Now available
The new console experience is available in all AWS Regions where the bedrock-mantle endpoint is offered: US East (N. Virginia, Ohio), US West (Oregon), Asia Pacific (Jakarta, Mumbai, Sydney, Tokyo), Europe (Frankfurt, Ireland, London, Milan, Stockholm), and South America (São Paulo). Check the full list of Regions for future updates.

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

— Channy

Updated on July 13, 2026 – Fixed the first console image to reflect the latest UI.

As we previewed in What’s Next with AWS 2026, we’re announcing the availability of OpenAI GPT-5.5, GPT-5.4 models, and Codex on Amazon Bedrock, giving you access to frontier models and a coding agent for software development.

According to OpenAI, GPT-5.5 and GPT-5.4 models are excellent for coding, reasoning, agentic workflows, and complex professional work. You can use GPT-5.5 for the hardest customer workloads and GPT-5.4 for the best price-performance. You can call them through Responses API on Amazon Bedrock’s next-generation inference engine built for high performance, reliability, and security.

Codex is the OpenAI coding agent for AI-powered software development. According to OpenAI, more than 4 million developers use Codex every week to write, refactor, debug, test, and validate code across large codebases. With GPT-5.5 powering inference, Codex introduces a new class of intelligence optimized for complex, long-horizon developer workflows. You can use the Codex App, the Codex CLI, and IDE integrations with Visual Studio Code, JetBrains, and Xcode, with all model inference routed through the Responses API on Amazon Bedrock.

For customers with data residency requirements, all processing stays within the Bedrock Region you select. You pay per token with no seat licenses and no per-developer commitments.

GPT-5.5 and GPT-5.4 models on Bedrock in action
You can access the model programmatically using the OpenAI Responses API to call the bedrock-mantle endpoints through the OpenAI SDK, command-line tools such as curl.

Let’s start with OpenAI SDK for Python. Install OpenAI SDK.

pip install -U openai

Set the environment variables for authentication.

export OPENAI_BASE_URL="https://bedrock-mantle.us-east-2.api.aws/openai/v1"
export OPENAI_API_KEY="<BEDROCK_API_KEY>"
export BEDROCK_OPENAI_MODEL_ID="openai.gpt-5.5"

Here is a sample Python code to call GPT-5.5 model on Bedrock:

import os
from openai import OpenAI
 
client = OpenAI(
    base_url=os.environ["OPENAI_BASE_URL"],
    api_key=os.environ["OPENAI_API_KEY"],
)
 
response = client.responses.create(
    model=os.environ["BEDROCK_OPENAI_MODEL_ID"],
    input=[
        {
            "role": "developer",
            "content": "You are a software engineer with excellent AWS cloud knowledge. Be concise and practical.",
        },
        {
            "role": "user",
            "content": "Design a distributed architecture on AWS in Python that should support 100k requests per second across multiple geographic regions.",
        },
    ],
    reasoning={"effort": "medium"},
    text={"verbosity": "low"},
)
 
print(response.output_text)

You can call directly the model endpoint using curl.

curl "$OPENAI_BASE_URL/responses" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "openai.gpt-5.5",
    "input": [
      {
        "role": "developer",
        "content": "You are a software engineer with excellent AWS cloud knowledge."
      },
      {
        "role": "user",
        "content": "Design a distributed architecture on AWS in Python that should support 100k requests per second across multiple geographic regions."
      }
    ],
    "reasoning": {"effort": "medium"},
    "text": {"verbosity": "low"}
  }'

You can use the Responses API when you want to use model-managed multi-turn state, need hosted tools, function tools, or richer tool orchestration, and run background or long-running work. To learn more, visit the OpenAI Cookbook Responses examples and getting started guide.

Using OpenAI Codex with GPT-5.5 on Amazon Bedrock
You can download Codex CLI, Codex App or Codex VS Code extension and get started with the Bedrock for model inference. Codex supports two Bedrock authentication pathways: Amazon Bedrock API key or AWS SDK credential chain. If you set AWS_BEARER_TOKEN_BEDROCK, Codex uses it first; otherwise Codex falls back to AWS SDK credential chain.

Set AWS_BEARER_TOKEN_BEDROCK in the environment that Codex will read:

export AWS_BEARER_TOKEN_BEDROCK=<your-bedrock-api-key>

Then, configure your preferred Region and set the model ID to openai.gpt-5.5 in ~/.codex/config.toml, which is required for Bedrock API-key authentication. You can also choose openai.gpt-5.4, openai.gpt-oss-120b, or openai.gpt-oss-20b. For the desktop app or VS Code extension, put any environment variables the app needs in ~/.codex/.env.

model = "openai.gpt-5.5"
model_provider = "amazon-bedrock"
[model_providers.amazon-bedrock.aws]
region = "us-east-2"

Restart the desktop app or VS Code extension after changing ~/.codex/config.toml or ~/.codex/.env. In Codex CLI, you should see a /status tab that looks like this:

In Codex App, you can use GPT-5.5 model through Amazon Bedrock inference.

To learn more about how to configure Codex to use OpenAI models on Amazon Bedrock, visit Use Codex with Amazon Bedrock.

Things to know
Let me share some important technical details that I think you’ll find useful.

• Model latency: OpenAI model information positions GPT-5.5 as fast and GPT-5.4 as medium speed, but customer-perceived latency depends on reasoning effort, output length, tool calls, background mode, Region, quotas, throttling, prompt size, and cache hits. Start GPT-5.5 at medium effort. Start GPT-5.4 with effort set explicitly rather than relying on its none default.
• Scaling and capacity: Bedrock’s new inference engine is designed to rapidly provision and serve capacity across many different models. When accepting requests, we prioritize keeping steady state workloads running, and ramp usage and capacity rapidly in response to changes in demand. During periods of high demand, requests are queued, rather than rejected.

Now available
OpenAI GPT models and Codex on Amazon Bedrock are available today: GPT-5.5 model in the US East (Ohio) Region, GPT-5.4 model in the US East (Ohio) and US West (Oregon) Regions. Check the full list of Regions for future updates. To learn more, visit the OpenAI on Amazon Bedrock page and the Amazon Bedrock pricing page.

Give GPT-5.5, GPT-5.4 models, and Codex on Amazon Bedrock a try today and send feedback to AWS re:Post for Amazon Bedrock or through your usual AWS Support contacts.

— Channy

Updated on June, 1, 2026 – The GPT 5.5 and 5.4 models now support the Responses API only on Amazon Bedrock, and console support is coming soon.

Updated on June, 3, 2026 – Amazon Bedrock now supports GPT‑5.4 from OpenAI in AWS GovCloud (US-West) Region.

Updated on June, 7, 2026 – You can use the GPT 5.5 and 5.4 models in the new Amazon Bedrock console.

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

Just a year ago, we launched AWS Transform for .NET, Mainframe and VMware workloads, the first agentic AI service purpose-built for modernizing enterprise applications at scale. At re:Invent 2025, we introduced AWS Transform custom, which enables organizations to modernize and transform code at scale using AWS-managed and custom transformations. You can upgrade language versions, migrate frameworks, optimize performance, and analyze code bases using transformations that are ready to use or can be customized to meet your organization’s specific requirements. We also introduced full-stack Windows modernization capabilities and Reimagine capabilities and automated testing functionality for mainframe.

In 12 months, thousands of customers migrated hundreds of thousands of servers, saved 1.6+ million hours, and processed 4.5+ billion lines of code with AWS Transform. Celebrating its 1-year anniversary, AWS Transform agents now available in Kiro, Claude, Cursor, and Codex, including the agent builder toolkit Kiro power for building customized transformation agents.

To learn what happened in 12 months, the four things we learned, and how that evolved our roadmap, visit the one-year anniversary blog post.

Last week’s launches
Here are last week’s launches that caught my attention:

• The general availability of Claude Platform on AWS – You can get direct access to Anthropic’s native Claude Platform experience, including APIs, console, and early-access beta features, directly through your existing AWS account, without managing separate accounts, billing, or tracking. Claude Platform on AWS is operated by Anthropic, and customer data is processed outside the AWS security boundary. To learn more, visit the deep dive blog post.
• Amazon EC2 M3 Ultra Mac instances – These instances are built on Apple M3 Ultra Mac Studio computers featuring a 28-core CPU, 60-core GPU, 32-core Neural Engine, and 256GB of unified memory. Compared to EC2 M4 Max Mac instances, M3 Ultra Mac instances provide 2x the unified memory, 1.75x the CPU cores, 1.5x the GPU cores, and 2x the Neural Engine cores, giving Apple developers the headroom to run significantly more Xcode simulators in parallel and accelerate on-device ML workflows to improve product time to market.
• Amazon Redshift RG instances powered by AWS Graviton – These instances deliver better performance, running data warehouse and data lake workloads up to 2.4x as fast as previous generation RA3 instances, at 30% lower price per vCPU. RG instances include Redshift’s custom-built vectorized data lake query engine that processes Apache Iceberg and Parquet data on your cluster nodes.
• Amazon Bedrock Advanced Prompt Optimization – You can optimize your prompts for any model on Bedrock, while comparing your original prompts to your optimized prompts across up to 5 models simultaneously. You can also use this if you are migrating to a new model or just want to get better performance on your current model.
• AWS Security Agent full repository code scanning (preview) – You can use a new capability in AWS Security Agent that performs deep, context-aware security analysis of your entire codebase. When vulnerabilities are found, the scanner generates code remediation—specific fixes tied to the exact file and line—enabling teams to remediate security vulnerabilities faster than ever before. This capability is available at no additional charge for existing AWS Security Agent customers during the preview.
• AWS Interconnect – multicloud connectivity with Oracle Cloud Infrastructure (preview) – You can quickly provision resilient, scalable private connections to other cloud providers using AWS Interconnect – multicloud connectivity. OCI is the latest CSP to adopt the open specification that powers AWS Interconnect. This allows AWS to provide a consistent, simple experience to our customers on OCI (preview), Google Cloud (generally available), and Microsoft Azure (coming later in 2026).

