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

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

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

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

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

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

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

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

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

For a full list of AWS blog posts, be sure to keep an eye on the AWS Blogs page.

Learn more about AWS, browse and join upcoming AWS-led in-person and virtual events, startup events, and developer-focused events as well as AWS Summits and AWS Community Days. Join the AWS Builder Center to connect with builders, share solutions, and access content that supports your development.

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

-Micah

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

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

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

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

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

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

The next generation of AWS Resilience Hub in action
To get started, you configure a resilience policy, set up your first system and service, run a failure mode assessment, review the results, and implement the findings.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

— Channy

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

Today, we’re announcing the next generation of Amazon OpenSearch Serverless, a fully managed search and vector engine designed for customers building AI agents. The next generation of OpenSearch Serverless scales from zero to thousands of requests per second and back to zero when idle, offering up to 60% cost savings compared to the cost of OpenSearch Service clusters provisioned for peak capacity.

The next generation of OpenSearch Serverless creates resources in seconds and scales capacity up to 20 times faster than the previous generation. With instant resource creation and native integrations with AI development platforms like Vercel and Kiro, you can deploy production-ready search and vector backends for your AI agents in minutes without managing infrastructure.

The next generation of OpenSearch Serverless in action
To get started with the next generation of OpenSearch Serverless, choose Create collection in the Serverless menu in the Amazon OpenSearch Service console.

Create NextGen collection with instant auto scaling and scale-to-zero for cost optimization. At launch, we support full-text search and vector search only for the collection type. If you want to use the existing OpenSearch Serverless infrastructure, choose Switch to Classic.

Choose Express create, the fastest way to create collection. No configuration is required—the default settings and matching security policies are applied automatically. Some configuration options can be changed later.

When you choose Create collection, OpenSearch Serverless will provision resources in seconds.

You can also create a collection of OpenSearch Serverless with AWS Command Line Interface (AWS CLI) or AWS SDKs. Here is a sample CLI command to create a collection group.

aws opensearchserverless create-collection-group 
    --name channy-nextgen-group 
    --standby-replicas ENABLED 
    --generation NEXTGEN 
    --description "My NextGen collection group" 
    --capacity-limits '{
        "maxIndexingCapacityInOCU": 10,
        "maxSearchCapacityInOCU": 10,
        "minIndexingCapacityInOCU": 0,
        "minSearchCapacityInOCU": 0
    }' 
    --region "us-east-1"

Now, you can create a collection that inherits the generation from its parent collection group. Supported collection types: SEARCH and VECTORSEARCH.

aws opensearchserverless create-collection 
    --name channy-nextgen-collection 
    --type SEARCH 
    --collection-group-name channy-nextgen-group 
    --standby-replicas ENABLED 
    --description "My collection in NextGen group" 
    --region "us-east-1"

To learn more about managing the next generation of OpenSearch Serverless, visit the Amazon OpenSearch Serverless documentation.

Building your agents faster with OpenSearch Serverless
To support building production-ready agent applications in Vercel, you can now create a new OpenSearch collection or connect your existing OpenSearch Serverless collection within the Vercel console. Create a search backend in seconds and add features on-demand as your application grows. To learn more, visit AWS for Vercel.

You can go from idea to working prototype in minutes using Claude Code, Cursor, and Kiro. OpenSearch Agent Skills provide a repository of skills that bring OpenSearch intelligence directly into your agent. Each skill encapsulates domain knowledge, best practices, and multi-step execution logic for a specific workflow–so your agent not only gets results, but understands how they were achieved. You can also use the OpenSearch Launchpad in Kiro Powers to accelerate search applications with guided, end-to-end architecture planning.

Now available
The next generation of Amazon OpenSearch Serverless is generally available today and is available in all AWS commercial Regions where Amazon OpenSearch Serverless is currently available.

The next generation of OpenSearch Serverless charges for the compute you use in OpenSearch Compute Units (OCUs) for indexing, search, and GPU acceleration. You are charged separately for storage in GB-month. For more information, see Amazon OpenSearch Service Pricing.

Give it a try and send feedback to the AWS re:Post for Amazon OpenSearch Service or through your usual AWS Support contacts.

