Last week, we announced a public preview of Amazon Bedrock Managed Agents powered by OpenAI, built on a customized version of OpenAI’s Agents API engineered to be AWS-native and integrated with AWS resources. You can now build agents optimized for OpenAI models that run entirely inside AWS with the identities, permissions, and governance controls you already use.

You can choose an execution environment: self-hosted compute to use an existing development machine, container, or compute environment or Amazon Bedrock AgentCore Runtime, for managed runtime sessions and configurable storage in your AWS account. To learn more, visit the Amazon Bedrock documentation.

In addition, we are adding new frontier models on Amazon Bedrock to expand your model choices:

• OpenAI GPT-6.1 Sol: An upgrade to GPT-6 Sol, GPT-6.1 Sol delivers exceptionally strong performance on agentic coding, computer use, and professional work. According to OpenAI, it approaches GPT-6 Astra across demanding evaluations at roughly one-fifth of the cost, giving developers more room to build and run capable agents at scale. To learn more, visit the GPT-6.1 Sol model card.
• OpenAI GPT-6 Astra UltraFast mode: Ultrafast is a premium speed tier for GPT-6 Astra, built for workloads where speed matters most. According to OpenAI, Ultrafast delivers up to 6x faster inference in the API, with up to 300 tokens per second. The Amazon Bedrock inference engine delivers the performance, security, and reliability required for production workloads. To learn more, visit the GPT-6 Astra model card.
• Anthropic Claude Sonnet 5.5: Claude Sonnet 5.5 is a smarter, more efficient Sonnet and a step up from Sonnet 5, making it a natural upgrade for teams already building on Sonnet. It’s stronger for coding, completing well-scoped tasks as part of a larger coding strategy such as building and fixing features with Claude in the same session or verifying output against requirements. To learn more, visit the Claude Sonnet 5.5 model card.
• SpaceXAI Grok 4.7: Grok 4.7 builds on Grok 4.6 with better mixed-document handling, more dependable repo-scale coding with planning and error recovery, and enhanced browser-use agents for form fills and portal navigation. To learn more, visit the Grok 4.7 model card.

Last week’s launches
Here are some launches that got my attention:

• AWS Well-Architected Agent (preview): You can use an AI-powered agent service that analyzes your AWS environment to deliver targeted, contextual recommendations for improving your applications’ cost, security, performance, and resilience. The agent analyzes your infrastructure, understands your unique business goals, and delivers contextual recommendations.
• Amazon Aurora PostgreSQL supports direct querying of Apache Iceberg and Parquet data: You can directly query operational data together with data stored in data lakes in Apache Iceberg and Parquet formats using your existing PostgreSQL applications and tools, without extract, transform, and load (ETL) pipelines or data duplication.
• Amazon S3 Tables support all Apache Iceberg V3 data types: Amazon S3 Tables add support for geometry, geography, unknown, and nanosecond timestamp data types, along with column default values, as defined in the Iceberg V3 specification. You can now store geospatial coordinates and nanosecond-precision event times natively instead of encoding them in strings or integers.

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

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 September 29, 2026.

Services moving to Maintenance (no longer accessible to new customers starting October 29, 2026):

Services entering Sunset:

Services reaching End of Support (as of September 29, 2026):

• Amazon Mechanical Turk

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

Other AWS news
Here are some additional projects and news items you may find interesting:

• Introducing Kiro workflows: Kiro workflows enable you to carry out complex tasks from start to finish with multiple agents and less supervision. We’ve been building Kiro itself with workflows, including the new cloud configuration, cloud sessions, and most of the workflow experience.
• Introducing Strands Decider: Strands Decider is one of a new class of decision models or system one models, a type of model that has been gaining significant attention since TypeSafe AI’s launch of Jev earlier this month. Strands Decider 2B is a small, open source, decision model optimized for fast experimentation, local development, and innovation.
• New FDE pathways for AWS Partners: On June 30, AWS announced the Forward Deployed Engineering (FDE) organization, backed by a $1 billion investment, and extended this hands-on delivery approach to AWS Partners through the Partner-Led FDE motion. Now, AWS Partners have a structured way to build and validate that depth with three new Partner FDE pathways and credentials that recognize the applied proficiency required to deliver production agentic AI.