Additional updates
Here are some additional news items that you might find interesting:

• Accelerate AI research and education with Build on Trainium program – Read how the next generation of AI researchers is using Amazon chips to accelerate discovery. AWS invested $110 million to give university researchers access to purpose-built AI chips. AWS Trainium is speeding up AI research at UC Berkeley, MIT, Carnegie Mellon, and more. All research is open source, meaning improvements flow back to the broader developer community.
• A full list of AWS Community Days 2026 – There’s something different about an event where the speakers are your peers, the organizers are volunteers who do this out of passion, and the agenda was shaped by the community itself. That’s exactly what AWS Community Days are, and they’re happening in cities across every continent, every year.
• The Kiro Startups Credit program is back – Thousands of founders applied in the first round, and now applications are open again. Apply to receive up to one year of Kiro Pro+ credits automatically applied to your organization’s AWS account.

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 Summits. 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!

— Channy

Today, we’re announcing Amazon Bedrock Advanced Prompt Optimization, a new tool that you can use to optimize your prompts for any model on Amazon Bedrock, while comparing your original prompts to optimized prompts across up to 5 models simultaneously. With the new prompt optimization, you can migrate to a new model or improve performance from your current model. You can test them to make sure they see no regressions on known use cases and also improve on underperforming tasks.

The new prompt optimizer takes in your prompt template, example user inputs for the variable values, ground truth answers, and an evaluation metric to use as a guide. You can even use this with multimodal user inputs – it supports png, jpg, and pdf as inputs to your prompt templates so you can optimize prompts for tasks like document and image analysis.

You can also provide an AWS Lambda function, LLM-as-a-judge rubric, or a short natural language description to guide the optimization. The prompt optimizer works in a metric-driven feedback loop to optimize the prompt and resulting model responses for the evaluation metric, and outputs the original and final prompt templates with evaluation scores, cost estimates, and latency.

Bedrock Advanced Prompt Optimization in action
To get started with the new prompt optimization, choose Create prompt optimization on the Advanced Prompt Optimization page of Amazon Bedrock console.

Pick up to 5 inference models for which to optimize your prompts. You can use this if you are migrating to a new model or just want to get better performance on their current model. If you’re changing models, you can select your current model as a baseline and up to 4 other models. If you aren’t changing models, then just select your current model to see before and after optimization.

You should prepare your prompt templates in JSONL format with example user data, ground truth answers, and an evaluation metric or rewriting guidance. For .jsonl files, each JSON object must be on a single line.

{
    "version": "bedrock-2026-05-14",           // required; Fixed value
    "templateId": "string",                    // required
    "promptTemplate": "string",                // required
    "steeringCriteria": ["string"],            // optional
    "customEvaluationMetricLabel": "string",   // required if customLLMJConfig or evaluationMetricLambdaArn is used
    "customLLMJConfig": {                      // optional
        "customLLMJPrompt": "string",          // required if customLLMJConfig present
        "customLLMJModelId": "string"          // required if customLLMJConfig present
    },
    "evaluationMetricLambdaArn": "string",     // optional
    "evaluationSamples": [                     // required
        {
            "inputVariables": [                // required
                {
                    "variableName1": "string",
                    "variableName2": "string"
                }
            ],
            "referenceResponse": "string"      // optional
            "inputVariablesMultimodal": [      // optional
                {
                "Arbitrary_Name": {            // required for your multimodal variable.
                    "type": "string",          // choose from "PDF" or "IMAGE". Acceptable filetypes for IMAGE = png, jpg,  
                    "s3Uri": "string"          // input the S3 path of the file
                }
            ]
        }
    ]
}

You can upload files directly or import prompt templates from Amazon Simple Storage Service (Amazon S3) and set an S3 output location where prompt optimization results and evaluation data will be stored. Then, choose Create optimization.

Amazon Bedrock automatically sends your prompt templates and example data with optional ground truth to your inference models, evaluates the responses with your evaluation metric, then rewrites the prompt in a feedback loop to optimize it for your inference models. You’ll see evaluation results based on your provided metric and your final optimized prompts.

As you noted, you can evaluate prompt quality in three ways: a Lambda function with your own Python scoring logic, LLM-as-a-Judge with a custom rubric, or natural-language steering criteria. You can just choose one per prompt template, but can do multiple prompt templates in a job, so they can use a different method for each prompt template if they want.

• Lambda function: If you have a concrete metric (accuracy, F1, execution accuracy, structured-JSON match, etc.), you can deploy a Lambda function containing your custom scoring logic and configure evaluationMetricS3Uri field of the prompt template. Inside the Lambda, the core is a compute_score implementation that programmatically compares model outputs against reference responses.
• LLM-as-a-Judge: If your task is open-ended (summarization, generation, reasoning explanations) and you want a rubric-based score, you can configure the S3 config file in the customLLMJConfig field of the prompt template to define named metrics with structured instructions and a rating scale. A Bedrock judge model evaluates each prompt-response pair and returns a score with reasoning. The default model is Claude Sonnet 4.6 and you can also select your own from a list of judge models.
• Steering criteria: If you know the qualities you want (brand voice, format, safety constraints) but don’t want to author a full judge prompt, you can define criteria in the input dataset through the steeringCriteria array of the prompt template. Instead of structured metrics with rating scales, you provide free-form natural language criteria that the LLM judge evaluates holistically. If you use this option, then a default LLM-as-a-judge prompt will evaluate the responses and incorporate your steering criteria into the judge prompt. The judge model in this case is Anthropic Claude Sonnet 4.6.

To learn more about how to use the advanced prompt optimization and migration, visit the advanced prompt optimization in Bedrock guide and the sample codes in Github.

Now available
Amazon Bedrock Advanced Prompt Optimization is available today in US East (N. Virginia, Ohio), US West (Oregon), Asia Pacific (Mumbai, Seoul, Singapore, Sydney, Tokyo), Canada (Central), Europe (Frankfurt, Ireland, London, Zurich), and South America (São Paulo) Regions. You are charged based on the Bedrock model-inference tokens consumed during optimization, at the same per-token rates as regular Bedrock inference. To learn more, visit the Amazon Bedrock pricing page.

Give the advanced prompt optimization a try in the Amazon Bedrock console or with CreateAdvancedPromptOptimizationJob API today and send feedback to AWS re:Post for Amazon Bedrock or through your usual AWS Support contacts.

— Channy

My most exciting news of last week: Amazon Bedrock AgentCore previewed the first managed payment capabilities enabling AI agents to autonomously access and pay for APIs, MCP servers, web content, and other agents. Built in partnership with Coinbase and Stripe, it removes the undifferentiated heavy lifting of building customized systems for billing, credential management, and compliance.

You can connect a Coinbase CDP wallet or Stripe Privy wallet as a payment connection, set session-level spending limits, and your agent transacts autonomously during execution. What excites me most is what AgentCore payments can unlock—like a research agent that can pay for real-time market data on the fly, or a coding agent calling paid APIs mid-task.

To learn more, visit the blog post, dive deeper using the documentation, and get started with the AgentCore CLI.

Last week’s launches
Here are last week’s launches that caught my attention:

• Agent Toolkit for AWS – A production-ready suite of tools and guidance, available at no additional charge, that helps AI coding agents build on AWS with fewer errors, lower token costs, and enterprise-grade security controls. The Agent Toolkit for AWS is the successor to the MCP servers, plugins, and skills available on AWS Labs. To get started, visit the quick start guide or browse the available skills and plugins on GitHub.
• AWS MCP Server GA – You can use a managed remote Model Context Protocol (MCP) server that gives AI agents and coding assistants secure, authenticated access to all AWS services through a small, fixed set of tools. It is part of the Agent Toolkit for AWS. To learn more, visit Seb Stormacq’s blog post.
• Amazon WorkSpaces for AI agents (Preview) – You can use AI agents to securely access and operate desktop applications through managed WorkSpaces environments. This capability allows organizations to automate everyday workflows at scale while maintaining full enterprise-grade governance and compliance. To learn more, visit Micah Walter’s blog post.
• Amazon EC2 M8idn/M8idb and R8idn/R8idb instances – These instances are powered by custom sixth-generation Intel Xeon Scalable processors available only on AWS and the latest sixth-generation AWS Nitro cards. These instances deliver up to 43% better compute performance per vCPU compared to previous-generation instances. M8idn/R8idn instances offer up to 600 Gbps network bandwidth, and M8idb/R8idb instances deliver up to 300 Gbps EBS bandwidth.

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

Additional updates
Here are some additional news items that you might find interesting:

• Valkey turns two – Valkey stands as proof that open, community-driven technology innovates faster, scales further, and delivers more value than any single-vendor model. Valkey has surpassed 100 million Docker pulls (up 17x year over year) and attracted more than 225 contributors who have submitted over 1,500 pull requests, roughly double the development pace of Redis over the same period. You can also use the latest Valkey 9.0 in Amazon ElastiCache.
• Query billion-scale vectors with SQL – You can learn how to query Amazon S3 Vectors from Amazon Aurora PostgreSQL-Compatible Edition using standard SQL, and how to combine vector similarity results with relational filters in a single query, for example, finding the most semantically similar products and then filtering by price, stock status, or tenant in one SQL statement.
• Building an end-to-end agentic SRE using AWS DevOps Agent – Learn how to configure DevOps Agent Spaces that define an investigation scope, integrating seamlessly with Amazon CloudWatch, Splunk, GitHub, and Slack. You can also learn how to trigger automated investigations via webhooks, generate mitigation plans, and hand off agent-ready specs to coding agents like Kiro for implementation.