— Channy

The post Introducing the next generation of Amazon OpenSearch Serverless for building your agentic AI applications first appeared on Azalio.

We’re excited to welcome four outstanding community leaders as our newest AWS Heroes. These individuals embody the spirit of collaboration and knowledge sharing that makes the AWS community thrive. From building AI-powered tools that help fellow builders navigate AWS re:Invent, to leading some of the largest AWS communities in Latin America, to sharing deep cloud architecture expertise across blogs and events. Their dedication to lifting others up through education, mentorship, and community organizing inspires builders around the world.

Damiano Giorgi – Pavia, Italy

Artificial Intelligence Hero Damiano Giorgi is a Cloud Solutions Architect focused on AI and its evolution, who transitioned from on-premises (on-prem) systems engineering to AWS and never looked back. He helps organize AWS User Group Pavia and AWS User Group Milan, and shares content on his personal blog, “Bass and Bytes.” Damiano developed the “Unofficial post:Invent Session Suggester,” powered by Amazon Bedrock and Amazon Nova, to help builders find AWS re:Invent sessions matching their interests. He speaks at conferences across Europe including AWS Summit Milan, AWS Community Day Italy, Adria, Greece, and the Netherlands.

Darryl Ruggles – Ottawa, Canada

Serverless Hero Darryl Ruggles is a Cloud Solutions Architect who spent many years as a software developer before focusing on AWS application and AI/ML architectures. He shares knowledge across serverless, containers, AI/ML, and FinOps through his blog, LinkedIn, and published projects. Darryl is an active member of many online AWS communities including “Believe In Serverless” and loves interacting with the community at events both online and in person.

Ricardo Daniel Ceci – Buenos Aires, Argentina

Artificial Intelligence Hero Ricardo Daniel Ceci leads the AWS User Group Buenos Aires, which is the largest AWS community in Argentina with nearly 2,400 members. He is also the principal organizer of the AWS Community Day Argentina and was recognized as the AWS Community Leader of the Year 2025 for LATAM. Ricardo hosts a podcast featuring conversations with cloud experts, AWS Heroes, and developer advocates across Latin America. He has over fifteen years of experience in cloud and web development, and is passionate about empowering Spanish-speaking builders and lowering the barrier to cloud and AI across LATAM.

Matias Kreder – Buenos Aires, Argentina

Artificial Intelligence Hero Matias Kreder is an AWS Certification Subject Matter Expert (SME) who contributed to multiple AI/ML certifications, including the AWS Certified AI Practitioner exam. His journey began with AWS DeepRacer where he qualified three times as a finalist, which sparked his community work organizing racing events and ML talks across the region. As an AWS User Group Leader for Buenos Aires, he organized the AWS Community Day Argentina 2025 and speaks at community events throughout LATAM.

Learn More

Visit the AWS Heroes webpage if you’d like to learn more about the AWS Heroes program, or to connect with a Hero near you.

— Taylor

The post Meet Our Newest AWS Heroes – May 2026 first appeared on Azalio.

There’s something genuinely energizing about working with startups — something I’ve been doing intensely for more than two years now. Startups operate at a different frequency: the urgency is real, the constraints are tight, and the stakes are personal. Helping them navigate the challenge of proving their business model requires not just technical depth but a willingness to move fast, challenge assumptions, and make bets on the right architecture before the perfect data exists.

What I love most is that the work is never abstract: every decision I help a startup make has a direct impact on whether they ship on time, stay within budget, and earn the next round of confidence from their investors.

Let’s dive into this week’s AWS news.

Headlines
Now Open — AWS Local Zones in Istanbul, Türkiye — AWS has opened a new Local Zone in Istanbul, Türkiye, bringing AWS compute, storage, and networking services to one of Europe’s largest metropolitan areas. AWS Local Zones place AWS infrastructure much closer to large population and industry, enabling organizations to store and process data within specific jurisdictions to meet data residency requirements, while delivering single-digit millisecond latency for applications that need to run closer to end users. This supports compliance needs across financial services, government, telecoms, and healthcare.

A Local Zone is a significant infrastructure investment: it requires the same level of operational excellence as a Region, with consistent hardware, power, and networking infrastructure, and reflects AWS’s continued expansion into underserved markets.