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 upcoming AWS re:Invent and AWS Community Days. Join the AWS Builder Center to connect with builders, share solutions, and access content that supports your development.

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

— Channy

The post AWS Weekly Roundup: Amazon Bedrock Managed Agents powered by OpenAI, Q3 service availability updates, Kiro workflows, and more (October 5, 2026) appeared first on The NOKIA Blog.

Today, we’re excited to introduce the newest members of the AWS Heroes program. AWS Heroes are a vibrant, worldwide group of AWS experts who go above and beyond to share knowledge, mentor others, and build thriving communities. These individuals make a real difference in helping developers and organizations succeed with AWS.

This month, we welcome three exceptional community leaders from across the globe, each bringing unique expertise and a deep commitment to empowering builders everywhere.

Avinash Shashikant Dalvi – Bengaluru, India

Serverless Hero Avinash Shashikant Dalvi is a tech architect and co-organizer of AWS User Group Bengaluru who is focused on serverless, containers, and production-ready applications on AWS. He has delivered over 40 community talks, publishes the AWS for Product Builders newsletter, and creates technical content covering Amazon ECS, AWS Fargate, AWS Lambda, and AWS Amplify.

Joanne Skiles – Orlando, USA

Serverless Hero Joanne Skiles is an engineering leader and educator with over 16 years of experience building full-stack systems, including serverless architecture and AI systems on AWS. She organizes the Orlando AWS User Group and teaches cloud and AI concepts through her YouTube channel, conference talks, and her podcasts Chaotic Commits and Her Career Unplugged. Joanne is also a professor in the Computer Science department at Rollins College, where she runs the Transparent Systems lab.

Xiaofei Li – Shanghai, China

Community Hero Xiaofei Li is an AWS Golden Jacket holder and is an active community leader in the Greater China Region, leading the Kiro, Amazon Quick, and Tokyo Chinese AWS communities. He founded the Kiro Chinese User Community (5,000+ members) and initiated the Chinese localization of AWS Builder Cards across 15 cities and 3,000+ participants. Xiaofei also mentors underserved students and supports Women in Tech initiatives.

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. To learn more about how to get involved with the AWS community, visit our AWS Builder Center.

— Taylor

The post Celebrating Our Newest AWS Heroes – September 2026 appeared first on The NOKIA Blog.

If there’s one theme that defined last week, it’s choice. The frontier models keep arriving, and the interesting question is no longer just “how smart is it?” but “which model fits this step, at this cost, at this latency?” That’s exactly what landed on Amazon Bedrock over the past few days: GPT-6 Sol and GPT-6 Luna from OpenAI, giving you two new points on the intelligence-versus-efficiency curve, and Claude Opus 5.5 from Anthropic, the first of the Claude 5.5 family.

GPT-6 Sol is built for the demanding, recurring work of development and operations, while GPT-6 Luna makes focused, repeatable tasks practical at high volume, and both ship at significantly lower pricing than their GPT-5.6 predecessors. Claude Opus 5.5, meanwhile, does more with fewer tokens than Opus 5 and is tuned for agentic coding and long-running tasks. What I like about all three is that they push toward the same idea: match the model to the job instead of reaching for the biggest one every time. The other thread was observability catching up to this agentic world, including a launch I had the pleasure of writing about myself.

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 CloudWatch Omni – You can now observe your applications and AI agents together in a single, collaborative experience. Amazon CloudWatch Omni is built on OpenTelemetry, so your existing telemetry shows up with nothing to reconfigure, and your whole team reaches it through one URL with enterprise SSO — no console access required. It auto-discovers your services, maps dependencies, and brings AWS DevOps Agent into investigation sessions to correlate signals and trace root causes. There’s a companion post on the agent-observability side, a deeper dive on the AWS Cloud Operations blog on what observability for the AI era looks like, and the announcement on What’s New with the specifics. If you want the bigger picture, Matt Wood’s Wrong, not broken is a great read on why correctness now has to be measured at the level of the run.