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!

— Channy

Enterprises face a significant challenge when deploying AI agents: the desktop and legacy applications that power most business workflows are simply inaccessible to modern AI systems. According to a 2024 Gartner report, 75% of organizations run legacy applications that lack modern APIs, and 71% of Fortune 500 companies operate critical processes on mainframe systems without adequate programmatic access. For many organizations, this has meant choosing between delaying AI adoption or undertaking expensive and risky modernization projects.

Today, we are announcing that Amazon WorkSpaces now enables AI agents to securely operate desktop applications without requiring application modernization. The same managed virtual desktops that millions of employees use and trust can now also serve AI agents, turning WorkSpaces into infrastructure for scaling enterprise productivity, not just delivering it. Because agents operate within your existing WorkSpaces environment, there are no APIs to build, no application migrations to plan, and no new infrastructure to manage.

Some of our customers had an early opportunity to give their agents a WorkSpace. Chris Noon, Director, Nuvens Consulting shared with us, “WorkSpaces lets our clients give AI agents the same secure, governed desktop environment their employees already use — no custom API integrations, full audit trails, and enterprise-grade isolation out of the box. For regulated industries, that’s not a nice-to-have — it’s the baseline.”

Secure cloud desktop access for AI agents
With WorkSpaces, AI agents can securely access and operate desktop applications running inside managed WorkSpaces environments to complete complex business workflows. Agents authenticate through AWS Identity and Access Management (IAM) and connect via Workspaces with complete audit trails available through AWS CloudTrail and Amazon CloudWatch. Because agents operate within secure WorkSpaces environments rather than on local machines, your existing security controls and compliance policies remain fully intact.

Amazon Workspaces supports the industry-standard Model Context Protocol (MCP), which means WorkSpaces works with any agent framework, such as LangChain, CrewAI and Strands Agents.

Let’s try it out
To set up a WorkSpaces environment for AI agents, I started in the AWS Management Console by creating a new WorkSpaces Applications stack—the environment definition that controls how agents connect and what they’re allowed to do.

From the Amazon WorkSpaces console, I chose Create stack and configured the basics: name, fleet association, and VPC endpoints. In Step 3 of the stack creation workflow, I noticed the new AI agents section with two options. The first, No AI agent access, is the default configuration for standard WorkSpaces designed for people. The second, Add AI Agents, allows AI agents to securely access and operate applications using their own identity and permissions. I selected Add AI Agents to enable agent connections on this stack.

Next, I will enable storage before configuring the agent access settings to define how agents interact with the desktop.

Under Agent features, I enabled three capabilities. Computer input allows the agent to click, type, and scroll within the desktop. Computer vision allows the agent to capture screenshots of the desktop, which is how it “sees” the application. Finally, screenshot storage configures where session screenshots are stored for audit and debugging.

Under Desktop screen layout, I set the screen resolution to 1280×720 and image format to PNG. The resolution determines the fidelity of what the agent sees during a session—a complex application with dense UI elements might benefit from higher resolution, while a terminal-style interface works well at 720p.

With my stack configured, WorkSpaces exposes a managed MCP endpoint. I pointed my agent framework to this endpoint, provided IAM credentials for authentication, and my agent began interacting with the desktop applications installed on the fleet’s image.

To see this in action, here’s an agent built with the Strands Agent SDK and Amazon Bedrock handling a prescription refill, looking up the patient record, searching for the medication, placing the order, and confirming a successful refill, all inside a sample pharmacy system with no API.

The application doesn’t know an agent is driving it. Nothing about the software was modified, rebuilt, or integrated. The agent worked with it exactly as it exists today.

Now available
This feature is available today at no additional cost in US East (N. Virginia, Ohio), US West (Oregon), Canada (Central), Europe (Frankfurt, Ireland, Paris, London), and Asia (Tokyo, Mumbai, Sydney, Seoul, Singapore) Regions.

Get started building today using our GitHub repo, or visit the WorkSpaces page for more details.

Updated July 1, 2026– Feature has moved from public preview to GA.

Last week, I took some time off in York, England, often described as the most haunted city in the country. I wandered through the ruins of abbeys that have stood for nearly a thousand years, walked along medieval walls, and spent an evening on a ghost tour hearing stories passed down through centuries. There’s something grounding about standing in a place that has witnessed so much history. Now I’m back at my desk, and the contrast is hard to miss: those abbey stones have stood for a thousand years largely unchanged, while in the span of a single week away, the pace of technological change has moved forward yet again.

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

Headlines
On April 28, Matt Garman, CEO of AWS, Colleen Aubrey, SVP Amazon Applied AI Solutions, Julia White, CMO of AWS, and OpenAI leaders took the stage to share how customers are changing the way businesses operate with agents. The event brought a packed slate of announcements across Amazon Quick, Amazon Connect, and a deeper partnership with OpenAI. Here’s a roundup of the biggest announcements from the event.

Amazon Quick expands with a desktop app, new pricing plans, and visual asset generation – Amazon Quick is an AI assistant for work that connects to your apps, learns what matters to you, and takes action on your behalf. This week, Quick introduced a new desktop app (Preview) that keeps you connected to your local files, calendar, and communications without opening a browser. You can sign up within minutes using your personal email address or existing Google, Apple, Github, or Amazon credentials—no AWS account required. Quick can now generate polished documents, presentations, infographics, and images directly from the chat interface, and native integrations expand to include Google Workspace, Zoom, Airtable, Dropbox, and Microsoft Teams. A new Build custom apps with Quick capability (Preview) lets you create intelligent apps, dashboards, and web pages connected to the rest of your business using natural language.

Amazon Connect expands into four agentic AI solutions – Amazon Connect is expanding from a single product into a set of four agentic AI solutions designed to work within your existing workflows. Amazon Connect Decisions is a supply chain planning and intelligence solution that shifts teams from crisis management to proactive planning, combining 30 years of Amazon operational science with more than 25 specialized supply chain tools. Amazon Connect Talent (Preview) is an agentic AI hiring solution that delivers AI-led interviews, science-backed assessments, and consistent evaluation for talent acquisition leaders managing scaled hiring. Amazon Connect Customer, previously known as Amazon Connect, delivers personalized customer experiences across voice, chat, and digital channels, with new configuration capabilities that enable organizations to set up conversational AI in weeks rather than months. Amazon Connect Health delivers agentic patient verification, appointment management, patient insights, ambient documentation, and medical coding, giving patients faster access to care and clinicians more time to deliver it.

AWS and OpenAI expand their partnership across Amazon Bedrock – AWS and OpenAI are bringing the latest OpenAI models to Amazon Bedrock, launching Codex on Amazon Bedrock, and introducing Amazon Bedrock Managed Agents powered by OpenAI — all in limited preview. OpenAI models on Amazon Bedrock (Limited preview) brings the latest OpenAI models, including GPT-5.5 and GPT-5.4, to the Bedrock APIs you already use, with unified security, governance, and cost controls. No additional infrastructure to configure, no new security model to learn. Codex on Amazon Bedrock (Limited preview) lets you access the OpenAI coding agent within your existing AWS environments, authenticating with your AWS credentials, processing inference through Bedrock, and applying Codex usage toward your AWS cloud commitments. Codex on Bedrock is available through the Bedrock API, starting with the Codex CLI, the Codex desktop app, and a Visual Studio Code extension. Amazon Bedrock Managed Agents, powered by OpenAI (Limited preview) combines OpenAI frontier models with AWS infrastructure to build production-ready OpenAI-powered agents in the cloud, built with the OpenAI harness for faster execution, sharper reasoning, and reliable steering of long-running tasks.

To learn more, visit Top announcements of the What’s Next with AWS, 2026.

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

• Amazon EC2 M8in and M8ib instances are now generally available – Powered by custom 6th-gen Intel Xeon Scalable processors and 6th-gen AWS Nitro cards, these instances deliver up to 43% higher performance over M6in and M6ib. M8in offers 600 Gbps network bandwidth, while M8ib delivers up to 300 Gbps EBS bandwidth. Available in US East (N. Virginia), US West (Oregon), Asia Pacific (Tokyo), and Europe (Spain).
• Amazon EC2 R8in and R8ib instances are now generally available – Memory-optimized instances built on the same 6th-gen Intel Xeon Scalable processors and Nitro cards, with the same 600 Gbps network and 300 Gbps EBS bandwidth profiles. Well-suited for large commercial databases, data lakes, and in-memory databases such as SAP HANA. Available in US East (N. Virginia, Ohio), US West (Oregon), and Europe (Spain).
• Amazon EC2 C8ine and M8ine instances are now generally available – Network-optimized instances offering up to 2.5x higher packet performance per vCPU and up to 2x higher network throughput for traffic through internet gateways compared to C6in and M6in. Designed for security and network virtual appliances including virtual firewalls, load balancers, and 5G UPF workloads. Available in US East (N. Virginia), US West (Oregon), and Asia Pacific (Tokyo) for C8ine; US East (N. Virginia) and US West (Oregon) for M8ine.
• Amazon Bedrock AgentCore adds optimization capabilities (Preview) – AgentCore now offers recommendations, batch evaluations, and A/B tests to complete the observe-evaluate-improve loop for agents in production. Recommendations analyze production traces and evaluation outputs to propose optimized system prompts and tool descriptions, which you can validate with batch evaluations against pre-defined test cases or A/B tests against live traffic. Every recommendation requires your approval before it ships.
• AWS Lambda adds support for Ruby 4.0 – Ruby 4.0, the latest LTS release, is available as a Lambda managed runtime and container base image. It includes support for Lambda advanced logging controls, including JSON structured logs, configurable logging levels, and target CloudWatch log group configuration. Available in all AWS Regions, including China Regions and AWS GovCloud (US).