For builders in Türkiye, this opens up a new set of architectural possibilities. You can now store and back up data within Turkish borders to help meet data residency requirements, and run latency-sensitive workloads in the Istanbul Local Zone while connecting seamlessly to the AWS Region—giving you the flexibility to architect hybrid applications without managing your own data center infrastructure.

To learn more about our decade-long commitment, available services, customers and partners in Türkiye, visit the launch blog post.

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

• Security Hub Extended expands to 21 curated partner solutions across 9 categories — AWS Security Hub Extended now integrates with 21 curated partner security solutions spanning 9 categories, including endpoint protection, cloud security posture management, threat intelligence, and more. You can now get consolidated, prioritized security findings from a broader ecosystem of tools directly within Security Hub, without requiring custom integrations. This is particularly valuable for enterprise security teams that want a unified view of their security posture across AWS and third-party tooling.
• Amazon SageMaker AI now supports OpenAI-compatible APIs for inference endpoints — You can now call Amazon SageMaker AI inference endpoints using OpenAI-compatible APIs, making it significantly easier to migrate AI workloads from OpenAI to SageMaker — or to build applications that work across multiple providers — with no SDK changes required. This lowers the migration barrier for teams that started prototyping with OpenAI and are now looking to move to a more scalable, cost-controlled infrastructure on AWS. Your existing application code works as-is; you simply point it at your SageMaker endpoint.
• Introducing pre-fetching and IAM role assumption for AWS Secrets Manager Agent — The AWS Secrets Manager Agent can now pre-fetch secrets at startup and assume IAM roles to retrieve them, eliminating the cold-start latency associated with on-demand secret retrieval in latency-sensitive applications. You can configure the agent to preload the secrets your application needs before it starts serving traffic, reducing the risk of secrets-related latency spikes in production. IAM role assumption support also makes it easier to share the agent across workloads with different permission boundaries.
• AWS announces ExtendDB, an open-source DynamoDB-compatible adapter — AWS has open-sourced ExtendDB, a DynamoDB-compatible adapter that allows you to use the DynamoDB API and data model on top of alternative backend storage systems. This is particularly useful for local development and testing workflows — you can write against the DynamoDB API without requiring a live AWS connection. It’s also valuable for scenarios where you need DynamoDB-compatible semantics with more control over the underlying storage layer. It’s a practical tool for teams that want to build portability into their data access layer.
• AWS SAM CLI adds AWS CloudFormation Language Extensions support to accelerate local serverless development — The AWS SAM CLI now supports AWS CloudFormation Language Extensions locally, meaning you can use transforms, dynamic references, and other CloudFormation language features directly in your local development and testing workflows. This closes a long-standing gap between what you can test locally and what runs in production, making local serverless development faster and more reliable. If you build serverless applications with SAM and encounter edge cases in local testing, this update will meaningfully improve your experience.

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 Bedrock introduces new advanced prompt optimization and migration tool — This post covers the newly launched Advanced Prompt Optimization and Migration Tool in Amazon Bedrock, which helps you automatically tune your prompts for better model performance and assists you in migrating prompts across different foundation models. It’s a must-read if you’re iterating on prompt quality for production AI workloads.
• Introducing Kiro Web — Kiro, AWS’s AI-powered development environment, now has a web-based interface. Kiro Web lets you access Kiro’s spec-driven development, AI chat, and agent capabilities directly from your browser, without needing to install the desktop IDE. This is a great step toward making AI-assisted development more accessible — whether you’re doing a quick review, prototyping from a new machine, or introducing your team to the Kiro workflow.
• Announcing updated retry behavior for AWS SDKs and Tools — AWS has updated the default retry behavior across its SDKs and CLI tools, improving resilience for transient errors without requiring configuration changes from developers. The updated behavior includes smarter backoff strategies and better handling of throttling responses. If you’re running production workloads that occasionally hit API rate limits or transient failures, this update improves reliability out of the box. It’s worth reading to understand what changed and how it affects your applications.
• Bitnami image removal from ECR Public — AWS has announced that Bitnami container images will be removed from Amazon ECR Public. If your workloads pull Bitnami images from ECR Public, you should review this post to understand the timeline and migration path. The Bitnami images remain available directly from Bitnami’s own registry, and this post explains how to update your image references to continue pulling them without interruption.