• Enhanced custom event buses in Amazon EventBridge – Amazon EventBridge now offers an enhanced custom event bus purpose-built for organizations scaling event-driven applications across teams and accounts. You can now deploy a single centralized bus shared across every account in your organization through AWS RAM, with optional event ordering, a simplified Subscriber resource that bundles filtering, targets, and retries, content-based deduplication, and synchronous invocation for targets like AWS Lambda. A new ingress/egress pricing model replaces the compounding cross-account routing charges of multi-bus setups, and your existing buses keep working unchanged as “classic.”

• Amazon SageMaker HyperPod Inference Gateway – You can now front your LLM inference on Amazon SageMaker HyperPod with a Kubernetes-native, GPU-aware routing layer that deploys as a single Amazon EKS managed add-on with zero application changes. Instead of round-robin load balancing, it routes on real-time inference signals — KV cache utilization, queue depth, prefix cache hits, predicted latency, and more — cutting first-token latency by up to 82% in mixed-hardware and bursty scenarios. It works with any OpenAI-compatible model server, including vLLM and SGLang.

• AI agent skills for AWS End User Messaging and Amazon SES – You can now build and send messages by asking your AI coding agent in plain language. Amazon SES and AWS End User Messaging publish AI agent skills for the AWS MCP Server, giving your agent step-by-step, validated guidance for tasks like verifying a sending identity, sending a production email, or building a branded RCS agent with cards and buttons. The skills work with Claude Code, Codex, Cursor, and Kiro, so you can complete messaging workflows without hopping between docs and console screens.

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 Strands harness – The Strands Agents team released Strands harness, a fully assembled, general-purpose agent harness you can run locally or deploy anywhere, under Apache 2.0. It takes one line of Python or TypeScript to wire up your model of choice across Amazon Bedrock, Anthropic, OpenAI, Google, or a local Ollama model, and it ships with sensible defaults for prompt caching and context management (truncating bulky tool results, compacting when the context window fills up, and keeping memory across runs). The team reports it costs about 28% less than comparable harnesses on the same models while holding accuracy steady.

• Announcing the new AWS Reimagine report on AI – The AWS Executive in Residence team spent nine months interviewing 154 leaders across 27 countries about what separates organizations that turn AI into value from those that don’t. The report is candid (including where AI hasn’t worked at Amazon), and the recurring insight is that once building gets fast, the bottleneck moves to deciding, funding, and governing the work. Well worth a read if you’re thinking about how your teams adopt AI in practice.

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

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

• AWS re:Invent – AWS re:Invent returns to Las Vegas from November 30 to December 4, and session times, locations, and speakers are live. Reserved seating opens October 6, so register now and be ready to claim your spot in chalk talks, workshops, and builders’ sessions.

• AWS Summits – With re:Invent on the horizon, the Summits are wrapping up for the year. The last stop is Dubai (September 30) at the Dubai World Trade Center, with 60+ sessions, an AWS Village, and hands-on workshops.

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

The post AWS Weekly Roundup: GPT-6 Sol and Luna, Claude Opus 5.5 on Amazon Bedrock, Strands harness, and more (September 28, 2026) appeared first on The NOKIA Blog.

Today, Amazon CloudWatch introduces CloudWatch Omni, a unified observability experience for application and AI workloads that is app-centric, AI-powered, built on open standards, and delivered off-console. CloudWatch Omni is a purpose-built observability, evaluation, and experimentation solution for AI agents. It helps teams design, evaluate, and operate AI agents across any model provider, framework, or runtime, with an eval-driven workflow, support for the tools you already use, and observability delivered where you work: directly in your IDE and through a standalone web experience, separate from the AWS Management Console.