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:

• Amazon Q Developer end-of-support announcement – Amazon Q Developer IDE plugins and paid subscriptions will reach end of support on April 30, 2027, giving customers 12 months to transition to Kiro. New signups will be blocked starting May 15, 2026, although existing subscriptions can continue to add users. Starting May 29, 2026, Opus 4.6 will no longer be available on Q Developer Pro; Opus 4.5 and other existing models remain available, and the latest coding models including Opus 4.7 are available exclusively on Kiro. Amazon Q Developer in the AWS Management Console and first-party AWS experiences (documentation, mobile app, Slack, and Microsoft Teams) are not affected.
• AWS 10,000 AIdeas Competition: Meet the Winners – AWS announced the 20 winners of the 10,000 AIdeas Competition, a global challenge where builders submitted AI applications built entirely with Kiro and the AWS Free Tier, with submissions from 115 countries narrowed down through four rounds of evaluation and two rounds of community voting. Winners span Global Champions, Regional Champions, Innovation Awards, and Creative Track categories, with cash prizes and AWS credits awarded across each tier.
• AWS Student Builder Groups – AWS Cloud Clubs is evolving to AWS Student Builder Groups. The community now spans 600+ colleges and universities across 63 countries. Existing Cloud Club memberships, badges, and progress carry forward, and Cloud Club Captains become Group Leaders. Membership is open to any learner 18 or older. You can find a group near you on AWS Builder Center or apply to launch a new group on your campus.

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

• AWS Summits – AWS Summits are free in-person events covering cloud and AI. Coming up in May: Singapore (May 6), Tel Aviv (May 6), Warsaw (May 6), Stockholm (May 7), Sydney (May 13–14), Hamburg (May 20), Seoul (May 20), Amsterdam (May 27), Milano (May 28), and Mumbai (May 28).
• AWS Community Days – Community-led conferences planned and delivered by community leaders. Upcoming events include İstanbul, Türkiye (May 9) and Panama City, Panama (May 23).

Visit the AWS Builder Center to meet other builders, contribute solutions, and find resources that help you keep building. You can also browse upcoming AWS-led in-person and virtual events, plus developer-focused sessions.

— 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!

Today at the What’s Next with AWS, Matt Garman, CEO of AWS, Colleen Aubrey, SVP Amazon Applied AI Solutions, Julia White, CMO of AWS, and OpenAI leaders discussed how they and their customers are changing how businesses operate with agents.

Here’s our roundup of the biggest announcements from the event:

Amazon Quick is an AI assistant for work that connects to all of them, learns what matters to you, and takes action on your behalf. Starting today, you can use the new desktop app, sign up for Free and Plus pricing plans, generate visual assets in the chat, and easily connect Quick to even more apps.

• Quick’s new desktop app (Preview): You can create a personalized experience by staying connected to your local files, calendar, and communications without opening a browser.
• New Free and Plus pricing plans for Quick: You can sign up within minutes using your personal email address or existing Google, Apple, Github, or Amazon credentials—no AWS account required.
• Generate visual assets on the fly: Available today, Quick now lets you create polished documents, presentations, infographics, and images directly from the chat interface, no design skills or hours of formatting required.
• Easily connect Quick to even more apps: Available today, Quick is expanding its native integrations to include Google Workspace, Zoom, Airtable, Dropbox, and Microsoft Teams.
• Build custom apps with Quick (Preview): You can use Quick to create intelligent apps, dashboards, and web pages that are deeply connected to the rest of your business using natural language.

To learn more, visit the About Amazon News post.

Amazon Connect is expanding from a single product into a set of four agentic AI solutions designed to work within your existing workflows: Amazon Connect Decisions (supply chains), Talent (hiring), Customer (customer experience), and Health (health care).

• Amazon Connect Decisions is a supply chain planning and intelligence solution that shifts teams from crisis management to proactive planning and decisioning. AI teammates, combining 30 years of Amazon operational science and 25+ specialized supply chain tools, adapt to your business, learn from your team, and continuously improve your operations.
• Amazon Connect Talent (Preview) is an agentic AI hiring solution built for talent acquisition leaders managing scaled hiring. It delivers AI-led interviews, science-backed assessments, and consistent evaluation, helping recruiters hire high quality candidates faster while providing applicants with a flexible interview experience that reduces human preconceptions.
• Amazon Connect Customer, previously known as Amazon Connect, delivers intelligent, personalized customer experiences across voice, chat, and digital channels. Amazon Connect Customer now offers new configuration capabilities that enable organizations to set up conversational AI in weeks, not months, and configure experiences without technical expertise.
• Amazon Connect Health delivers agentic patient verification, appointment management, patient insights, ambient documentation, and medical coding — giving patients faster access to care, clinicians more time for care, and staff capacity for specialized work.

To learn more, visit the About Amazon News post.

AWS and OpenAI expanded partnership
AWS and OpenAI are bringing the latest OpenAI models to Amazon Bedrock, launching Codex on Amazon Bedrock, and launching Amazon Bedrock Managed Agents, powered by OpenAI (all in limited preview), giving enterprises the frontier intelligence they want on the infrastructure they trust.

• OpenAI models on Amazon Bedrock (Limited preview): The latest OpenAI models, including GPT-5.5 and GPT-5.4, will be available in preview on Amazon Bedrock. Use OpenAI’s frontier models through the same Bedrock APIs you already rely on, with unified security, governance, and cost controls. No additional infrastructure to configure, no new security model to learn.
• Codex on Amazon Bedrock (Limited preview): You can access the OpenAI coding agent within the AWS environments where they already operate at scale. You can authenticate using their AWS credentials, process inference through Amazon Bedrock infrastructure, and apply Codex usage toward their AWS cloud commitments. Codex on Bedrock is available through the Bedrock API, starting with the Codex CLI, the Codex desktop app, and Visual Studio Code extension.
• Amazon Bedrock Managed Agents, powered by OpenAI (Limited preview): Amazon Bedrock Managed Agents combines frontier AI models with trusted AWS infrastructure, enabling customers to quickly and easily build production-ready OpenAI-powered agents in the cloud. It is built with the OpenAI harness, which is engineered to unlock the full potential of OpenAI frontier models, delivering faster execution, sharper reasoning, and reliable steering of long-running tasks.

To learn more, visit the AWS What’s New post and About Amazon News post.

Updated on April 29th – Added a new Quick feature to build custom applications using natural language.

Late March took me to Seattle for the Specialist Tech Conference, one of the most energizing gatherings of AWS specialists from around the world.

It was an incredible opportunity to connect with peers, exchange experiences, and go deep on the latest advancements in Generative AI and Amazon Bedrock — and a powerful reminder of something I truly believe in: when specialists come together to challenge each other, explore edge cases, and co-create solutions, the impact goes far beyond the meeting room. In a fast-moving space like AI, having a strong internal community isn’t a nice-to-have — it’s a competitive advantage.

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

Headlines
Anthropic partnership: Claude on AWS Trainium and Graviton, and Claude Cowork in Amazon Bedrock – This week, AWS and Anthropic deepened their product collaboration in meaningful ways for builders. Anthropic is now training its most advanced foundation models on AWS Trainium and Graviton infrastructure, co-engineering directly at the silicon level with Annapurna Labs to maximize computational efficiency from the hardware up through the full stack.

Claude Cowork is now available in Amazon Bedrock – Claude Cowork brings Anthropic’s collaborative AI capabilities directly to enterprise builders within the AWS ecosystem, enabling teams to work alongside Claude as a true collaborator, not just a tool. You can now deploy Claude Cowork within your existing Amazon Bedrock environment, keeping your data secure within AWS while leveraging the full power of Claude for team-based AI workflows.

Claude Platform on AWS (Coming soon) – A unified developer experience to build, deploy, and scale Claude-powered applications without leaving AWS. If you’re building with Generative AI on AWS, this is a significant step forward in what you’ll be able to do with Claude directly through Amazon Bedrock.

Meta signs agreement with AWS to power agentic AI on Amazon’s Graviton chips – Meta has signed an agreement to deploy AWS Graviton processors at scale, starting with tens of millions of Graviton cores to power CPU-intensive agentic AI workloads — including real-time reasoning, code generation, search, and multi-step task orchestration.