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

• AWS Summit Amsterdam — Join us in Amsterdam on May 27 for a full day of cloud and AI sessions, hands-on labs, and networking with builders and AWS experts from across Europe. Registration is free.
• AWS Summit Bangkok — AWS Summit Bangkok takes place on May 28. It’s a fantastic opportunity for builders and customers across Southeast Asia to connect and explore the latest in cloud innovation.
• AWS Summit Milan — Also on May 28, AWS Summit Milan brings the AWS community together in Italy. If you’re in Southern Europe, this is your event.
• AWS Summit Mumbai — Also on May 28, AWS Summit Mumbai brings cloud and AI content to builders across India. Check the link for the full agenda and registration.
• AWS Summit Los Angeles — Mark your calendar for June 10 in Los Angeles. The AWS Summit LA is coming up and it’s a great opportunity to connect with the West Coast builder community.
• AWS Community Days — Community-led conferences where content is planned, sourced, and delivered by community leaders. If you’re in Latin America, don’t miss AWS Community Day Belo Horizonte on 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!

The post AWS Weekly Roundup: AWS Local Zones in Istanbul, open-source ExtendDB, Kiro Web, and more (May 25, 2026) first appeared on Azalio.

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

The post AWS Weekly Roundup: AWS Transform at 1 year, Claude Platform on AWS, EC2 M3 Ultra Mac instances, and more (May 18, 2026) first appeared on Azalio.

I have been building with AI agents and MCP tools for a while now, and one question kept coming up: how do you give an agent real, authenticated access to AWS without handing it the keys to the kingdom? Today, there is an answer.

I’m happy to announce the general availability of the AWS MCP Server, 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.

The AWS MCP Server is part of the Agent Toolkit for AWS, a suite of tooling that includes the MCP Server, skills, and plugins that help coding agents build more effectively and efficiently on AWS.

AI coding agents are already useful for many tasks, but they run into real trouble when working with AWS at any meaningful depth. Without access to current AWS documentation, agents rely on training data that may be months out of date and may not know about services like Amazon S3 Vectors, Amazon Aurora DSQL, or Amazon Bedrock AgentCore. When asked to build infrastructure, they tend to reach for the AWS Command Line Interface (AWS CLI) rather than AWS Cloud Development Kit (AWS CDK) or AWS CloudFormation, and they produce AWS Identity and Access Management (IAM) policies that are far broader than necessary. The result is infrastructure that works in a demo but is not production-ready.

The AWS MCP Server addresses this through a compact set of tools that do not consume your model’s context window. The call_aws tool executes any of the 15,000+ AWS API operations using your existing IAM credentials. When we will launch new APIs, they will be supported within days. The search_documentation and read_documentation tools retrieve current AWS documentation and best practices at query time, so the agent always works from up-to-date information.

With general availability, we are introducing several new capabilities. The AWS MCP Server now supports IAM context keys, so you no longer need a separate IAM permission to use the server and can express fine-grained access in a standard IAM policy. Documentation retrieval no longer requires authentication. We have also reduced the number of tokens required per interaction, which matters for complex, multi-step workflows.

Also new, the run_script tool lets the agent write a short Python script that runs server-side in a sandboxed environment. The sandbox inherits your IAM permissions but has no network access, so you can give an agent the ability to process data without giving it access to your local file system or a shell. When an agent needs to call multiple APIs and combine the results, making them one at a time is slow and burns context. With run_script, the agent chains API calls, filters responses, and computes results in a single round-trip, which is both faster and more context-efficient.

The most significant addition is the transition from Agent SOPs to Skills. Skills provide curated guidance and best practices for the tasks where agents most commonly make mistakes. This helps agents complete work faster, using validated best practices, with fewer errors and fewer tokens — all of which saves you time and money. Skills are contributed and maintained by AWS service teams. This keeps the tool list short and predictable, which reduces hallucination and keeps the agent focused.

For enterprise customers, the AWS MCP Server provides a clear separation between human and agent permissions. You can use IAM policies or Service Control Policies to specify that a given user can perform mutating operations while the MCP server is restricted to read-only actions. Amazon CloudWatch metrics published under the AWS-MCP namespace let you observe MCP server calls separately from direct human calls, giving you the audit trail that compliance teams require. Amazon CloudTrail captures all API calls for a complete record.