Organizations deploying agentic AI systems face observability challenges that traditional monitoring can’t address. Agent behavior is non-deterministic: a prompt change can degrade response quality even when standard metrics show no errors. Teams spend hours manually reviewing logs across multiple systems, unable to pinpoint what changed or why. Existing tools force teams to choose between siloed generative AI monitoring or fragmented solutions requiring constant context-switching between their coding environment and browser-based dashboards.

CloudWatch Omni captures every trace and includes built-in evaluators for correctness, coherence, retrieval quality, and tool selection, among others. You can compare prompt versions side by side in the playground, build test datasets from production traffic, run experiments across different configurations, and detect regressions automatically.

Two surfaces for development and operations
CloudWatch Omni delivers observability through two complementary surfaces. Developers get a native extension inside VS Code and Kiro (the currently supported IDEs), where traces appear as you run your agent with a playground and evaluators a click away. Operators get a standalone web experience, separate from the AWS Management Console to monitor the fleet, accessible through SSO with no AWS console needed. Both share the same data: the trace a developer debugs is the trace an operator investigates.

The Cloud Login feature connects your local IDE environment to your AWS account, enabling you to send telemetry data to Amazon CloudWatch for persistent storage, share traces with your team, and access production dashboards. This connection is optional. You can use CloudWatch Omni entirely locally during development, then connect to the cloud when you are ready to monitor agents in production.

Getting started
CloudWatch Omni offers two ways to get started: through the IDE extension (for VS Code and Kiro) or directly through the cloud experience, where you can start sending telemetry data to CloudWatch without installing any IDE extension. In this walkthrough, I install the extension, create an agent, run it, and explore the traces and evaluation tools from my IDE.

After installing the CloudWatch Omni extension from the VS Code Marketplace, the CloudWatch Omni icon appears in the Activity Bar. From the welcome screen, I selected Get started with Sample Project to load a pre-configured agent with sample trace data or use shortcut to Command Palette using Command + Shift + P (on macOS) or Ctrl + Shift + P (on Windows/Linux) and select Omni: Create a new Project

Figure 1. CloudWatch Omni welcome screen & create new project in VS Code

The sample project comes with an agent implementation and example datasets. Part of the getting-started experience is adding OpenTelemetry instrumentation, and CloudWatch Omni guides you through each step. You can also create a new agent from scratch. CloudWatch Omni walks you through the process using an interactive chat where you define the agent’s purpose, select a model provider, and configure tools. All data is stored locally by default. You can optionally connect to AWS to send data to Amazon CloudWatch.

After verifying the configuration, I started the local dev server and sent a question to the agent. What makes this different from a typical chatbot interface is what happens next: selecting View Trace shows exactly how the agent processed the request.

Figure 2. CloudWatch Omni guides your AI code assistant to configure the local development environment for testing

CloudWatch Omni integrates with AI code assistants such as Kiro, Claude Code, and Codex to streamline the setup process. These assistants can configure the Dev Server, install dependencies, and set up instrumentation on your behalf, so you can go from installation to running your first traced agent session in minutes without manual configuration.

Figure 3. Interacting with the agent and viewing traces

Traces are essential for understanding AI agent behavior. Unlike traditional request-response systems, agents make multiple decisions per invocation: choosing tools, composing prompts, and chaining sub-calls. Without full trace visibility, diagnosing why an agent produced an incorrect answer or took an unexpected path becomes guesswork. CloudWatch Omni records every step in a structured timeline so you can pinpoint exactly where behavior diverged.

The Trace Explorer shows a detailed breakdown of every step the agent took (LLM calls, tool invocations, and reasoning steps) in a structured, hierarchical timeline. I could drill into any span to inspect inputs, outputs, token usage, and latency.

Figure 4. Trace Explorer showing the agent’s execution timeline

The Trace Explorer also supports Compare mode, which places two traces side by side to see how different prompts or configurations affect behavior. Compare mode is especially helpful when debugging regressions. And with Ask Assistant, an AI agent analyzes your traces to surface patterns and anomalies, answering questions like “Why did the agent call this tool twice?”