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

• AWS Lambda functions can now mount Amazon S3 buckets as file systems with S3 Files – You can now mount Amazon S3 buckets as file systems in AWS Lambda using S3 Files, enabling your functions to perform standard file operations without downloading data for processing. Built on Amazon EFS, S3 Files provides the simplicity of a file system with the scalability, durability, and cost-effectiveness of S3 — and multiple Lambda functions can connect to the same file system simultaneously, sharing data through a common workspace. This is particularly valuable for AI and machine learning workloads where agents need to persist memory and share state across pipeline steps.
• Amazon EKS Hybrid Nodes gateway for hybrid Kubernetes networking – Amazon Elastic Kubernetes Service now offers the Amazon EKS Hybrid Nodes gateway, which automates networking between your EKS cluster VPC and Kubernetes Pods running on EKS Hybrid Nodes. You can now eliminate the need to make on-premises pod networks routable or coordinate network infrastructure changes, greatly simplifying hybrid Kubernetes environments. The gateway automatically enables pod-to-pod traffic across cloud and on-premises environments, control plane-to-webhook communication, and connectivity for AWS services like Application Load Balancers, and is available at no additional charge.
• Amazon Aurora Serverless: Up to 30% better performance, smarter scaling, and still scales to zero – Amazon Aurora Serverless just got faster and smarter, with up to 30% better performance than the previous version and an enhanced scaling algorithm designed to handle workloads where multiple tasks compete for resources like busy APIs and agentic AI applications with bursts of activity and long idle windows. You can now run even more demanding workloads serverlessly, paying only for what you use, and automatically scaling to zero when not in use. All improvements are available in platform version 4 at no additional cost.
• Amazon Bedrock AgentCore adds new features to help developers build agents faster – Amazon Bedrock AgentCore introduces a managed harness (preview), the AgentCore CLI, and AgentCore skills for coding assistants, helping developers go from idea to working agent prototype faster. The managed harness lets you define an agent by specifying a model, system prompt, and tools and run it immediately with no orchestration code required and when you’re ready for full control, you can export the harness orchestration as Strands-based code. The AgentCore CLI deploys your agents with the governance and auditability of infrastructure-as-code (AWS CDK today, Terraform coming soon), and is available in 14 AWS Regions at no additional charge.

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:

• Introducing granular cost attribution for Amazon Bedrock – This post walks through how Amazon Bedrock’s granular cost attribution works and covers practical example cost tracking scenarios. You can now tag and track Bedrock usage costs at a finer level of detail — useful for organizations running multiple teams or projects on Bedrock who need precise cost visibility and chargeback capabilities.
• Automating Incident Investigation with AWS DevOps Agent and Salesforce MCP Server – This post (co-written with Salesforce) shows how AWS DevOps Agent, integrated with the Salesforce MCP Server, automates the full lifecycle of infrastructure incident investigation from identifying issues and diagnosing root causes to notifying customers through Salesforce Service Cloud. It’s a compelling real-world example of how AI agents and MCP-based tool connectivity are reshaping DevOps workflows in production, dramatically reducing mean time to resolution.
• Microcredentials from AWS are now free — Here’s why that matters – You can now access AWS microcredentials at no cost through AWS Skill Builder in all countries where the platform is offered. Unlike traditional multiple-choice certifications, microcredentials are hands-on assessments that place builders in simulated business scenarios where they configure, troubleshoot, and optimize directly in a live AWS environment, the same way they would on the job. A great opportunity to validate real cloud skills without a cost barrier.
• Amazon SageMaker AI now supports optimized generative AI inference recommendations – You can now use Amazon SageMaker AI to automatically identify optimized deployment configurations for your generative AI models, including instance type, container, and inference parameters. This new capability takes the guesswork out of tuning inference infrastructure, helping you reduce costs and improve latency for your AI applications in production.

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

• What’s Next with AWS: Tune in on April 28 for What’s Next with AWS, a virtual event featuring the latest announcements and product updates directly from AWS teams. A great opportunity to get up to speed on what’s new before diving into the week’s launches.
• AWS Summits: AWS Summits are free in-person events where you can explore the latest in cloud and AI innovation, learn best practices, and network with builders and experts. Coming up in May: Singapore (May 6), Tel Aviv (May 6), Warsaw (May 6), Stockholm (May 7), Sydney (May 13–14), Hamburg (May 20), Seoul (May 20), Amsterdam (May 27), Bangkok (May 28), Milan (May 28), and Mumbai (May 28). And in June, join us in Los Angeles (June 10). Check the full schedule and register at the link above.
• 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 Athens, Greece (April 28), Vancouver, Canada (May 1), İstanbul, Türkiye (May 9), and Panama City, Panama (May 23). If you’re in Latin America, mark your calendar for the AWS Community Day Belo Horizonte (August 22), registration is open at awscommunityday.com.br.

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!

Last week I had the honor of delivering a commencement speech at the University of Namur (uNamur) for their 2025 graduation ceremony.

Standing in front of freshly minted computer science graduates, I talked about the future of software development in the age of AI. My message to them was simple: AI will not make you obsolete. We’ve seen tools evolve over the decades, from punch cards to IDEs to AI-assisted coding, but the work remains yours, not the tool’s. The developers who will thrive are those who stay curious, think in systems, communicate with precision, and take ownership of what they build. The world needs more people with coding skills, not fewer. AI raises the bar on what we can accomplish, and that’s a good thing.

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

Headlines
Anthropic’s Claude Opus 4.7 is now available in Amazon Bedrock – Anthropic’s most intelligent Opus model is now available in Amazon Bedrock, with improved performance across coding, long-running agents, and professional knowledge work. Claude Opus 4.7 scores 64.3% on SWE-bench Pro and 87.6% on SWE-bench Verified, extending its lead in agentic coding with stronger long-horizon autonomy and complex code reasoning. It also does better on knowledge work tasks like document creation, financial analysis, and multi-step research.

The model runs on Bedrock’s next-generation inference engine with dynamic capacity allocation, adaptive thinking (letting Claude allocate thinking token budgets based on request complexity), and the full 1M token context window. It also adds high-resolution image support for better accuracy on charts, dense documents, and screen UIs. Claude Opus 4.7 is available at launch in US East (N. Virginia), Asia Pacific (Tokyo), Europe (Ireland), and Europe (Stockholm), with up to 10,000 requests per minute per account per Region.

AWS Interconnect is now generally available with a new option to simplify last-mile connectivity – AWS Interconnect brings two managed private connectivity capabilities to general availability. The first, AWS Interconnect – Multicloud, provides Layer 3 private connections between AWS VPCs and other cloud providers (Google Cloud available now, Azure and OCI coming later in 2026). Traffic flows over the AWS global backbone and the partner cloud’s private network, never over the public internet, with built-in MACsec encryption, multi-facility resiliency, and CloudWatch monitoring. AWS published the underlying specification on GitHub under Apache 2.0 so any cloud provider can become an Interconnect partner.

The second capability, AWS Interconnect – Last Mile, simplifies high-speed private connections from branch offices, data centers, and remote locations to AWS through existing network providers. It provisions 4 redundant connections across 2 physical locations automatically, configures BGP routing, activates MACsec encryption and Jumbo Frames by default, and offers bandwidth from 1 Gbps to 100 Gbps adjustable from the console without reprovisioning. Last Mile launches in US East (N. Virginia) with Lumen as the initial partner.

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

• Amazon ECR pull through cache now supports referrer discovery and sync – ECR’s pull through cache now automatically discovers and syncs OCI referrers (image signatures, SBOMs, attestations) from upstream registries into your private repositories. This means end-to-end image signature verification and SBOM discovery workflows work without client-side workarounds.
• AWS Transform is now available in Kiro and VS Code – AWS Transform, the agentic migration and modernization factory, is now accessible via Kiro (as a Power) and VS Code (as an extension). You can run custom transformations for common patterns like Java/Python/Node.js version upgrades and AWS SDK migrations directly from your IDE, with job state shared across the web console, CLI, and IDE.
• Aurora DSQL launches connector for PHP – A new Aurora DSQL Connector for PHP (PDO_PGSQL) simplifies building PHP applications on Aurora DSQL by automatically generating IAM tokens, handling SSL configuration, managing connection pooling, and providing opt-in optimistic concurrency control retry with exponential backoff.
• Amazon Q supports document-level access controls for Google Drive – Amazon Q now enforces document-level access controls for Google Drive knowledge bases, combining indexed ACL replication for fast pre-retrieval filtering with real-time permission checks against Google Drive at query time.
• AWS Secrets Manager now supports hybrid post-quantum TLS – Secrets Manager now supports hybrid post-quantum key exchange using ML-KEM to protect secrets against both current and future quantum computing threats. This is automatically enabled in Secrets Manager Agent 2.0.0+, Lambda Extension v19+, and the CSI Driver 2.0.0+.
• Amazon EC2 C8in and C8ib instances are now generally available – Powered by custom 6th-gen Intel Xeon Scalable processors and 6th-gen AWS Nitro cards, these instances deliver up to 43% higher performance over C6in. C8in offers 600 Gbps network bandwidth (highest among enhanced networking EC2 instances), while C8ib delivers up to 300 Gbps EBS bandwidth (highest among non-accelerated compute instances), scaling up to 384 vCPUs.

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:

• Navigating enterprise networking challenges with Amazon EKS Auto Mode – This post explains how EKS Auto Mode automates Kubernetes networking infrastructure including VPC CNI configuration, load balancer provisioning, and DNS management, reducing operational overhead while preserving enterprise security controls.
• Introducing granular cost attribution for Amazon Bedrock – My colleague Micah talked about this feature last week already, but the blog post came out after last week’s roundup. Amazon Bedrock now automatically attributes inference costs to the specific IAM principal that made each API call, with results flowing into AWS Cost and Usage Reports (CUR 2.0). You can aggregate costs by team, project, or cost center using IAM principal tags and session tags.
• Accelerate development workflows with Amazon EBS Volume Clones – EBS Volume Clones let you create instant, point-in-time copies of EBS volumes that are immediately usable without waiting for data transfer. The post highlights use cases including dev/test environment refreshes, disaster recovery testing, and CI/CD pipeline acceleration.
• Modernize VB6 applications at scale with AWS Transform Custom – A walkthrough of using AWS Transform Custom’s agentic AI capabilities to convert legacy Visual Basic 6.0 applications to modern C# ASP.NET Core web applications, addressing challenges like COM dependencies, ADO-to-Entity Framework migration, and VB6 forms-to-Blazor UI conversion.
• Migrating and decomposing APIs with zero-downtime using CloudFront – A zero-downtime API migration strategy using CloudFront Functions with CloudFront KeyValueStore for intelligent, user-aware traffic routing based on the Strangler Fig pattern. This is similar to what AWS Migration Hub Refactor Spaces offers, but implemented with just CloudFront and edge functions.