Let’s see it in action
For this demo, I chose to use Claude Code, but I can use the AWS MCP Server with any AI agent that supports MCP, which is basically all tools available today: Kiro CLI, Kiro, Cursor, Codex, and more. I configure Claude Code to use the Anthropic Opus 4.6 model.

Opus 4.6 has a knowledge cutoff date in May 2025. It means it doesn’t know anything that happened after May last year. I ask a question about an AWS service that was introduced recently: Amazon S3 Vectors, launched in preview in July 2025 and that went GA in December 2025.

The question is “how to store embedding on S3″. (embedding is a kind of vector)

It gives me five solutions, all correct, but none using S3 Vectors as I asked. Note that this answer comes from the Opus 4.6 model, not from Claude Code. Any AI tool using the same model will return similar answers because S3 Vectors wasn’t announced at the time the model was trained.

Let’s now try with the AWS MCP Server.

The AWS MCP Server uses AWS Identity and Access Management (IAM) and IAM SigV4 authentication. To use my local AWS credentials configuration over MCP, which only supports OAuth 2.1, I configure my AI coding agent to call the AWS MCP Server through a proxy. The MCP Proxy for AWS is an open source proxy that runs on my machine and bridges the world of IAM authentication to OAuth.

I add the MCP configuration with this command:

claude mcp add-json aws-mcp --scope user 
   '{"command":"uvx","args":["mcp-proxy-for-aws@latest","https://aws-mcp.us-east-1.api.aws/mcp","--metadata","AWS_REGION=us-west-2"]}'

Let’s analyze the JSON configuration:

• I use the user scope to make the server available to all my projects on my laptop.
• uvx mcp-proxy-for-aws is the command to launch the proxy; the rest of the arguments are parameters passed to the proxy.
• https://aws-mcp.us-east-1.api.aws/mcp is one of the two regional endpoints for the AWS MCP Server. The proxy will forward Claude Code’s requests to that endpoint.
• --metadata are passed to the proxy target. Here, it tells the AWS MCP Server to use the US West (Oregon) Region.

I start Claude Code and I type /mcp to verify the AWS MCP Server is correctly installed and can use my credentials.

I ask the same question: “how can I store embedding on S3”.

This time, Claude Code knows it has a tool it can use to answer the question. It asks me permission to invoke the aws___search_documentation tool. After a few seconds, I receive a correct answer: “AWS now has a dedicated service for this: Amazon S3 Vectors …”

Pricing and availability
The AWS MCP Server is available today in the US East (N. Virginia) and Europe (Frankfurt) AWS Regions and can make API calls to any Region. There is no additional charge for the AWS MCP server itself. You pay only for the AWS resources you create and any applicable data transfer costs.

The AWS MCP Server works with Claude Code, Kiro, Cursor, and any MCP-compatible client. To get started, see the AWS MCP Server User Guide.

I have been waiting for something like this since I started using MCP tools in my AI agents early last year. The combination of current documentation, authenticated API access, and sandboxed script execution in a single server changes what an agent can actually do on AWS. I am curious what you build with it. Let me know in the comments.

— seb

The post The AWS MCP Server is now generally available first appeared on Azalio.

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 in public preview at no additional cost in US East (N. Virginia, Ohio), US West (Oregon), Canada (Central), Europe (Frankfurt, Ireland, Paris), and Asia (Tokyo, Mumbai, Sydney, Seoul, Singapore) Regions.

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

The post Modernize your workflows: Amazon WorkSpaces now gives AI agents their own desktop (preview) first appeared on Azalio.

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.

The ruins of Whitby Abbey in North Yorkshire. Stones that have seen a thousand years, while this week alone brought another wave of change.

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!

The post AWS Weekly Roundup: What’s Next with AWS 2026, Amazon Quick, OpenAI partnership, and more (May 4, 2026) first appeared on Azalio.

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: Also available today, Quick is expanding its native integrations to include Google Workspace, Zoom, Airtable, Dropbox, and Microsoft Teams.

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 extended 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.

The post Top announcements of the What’s Next with AWS, 2026 first appeared on Azalio.