Figure 5. Comparing two traces side by side

Evaluation is what turns observability into actionable quality improvement for generative AI. Traditional metrics like latency and error rate cannot tell you whether an agent’s response was helpful, coherent, or factually correct. Evaluators score each response against quality dimensions, letting you measure what users actually experience and catch regressions that standard monitoring misses entirely.

CloudWatch Omni includes 17 built-in evaluators for metrics like coherence, helpfulness, faithfulness, and routing correctness. I selected traces from the Trace Explorer, chose evaluators, and ran an evaluation, getting per-example scores and aggregate metrics without building any custom evaluation framework.

Figure 6. Running evaluations on traces

From there, I used the Playground to test different system prompts side by side, comparing multiple model and prompt configurations in real time to see how each variation affects output quality before committing changes. With the Experiments view, I could run the same dataset against two agent variants and compare their evaluation scores, latency, and token usage side by side to pick the best-performing configuration.

Figure 7. Comparing evaluations across agent variants in the Omni Experiments console

With Prompt Management, you can version and track prompt configurations over time, making it easy to roll back when a new version underperforms.

CloudWatch Omni also provides a Session Explorer to review full conversation histories and understand how agents handle multi-turn interactions, along with an Agent Topology view that visualizes the architecture of your agent system, including sub-agents, tools, and their interconnections. You can drill into any node to inspect performance and identify bottlenecks.

CloudWatch Omni also offers a dedicated web experience accessible from any browser without an IDE. Teams can access all capabilities collaboratively, including application monitoring, analytics, agent observability, and AI-powered investigations.

Figure 8. CloudWatch Omni web experience with application monitoring, analytics, and agent observability

I curated traces into golden datasets for structured experimentation. The Experiment function runs the agent against a dataset and automatically scores results, creating benchmarks for regression testing whenever prompts or agent logic change.

If you already have an agent built with a supported framework, CloudWatch Omni provides two paths to add instrumentation: Auto-instrument with Kiro, which detects your framework and configures tracing automatically, or manual instrumentation with ready-to-use code snippets for Python and TypeScript. For detailed instrumentation guides, see the CloudWatch Omni documentation.

Supported frameworks and open standards
The walkthrough above uses the sample project, but CloudWatch Omni works with the agent frameworks teams are already using: LangChain, LangGraph, CrewAI, OpenAI SDK, Strands, Vercel AI SDK, and more, in both Python and TypeScript. It also provides native observability for agents built with Amazon Bedrock AgentCore, and uses AgentCore’s evaluation capabilities to assess agent quality directly within the Omni workflow.

Instrumentation uses open standards (OpenInference and ADOT), whether your agents run on Lambda, ECS, EKS, or other clouds. For evaluation, Omni integrates with third-party evaluators including AutoEval and DeepEval alongside built-in datasets, a playground, and batch experiments. No re-platforming required.

CloudWatch Omni brings agent observability and application observability together in a single experience. For the application observability experience, read the companion post Introducing Amazon CloudWatch Omni: collaborative AI-powered observability for your applications.

Pricing and availability
Amazon CloudWatch Omni is now generally available. The IDE extension is free to use. You don’t need an AWS account to get started. You only need AWS credentials for Amazon Bedrock models, or API keys for other providers like OpenAI or Anthropic. Get started today by installing the extension from the VS Code Marketplace.

To explore all capabilities and get started quickly, visit CloudWatch on AWS Builder Center.

If you want to call APIs, search documentation, find regional availability, and check troubleshooting about this feature, try using the AWS MCP Server and plugins with your preferred AI tool. Share your feedback on AWS re:Post or reach out through your usual AWS Support contacts.

Happy building!

— Daniel Abib

The post Introducing Amazon CloudWatch Omni: AI-powered observability for generative AI and agentic workloads appeared first on The NOKIA Blog.