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

• AWS Events: Browse upcoming AWS-led in-person and virtual events, startup events, and developer-focused events near you.
• AWS Builder Center: Find community-led events, meetups, and user groups in your area.

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

— seb

Today, we’re announcing Claude Opus 4.7 in Amazon Bedrock, Anthropic’s most intelligent Opus model for advancing performance across coding, long-running agents, and professional work.

Claude Opus 4.7 is powered by Amazon Bedrock’s next generation inference engine, delivering enterprise-grade infrastructure for production workloads. Bedrock’s new inference engine has brand-new scheduling and scaling logic which dynamically allocates capacity to requests, improving availability particularly for steady-state workloads while making room for rapidly scaling services. It provides zero operator access—meaning customer prompts and responses are never visible to Anthropic or AWS operators—keeping sensitive data private.

According to Anthropic, Claude Opus 4.7 model provides improvements across the workflows that teams run in production such as agentic coding, knowledge work, visual understanding,long-running tasks. Opus 4.7 works better through ambiguity, is more thorough in its problem solving, and follows instructions more precisely.

• Agentic coding: The model extends Opus 4.6’s lead in agentic coding, with stronger performance on long-horizon autonomy, systems engineering, and complex code reasoning tasks. According to Anthropic, the model records high-performance scores with 64.3% on SWE-bench Pro, 87.6% on SWE-bench Verified, and 69.4% on Terminal-Bench 2.0.
• Knowledge work: The model advances professional knowledge work, with stronger performance on document creation, financial analysis, and multi-step research workflows. The model reasons through underspecified requests, making sensible assumptions and stating them clearly, and self-verifies its output to improve quality on the first step. According to Anthropic, the model reaches 64.4% on Finance Agent v1.1.
• Long-running tasks: The model stays on track over longer horizons, with stronger performance over its full 1M token context window as it reasons through ambiguity and self-verifies its output.
• Vision: the model adds high-resolution image support, improving accuracy on charts, dense documents, and screen UIs where fine detail matters.

The model is an upgrade from Opus 4.6 but may require prompting changes and harness tweaks to get the most out of the model. To learn more, visit Anthropic’s prompting guide.

Claude Opus 4.7 model in action
You can get started with Claude Opus 4.7 model in Amazon Bedrock console. Choose Playground under Test menu and choose Claude Opus 4.7 when you select model. Now, you can test your complex coding prompt with the model.

I run the following prompt example about technical architecture decision:
Design a distributed architecture on AWS in Python that should support 100k requests per second across multiple geographic regions.

You can also access the model programmatically using the Anthropic Messages API to call the bedrock-runtime through Anthropic SDK or bedrock-mantle endpoints, or keep using the Invoke and Converse API on bedrock-runtime through the AWS Command Line Interface (AWS CLI) and AWS SDK.

To get started with making your first API call to Amazon Bedrock in minutes, choose Quickstart in the left navigation pane in the console. After choosing your use case, you can generate a short term API key to authenticate your requests as testing purpose.

When you choose the API method such as the OpenAI-compatible Responses API, you can get sample codes to run your prompt to make your inference request using the model.

To invoke the model through the Anthropic Claude Messages API, you can proceed as follows using anthropic[bedrock] SDK package for a streamlined experience:

from anthropic import AnthropicBedrockMantle
# Initialize the Bedrock Mantle client (uses SigV4 auth automatically)
mantle_client = AnthropicBedrockMantle(aws_region="us-east-1")
# Create a message using the Messages API
message = mantle_client.messages.create(
    model="anthropic.claude-opus-4-7",
    max_tokens=10000,
    messages=[ 
	    {"role": "user", "content": "Design a distributed architecture on AWS in Python that should support 100k requests per second across multiple geographic regions"}
    ]
)
print(message.content[0].text)

You can also run the following command to invoke the model directly to bedrock-runtime endpoint using the AWS CLI and the Invoke API:

aws bedrock-runtime invoke-model \ 
 --model-id anthropic.claude-opus-4-7 \ 
 --region us-east-1 \ 
 --body '{"anthropic_version":"bedrock-2023-05-31", "messages": [{"role": "user", "content": "Design a distributed architecture on AWS in Python that should support 100k requests per second across multiple geographic regions."}], "max_tokens": 32000}' \ 
 --cli-binary-format raw-in-base64-out \ 
invoke-model-output.txt

For more intelligent reasoning capability, you can use Adaptive thinking with Claude Opus 4.7, which lets Claude dynamically allocate thinking token budgets based on the complexity of each request.

To learn more, visit the Anthropic Claude Messages API and check out code examples for multiple use cases and a variety of programming languages.

Things to know
Let me share some important technical details that I think you’ll find useful.

• Choosing APIs: You can choose from a variety of Bedrock APIs for model inference, as well as the Anthropic Messages API. The Bedrock-native Converse API supports multi-turn conversations and Guardrails integration. The Invoke API provides direct model invocation and lowest-level control.
• Scaling and capacity: Bedrock’s new inference engine is designed to rapidly provision and serve capacity across many different models. When accepting requests, we prioritize keeping steady state workloads running, and ramp usage and capacity rapidly in response to changes in demand. During periods of high demand, requests are queued, rather than rejected.

Now available
Anthropic’s Claude Opus 4.7 model is available today in the US East (N. Virginia), Asia Pacific (Tokyo), Europe (Ireland), and Europe (Stockholm) Regions; check the full list of Regions for future updates. To learn more, visit the Claude by Anthropic in Amazon Bedrock page and the Amazon Bedrock pricing page.

Give Anthropic’s Claude Opus 4.7 a try in the Amazon Bedrock console today and send feedback to AWS re:Post for Amazon Bedrock or through your usual AWS Support contacts.

— Channy

Updated on April 17, 2026 – Fixed code samples and CLI commends to align new version.

Updated on May 30, 2026 – Removed requests per minute (RPM) quotas in Bedrock.

In my last Week in Review post, I mentioned how much time I’ve been spending on AI-Driven Development Lifecycle (AI-DLC) workshops with customers this year. A common theme in those sessions is the need for better cost visibility. Teams are moving fast with AI, but as they go from experimenting to full production, finance and leadership really need to know who is using which resources and at what cost. That’s why I was so excited to see the launch of Amazon Bedrock new support for cost allocation by IAM user and role this week. This lets you tag IAM principals with attributes like team or cost center and then activate those tags in your Billing and Cost Management console. The resulting cost data flows into AWS Cost Explorer and the detailed Cost and Usage Report, giving you a clear line of sight into model inference spending. Whether you’re scaling agents across teams, tracking foundation model use by department, or running tools like Claude Code on Amazon Bedrock, this new feature is a game changer for tracking and managing your AI investments. You can get all the details on setting this up in the IAM principal cost allocation documentation.

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

Headlines
Amazon Bedrock now offers Claude Mythos Preview – Anthropic’s most sophisticated AI model to date is now available on Amazon Bedrock as a gated research preview through Project Glasswing. Claude Mythos introduces a new model class focused on cybersecurity, capable of identifying sophisticated security vulnerabilities in software, analyzing large codebases, and delivering state of the art performance across cybersecurity, coding, and complex reasoning tasks. Security teams can use it to discover and address vulnerabilities in critical software before threats emerge. Access is currently limited to allowlisted organizations, with Anthropic and AWS prioritizing internet critical companies and open source maintainers.

AWS Agent Registry for centralized agent discovery and governance now in preview – AWS launched Agent Registry through Amazon Bedrock AgentCore, providing organizations with a private catalog for discovering and managing AI agents, tools, skills, MCP servers, and custom resources. The registry helps teams locate existing capabilities rather than duplicating them, with semantic and keyword search, approval workflows, and CloudTrail audit trails. It is accessible via the AgentCore Console, AWS CLI, SDK, and as an MCP server queryable from IDEs.

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

• Announcing Amazon S3 Files, making S3 buckets accessible as file systems – Amazon S3 Files transforms S3 buckets into shared file systems that connect any AWS compute resource directly with your S3 data. Built on Amazon EFS technology, it delivers full file system semantics with low latency performance, caching actively used data and providing multiple terabytes per second of aggregate read throughput. Applications can access S3 data through both file system and S3 APIs simultaneously without code modifications or data migration.
• Amazon OpenSearch Service supports Managed Prometheus and agent tracing – Amazon OpenSearch Service now provides a unified observability platform that consolidates metrics, logs, traces, and AI agent tracing into a single interface. The update includes native Prometheus integration with direct PromQL query support, RED metrics monitoring, and OpenTelemetry GenAI semantic convention support for LLM execution visibility. Operations teams can correlate slow traces to logs and overlay Prometheus metrics on dashboards without switching between tools.
• Amazon WorkSpaces Advisor now available for AI powered troubleshooting – AWS launched Amazon WorkSpaces Advisor, an AI powered administrative tool that uses generative AI to help IT administrators troubleshoot Amazon WorkSpaces Personal deployments. It analyzes WorkSpace configurations, detects problems automatically, and provides actionable recommendations to restore service and optimize performance.
• Amazon Braket adds support for Rigetti’s 108 qubit Cepheus QPU – Amazon Braket now offers access to Rigetti’s Cepheus-1-108Q device, the first 100+ qubit superconducting quantum processor on the platform. The modular design features twelve 9 qubit chiplets with CZ gates that offer enhanced resilience to phase errors. It supports multiple frameworks including Braket SDK, Qiskit, CUDA-Q, and Pennylane, with pulse level control for researchers.