There’s a particular energy to mid-September in New York. Pumpkin spice lattes are flowing, temperatures are dropping, and it’s nearly sweater weather. The city is back at full speed, and so is the AWS launch calendar. This week that energy showed up in a new frontier model on Amazon Bedrock, a desktop app for Amazon Quick, and a reminder that the developers seeing the biggest gains from AI agents aren’t just using better tools — they’re working differently.

Let’s dive in.

Headlines
OpenAI GPT-6 Astra is now generally available on Amazon Bedrock – GPT-6 Astra is OpenAI’s latest and most capable model to date, and you can now run it on Amazon Bedrock. It brings deeper reasoning and judgment, professional-quality writing and design, and advanced computer and browser use to demanding business workflows. The model supports a context window of up to 1 million input tokens, so you can send it large codebases, long contracts, or extensive document collections and ask it to reconcile competing inputs.

You can call GPT-6 Astra through supported Amazon Bedrock APIs, or configure ChatGPT Work and Codex to use the model on Amazon Bedrock. Alongside the launch, OpenAI is introducing new enterprise plugins for ChatGPT Work that extend Astra’s browser-use capabilities across common business applications. Established AWS controls help you secure workloads, govern access, and audit model invocation activity, and your inference data isn’t used for model training. Read more

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

• Amazon Quick desktop app is now generally available on macOS and Windows – The Amazon Quick desktop app brings Amazon Quick to your computer, where it can work with local files and stay connected to your calendar, email, and business apps in the background. Conversations, context, and agents stay synchronized across desktop and mobile, so work you start on one surface carries over to the other. With this release, Quick agents also keep running after you close your computer, which means you can start a long-running task before you leave the office, add input from the mobile app on the way home, and review the result when you get there. Existing Quick users can download the desktop app, and the mobile app is available from the Apple App Store and Google Play. Read more
• AWS Lambda now supports a 90-minute function timeout on Lambda Managed Instances – You can now configure a function timeout of up to 90 minutes for asynchronous and event source mapping (ESM) invocations on Lambda Managed Instances, a 6x increase from the previous 15-minute limit. That opens the door to data processing, media transcoding, financial calculations, AI inference, and batch jobs that need longer continuous execution, without splitting the work across multiple functions. Synchronous invocations keep the existing 15-minute maximum. The longer timeout also applies to steps inside Lambda durable functions, which can still run for up to a year when invoked asynchronously. Read more
• Amazon EBS Volume Clones now copies volumes across accounts – Amazon Elastic Block Store (Amazon EBS) Volume Clones can now copy a volume into another AWS account and re-encrypt it with an AWS Key Management Service (AWS KMS) key in the target account. If you keep production and development in separate accounts, you can share a volume with AWS Resource Access Manager (AWS RAM) and let the target account create a fresh copy in the same Availability Zone, for example, cloning a production database volume into an isolated development account. Cross-account copy works for all volume types, including unencrypted volumes and volumes encrypted with customer managed keys. Read more
• Second-generation single-rack AWS Outposts is now generally available – The new single-rack AWS Outposts is a self-contained 42U rack that puts compute, storage, and networking into one compact unit for locations that need low latency, local data processing, or data residency, and don’t have room for a larger footprint. A single rack delivers up to 2,688 vCPU and 100 TB of Amazon EBS storage, and supports the latest x86-powered Amazon EC2 instances, including general purpose (M7i, M8i), compute-optimized (C7i, C8i), memory-optimized (R7i, R8i), and Outposts accelerated networking instances. You get the same APIs, console, automation, governance, and security controls as multi-rack Outposts and AWS Regions. Read more
• Amazon OpenSearch Serverless is now available on v0 by Vercel – You can now describe a search or AI application in natural language inside v0 by Vercel and get a full-stack app backed by Amazon OpenSearch Serverless. v0 provisions a collection, indexes your data, and uses the OpenSearch Serverless endpoint for full-text search and vector search for retrieval-augmented generation (RAG) workloads, without leaving the v0 interface. OpenSearch Serverless scales capacity up and down for you, so you can focus on the application instead of cluster management. You can provision under a new AWS account or link an existing one. Read more
• AWS Transform for .NET modernization is now generally available via CLI – You can trigger an AWS-managed .NET modernization in AWS Transform custom with a single CLI command, then run it interactively or script it into an existing pipeline. The CLI sits alongside the existing AWS Transform for .NET experiences in the web application, Visual Studio IDE, Kiro Power, and MCP agents. Use it to upgrade language versions, migrate frameworks, optimize performance, and analyze codebases with transformations you can run as-is or customize. The .NET modernization transformation includes 50,000 free agent minutes per month. Read more