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:

• Building automated AWS Regional availability checks with Amazon S3– Storage blog post on implementing automated systems for monitoring service availability across AWS regions using Amazon S3 as core infrastructure.
• Understanding Amazon Bedrock model lifecycle – Machine learning blog post that walks through the stages foundation models go through in Bedrock from availability through deprecation, helping teams plan for model updates and manage version dependencies in production.
• Building memory intensive apps with AWS Lambda managed instances – Compute blog post exploring how Lambda managed instances extend the platform beyond lightweight workloads to support memory intensive applications while maintaining serverless benefits.
• Deploy OpenClaw on AWS: Choose the right options for your AI workload – Builder Center guide comparing four AWS deployment options for OpenClaw: Amazon Lightsail for individual developers, Amazon EC2 for startups needing deeper AWS integration, Amazon Bedrock AgentCore for serverless multiuser scenarios, and Amazon EKS for enterprises requiring VM level isolation and advanced orchestration.
• We’re bringing back the Kiro startup credits program – Kiro is relaunching its startup credits initiative, offering eligible early stage companies complimentary access to Kiro Pro+ for up to one year. The three tier program (Starter, Growth, Scale) provides 2 to 30 users based on team size, with rolling applications accepted globally.

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

• What’s Next with AWS (April 28, Virtual) Join this livestream at 9am PT for a candid discussion about how agentic AI is transforming how businesses operate. Featuring AWS CEO Matt Garman, SVP Colleen Aubrey, and OpenAI leaders discussing emerging agent capabilities, Amazon’s internal experiences, and new agentic solutions and platform capabilities.

Browse here for upcoming AWS led in person and virtual events, startup events, and developer focused events.

---

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

~ micah

Last week, I visited AWS Hong Kong User Group with my team. Hong Kong has a small but strong community, and their energy and passion are high. They recently started a new AI user group, and we hope more people will join. I was able to strengthen my bond with the community through great food and conversation.

This week, I’ll first take a closer look at some of the key launches.

AWS DevOps Agent and Security Agent GA
At the last re:Invent, we introduced the concept of frontier agents that work autonomously across multiple steps to achieve outcomes, operating continuously until the job is done. The first two—AWS DevOps Agent and AWS Security Agent—are now generally available after the preview.

AWS DevOps Agent helps you run cloud operations—investigating incidents, reducing time to resolution, and preventing issues before they happen. Customers like United Airlines, Western Governors University, and T-Mobile are already using DevOps Agent to accelerate incident response and simplify operations at scale. At WGU, resolution time dropped from hours to minutes, and in preview customers report up to 75% lower MTTR and 3 to 5 times faster resolution. Learn more in Sébastien’s preview blog post and GA announcement.

AWS Security Agent brings continuous, context-aware penetration testing into the development lifecycle. This agent operates like a human penetration tester. Customers including LG CNS, HENNGE, and Wayspring are seeing strong results. At LG CNS, teams estimate over 50% faster testing and ~30% lower costs, along with significantly fewer false positives. Learn more in Esra’s preview blog post and GA announcement.

Both are designed to work across AWS cloud, multicloud, and on-prem environments. You can have an always-available teammate that can handle the heavy lifting, so you can focus on what matters most.

AWS Service Availability Updates
When the availability of an AWS service or feature changes, we provide customers guidance in AWS Product Lifecycle Changes on available alternatives and support for migration so that disruptions to your operations are minimized. The following lifecycle changes were updated on March 31, 2026.

• Availability change guide for services in maintenance
  • AWS App Runner
  • AWS Audit Manager
  • AWS CloudTrail – Lake
  • AWS Glue – Ray jobs
  • AWS IoT FleetWise
  • Amazon Application Recovery Controller (ARC) – Readiness Check
  • Amazon Comprehend – Topic Modeling, Event Detection, and Prompt Safety Classification
  • Amazon Rekognition – Streaming Events and Batch Image Content Moderation
  • Amazon Simple Notification Service (Amazon SNS) – Message Data Protection (MDP)
• Availability change guide for services in sunset:
  • AWS Service Management Connector
  • Amazon RDS Custom for Oracle
  • Amazon WorkMail
  • Amazon WorkSpaces – Thin Client
• Services reaching in sunset:
  • Amazon Chime SDK – Proxy Sessions

We understand that changes in availability can impact your operations. For specific guidance, consult the relevant service documentation or contact AWS Support.

Last week’s launches
Here are last week’s launches that caught my attention:

• Amazon ECS announces Managed Daemons for ECS Managed Instances
• New AWS Sustainability console: Scope 1–3 reporting in one place
• Amazon Bedrock AgentCore Evaluations is now generally available
• AWS Transform custom announces general availability of automated codebase analysis
• Amazon CloudWatch launches OpenTelemetry Container Insights for Amazon EKS (Preview)
• New compute-optimized instance bundles for Amazon Lightsail with up to 72 vCPUs
• Amazon CloudFront now supports SHA-256 for signed URLs and signed cookies

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

Additional updates
Here are some additional news items that you might find interesting:

• Architecting for agentic AI development on AWS
• Optimizing data transfer costs when using AWS Network Load Balancer
• Announcing AWS World Sports Innovation Cup – Will your idea change the game?
• 5 Techniques to Stop AI agent hallucinations in production
• Explore the global AWS Community through a 3D interactive globe

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!

— Channy

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

Hello! I’m Daniel Abib, and this is my first AWS Weekly Roundup. I’m a Senior Specialist Solutions Architect at AWS, focused on the generative AI and Amazon Bedrock. With over 28 years of experience in solution architecture, software development, and cloud architecture, I help Startups & Enterprises harness the power of generative AI with Amazon Bedrock. I’ve been at AWS for more than six and a half years, working closely with customers across Latin America, and I’m also passionate about Serverless technologies.

Outside of work and endurance sports, I’m a dedicated father to Cecília (7) and Rafael (4), who keep me busier—and happier— than any distributed system ever could. I’m based in São Paulo, you can find me on LinkedIn and X (@DCABib), where I share insights about generative AI, Amazon Bedrock, AWS serverless services, and the occasional Ironman throwback.

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:

• Amazon Redshift increases performance for new queries in dashboards and ETL workloads by up to 7x — Amazon Redshift now delivers up to 7x faster performance for new queries in dashboards and ETL workloads. Queries you run for the first time — without cached results — now execute significantly faster, reducing wait times for interactive dashboards and accelerating your ETL pipelines. This is particularly impactful for workloads with high query variability where cache hits are less frequent.
• NVIDIA Nemotron 3 Super now available on Amazon Bedrock — NVIDIA Nemotron 3 Super is now available in Amazon Bedrock, expanding the lineup of foundation models you can access through the unified Bedrock API. Nemotron 3 Super is a high-performance language model optimized for tasks such as text generation, complex reasoning, summarization, and code generation. You can now invoke Nemotron 3 Super alongside other foundation models in your existing Bedrock workflows, without managing any infrastructure.
• Introducing Nova Forge SDK, a seamless way to customize Nova models for enterprise AI — Nova Forge SDK provides a streamlined way to fine-tune and customize Amazon Nova models for enterprise use cases. You can adapt Nova models to your domain-specific data and deploy them directly within Amazon Bedrock, reducing the complexity of building tailored AI solutions. The SDK handles the heavy lifting of model customization, letting you focus on your business logic rather than the underlying infrastructure.
• Amazon Corretto 26 is now generally available — Amazon Corretto 26, the latest long-term support (LTS) release of the no-cost, production-ready distribution of OpenJDK, is now generally available. Corretto 26 includes the latest Java language features, performance improvements, and security patches, all backed by long-term support from AWS. You can use it across development and production environments on Amazon Linux, Windows, macOS, and Docker images.
• AWS Lambda now supports Availability Zone metadata — AWS Lambda now provides Availability Zone metadata for your function invocations. You can now identify which Availability Zone your Lambda function is running in, enabling better observability, more informed architectural decisions, and simplified troubleshooting for latency-sensitive and multi-AZ workloads. This is particularly useful when correlating Lambda execution with other AZ-aware services in your architecture.
• Amazon CloudWatch Logs now supports log ingestion using HTTP-based protocol — Amazon CloudWatch Logs now supports ingesting logs using an HTTP-based protocol, making it simpler to send logs from applications and services that use standard HTTP endpoints. You can now route logs to CloudWatch Logs without requiring custom agents or additional SDK integrations, lowering the barrier to centralized log management across your workloads.
• Amazon EKS announces 99.99% Service Level Agreement and new 8XL scaling tier for Provisioned Control Plane clusters — Amazon EKS now offers a 99.99% Service Level Agreement (SLA) for clusters running on Provisioned Control Plane, up from the 99.95% SLA offered on standard control plane. EKS is also introducing the 8XL scaling tier, the largest available Provisioned Control Plane tier, which doubles the Kubernetes API server request processing capacity of the next lower 4XL tier — ideal for large-scale workloads like AI/ML training, high-performance computing (HPC), and large-scale data processing.

Other AWS news
Here are some additional posts and resources that you might find interesting:

• Kiro for students — Kiro is now available for students, giving the next generation of builders access to AI-powered development tools at no cost. As Swami Sivasubramanian shared on LinkedIn, “Students are the future decision-makers shaping technology” — and Kiro gives them hands-on experience building with AI from day one. If you’re a student or know someone who is, this is a great opportunity to start building with AI-assisted development.
• Strands Steering Hooks achieved 100% agent accuracy — The Strands Agents team published results showing that Steering Hooks can achieve 100% agent accuracy, outperforming both prompt engineering and rigid workflow approaches for controlling agent behavior. As Swami highlighted on LinkedIn, building reliable AI agents often means rethinking how we guide model behavior — and Steering Hooks offer a compelling new path to agent reliability.
• Introducing Badges on AWS Builder Center — AWS Builder Center now features badges that recognize your contributions and achievements within the builder community. You can earn badges by sharing solutions, participating in challenges, and engaging with fellow builders. It’s a great way to showcase your expertise and track your growth.
• Keep Building Together: The Power of Community — A thoughtful read on the power of community-driven learning and collaboration in the AWS ecosystem. Whether you’re just getting started with AWS or you’ve been building for years, the builder community is a place to connect, share knowledge, and grow together. I highly recommend checking it out.

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), Bengaluru (April 23–24), Singapore (May 6), Tel Aviv (May 6), and Stockholm (May 7).
• 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 San Francisco (April 10) and Romania (April 23–24).
• AWSome Women Summit LATAM — Taking place on March 28 in Mexico City, this event celebrates and empowers women in cloud technology across Latin America. A fantastic initiative for the LATAM tech community.

Join the AWS Builder Center to connect with builders, share solutions, and access content that supports your development. Browse the AWS Events and Webinars 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!

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 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!

Fiti AWS Student Community Kenya!

Last week was an incredible whirlwind: a round of meetups, hands-on workshops, and career discussions across Kenya that culminated with the AWS Student Community Day at Meru University of Science and Technology, with keynotes from my colleagues Veliswa and Tiffany, and sessions on everything from GitOps to cloud-native engineering, and a whole lot of AI agent building.

JAWS Days 2026 is the largest AWS Community Day in the world, with over 1,500 attendees on March 7th. This event started with a keynote speech on building an AI-driven development team by Jeff Barr, and included over 100 technical and community experience sessions, lightning talks, and workshops such as Game Days, Builders Card Challenges, and networking parties.

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:

• Introducing Amazon Connect Health, Agentic AI Built for Healthcare — Amazon Connect Health is now generally available with five purpose-built AI agents for healthcare: patient verification, appointment management, patient insights, ambient documentation, and medical coding. All features are HIPAA-eligible and deployable within existing clinical workflows in days.
• Policy in Amazon Bedrock AgentCore is now generally available — You can now use centralized, fine-grained controls for agent-tool interactions that operate outside your agent code. Security and compliance teams can define tool access and input validation rules using natural language that automatically converts to Cedar, the AWS open-source policy language.
• Introducing OpenClaw on Amazon Lightsail to run your autonomous private AI agents — You can deploy a private AI assistant on your own cloud infrastructure with built-in security controls, sandboxed agent sessions, one-click HTTPS, and device pairing authentication. Amazon Bedrock serves as the default model provider, and you can connect to Slack, Telegram, WhatsApp, and Discord.
• AWS announces pricing for VPC Encryption Controls — Starting March 1, 2026, VPC Encryption Controls transitions from free preview to a paid feature. You can audit and enforce encryption-in-transit of all traffic flows within and across VPCs in a region, with monitor mode to detect unencrypted traffic and enforce mode to prevent it.
• Database Savings Plans now supports Amazon OpenSearch Service and Amazon Neptune Analytics — You can save up to 35% on eligible serverless and provisioned instance usage with a one-year commitment. Savings Plans automatically apply regardless of engine, instance family, size, or AWS Region.
• AWS Elastic Beanstalk now offers AI-powered environment analysis — When your environment health is degraded, Elastic Beanstalk can now collect recent events, instance health, and logs and send them to Amazon Bedrock for analysis, providing step-by-step troubleshooting recommendations tailored to your environment’s current state.
• AWS simplifies IAM role creation and setup in service workflows — You can now create and configure IAM roles directly within service workflows through a new in-console panel, without switching to the IAM console. The feature supports Amazon EC2, Lambda, EKS, ECS, Glue, CloudFormation, and more.
• Accelerate Lambda durable functions development with new Kiro power — You can now build resilient, long-running multi-step applications and AI workflows faster with AI agent-assisted development in Kiro. The power dynamically loads guidance on replay models, step and wait operations, concurrent execution patterns, error handling, and deployment best practices.
• Amazon GameLift Servers launches DDoS Protection — You can now protect session-based multiplayer games against DDoS attacks with a co-located relay network that authenticates client traffic using access tokens and enforces per-player traffic limits, at no additional cost to GameLift Servers customers.

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

From AWS community
Here are my personal favorite posts from AWS community and my colleagues:

• I Built a Portable AI Memory Layer with MCP, AWS Bedrock, and a Chrome Extension — Learn how to build a persistent memory layer for AI agents using MCP and Amazon Bedrock, packaged as a Chrome extension that carries context across sessions and applications.
• When the Model Is the Machine — Mike Chambers built an experimental app where an AI agent generates a complete, interactive web application at runtime from a single prompt — no codebase, no framework, no persistent state. A thought-provoking exploration of what happens when the model becomes the runtime.

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

• AWS Community GameDay Europe — Think you know AWS? Prove it at the AWS Community GameDay Europe on March 17, a gamified learning event where teams compete to solve real-world technical challenges using AWS services.
• 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 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. Upcoming events include Slovakia (March 11), Pune (March 21), and the AWSome Women Summit LATAM in Mexico City (March 28)

Browse here for upcoming AWS led in-person and virtual events, startup events, and developer-focused events.

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

— seb

Today, we’re announcing the general availability of OpenClaw on Amazon Lightsail to launch OpenClaw instance, pairing your browser, enabling AI capabilities, and optionally connecting messaging channels. Your Lightsail OpenClaw instance is pre-configured with Amazon Bedrock as the default AI model provider. Once you complete setup, you can start chatting with your AI assistant immediately — no additional configuration required.

OpenClaw is an open-source self-hosted autonomous private AI agent that acts as a personal digital assistant by running directly on your computer. You can run AI agents on OpenClaw through your browser to connect to messaging apps like WhatsApp, Discord, or Telegram to perform tasks such as managing emails, browsing the web, and organizing files, rather than just answering questions.

AWS customers have asked if they can run OpenClaw on AWS. Some of them blogged about running OpenClaw on Amazon EC2 instances. As someone who has experienced installing OpenClaw directly on my home device, I learned that this is not easy and that there are many security considerations.

So, let me introduce how to launch a pre-configured OpenClaw instance on Amazon Lightsail more easily and run it securely.

OpenClaw on Amazon Lightsail in action
To get started, go to the Amazon Lightsail console and choose Create instance on the Instances section. After choosing your preferred AWS Region and Availability Zone, Linux/Unix platform to run your instance, choose OpenClaw under Select a blueprint.

You can choose your instance plan (4 GB memory plan is recommended for optimal performance) and enter a name for your instance. Finally choose Create instance. Your instance will be in a Running state in a few minutes.

Before you can use the OpenClaw dashboard, you should pair your browser with OpenClaw. This creates a secure connection between your browser session and OpenClaw. To pair your browser with OpenClaw, choose Connect using SSH in the Getting started tab.

When a browser-based SSH terminal opens, you can see the dashboard URL, security credentials displayed in the welcome message. Copy them and open the dashboard in a new browser tab. In the OpenClaw dashboard, you can paste the copied access token into the Gateway Token field in the OpenClaw dashboard.

When prompted, press y to continue and a to approve with device pairing in the SSH terminal. When pairing is complete, you can see the OK status in the OpenClaw dashboard and your browser is now connected to your OpenClaw instance.

Your OpenClaw instance on Lightsail is configured to use Amazon Bedrock to power its AI assistant. To enable Bedrock API access, copy the script in the Getting started tab and run copied script into the AWS CloudShell terminal.

Once the script is complete, go to Chat in the OpenClaw dashboard to start using your AI assistant!

You can set up OpenClaw to work with messaging apps like Telegram and WhatsApp for interacting with your AI assistant directly from your phone or messaging client. To learn more, visit Get started with OpenClaw on Lightsail in the Amazon Lightsail User Guide.

Things to know
Here are key considerations to know about this feature:

• Permission — You can customize AWS IAM permissions granted to your OpenClaw instance. The setup script creates an IAM role with a policy that grants access to Amazon Bedrock. You can customize this policy at any time. But, you should be careful when modifying permissions because it may prevent OpenClaw from generating AI responses. To learn more, visit AWS IAM policies in the AWS documentation.
• Cost — You pay for the instance plan you selected on an on-demand hourly rate only for what you use. Every message sent to and received from the OpenClaw assistant is processed through Amazon Bedrock using a token-based pricing model. If you select a third-party model distributed through AWS Marketplace such as Anthropic Claude or Cohere, there may be additional software fees on top of the per-token cost.
• Security — Running a personal AI agent on OpenClaw is powerful, but it may cause security threat if you are careless. I recommend to hide your OpenClaw gateway never to expose it to open internet. The gateway auth token is your password, so rotate it often and store it in your environment file not hardcoded in config file. To learn more about security tips, visit Security on OpenClaw gateway.

Now available
OpenClaw on Amazon Lightsail is now available in all AWS commercial Regions where Amazon Lightsail is available. For Regional availability and a future roadmap, visit the AWS Capabilities by Region.

Give a try in the Lightsail console and send feedback to AWS re:Post for Amazon Lightsail or through your usual AWS support contacts.

– Channy