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:

• Clare Liguori on frontier engineering – If you already use an AI coding assistant but don’t feel like you’re shipping much faster, start here. Clare Liguori, Senior Principal Engineer at AWS, published a practitioner’s manifesto on frontier engineering: ten principles, drawn from teams across Amazon, for changing how you build software with AI agents. The argument is direct. Software development has split in two, people who changed how they work with agents, and people who only changed their coding tools. Frontier engineering is not vibe coding. You spend the first weeks writing steering files, refactoring the codebase, and learning to decompose work for agents. Those weeks feel slower. The weeks after feel dramatically faster, because you’re no longer building the software directly — you’re building the agent setup that builds the software.
• A free year of Kiro for students around the world – The Kiro Students program is expanding from 11 universities to 121 new schools across 16 countries. Eligible students get one year of Kiro with 1,000 credits per month and full access to paid features such as premium models and Kiro Web, no credit card and no trial timer. You can work in the IDE, the CLI, Kiro Web in a browser, or Kiro Crew. If you’re a student, sign up with your university email.
• The state of AI for security: measuring what matters for trust – Security teams are using AI for triage, threat modeling, incident response, and code review, but a tool that flags everything doesn’t save time. In The state of AI for security, Anshumali Shrivastava and Neha Rungta introduce Deception Benchmark, a new evaluation that tests whether a model can tell a real vulnerability from code that looks risky but is actually safe. The benchmark includes 14,822 samples across 16 languages and more than 70 Common Weakness Enumeration (CWE) categories. Under standard prompting, precision landed in the mid-50s, about as likely to be inaccurate as accurate, and none of the 12 models tested kept both false positives and false negatives below 10 percent. The post links to the dataset, whitepaper, and submission workflow for verified scoring.
• Build full-stack AWS applications in minutes with AI-powered scaffolding – Version 1.0 of the Nx Plugin for AWS is an open source toolkit of deterministic generators for APIs, websites, databases, and AI agents, plus the AWS infrastructure to run them. Each generator writes working, deployable code with security, observability, and type-safety already in place, so an AI assistant can assemble the foundation and spend its effort on your application logic. Bingo Industries used it to take a multi-agent operations chatbot from idea to production in less than 3 weeks. The plugin is open source on GitHub. Create a workspace with pnpm create @aws/nx-workspace and point your coding agent at the included MCP server.
• The oldest architecture in computing – On All Things Distributed, Werner Vogels starts from a question customers always ask “Will AI take my job?”, and lands on memory. After spending time with Kiro Crew, he traces a line from Jeff Hawkins’ A Thousand Brains to how Crew stores, consolidates, and forgets across markdown files, a vector database, and a key-value index. His conclusion: the brain is the oldest architecture in computing, and the people who think hardest about how it works will build the next tools. Now, go build.

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

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

Join the AWS Builder Center to connect with builders, share solutions, and access content that supports your development. Browse here for upcoming AWS-led in-person and virtual events and developer-focused events.

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

— Micah

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

The post AWS Weekly Roundup: OpenAI GPT-6 Astra on Amazon Bedrock, Amazon Quick desktop GA, Kiro for students, and more (September 14, 2026) appeared first on The NOKIA Blog.

The news that interested me the most last week was the DuckLabs acquisition. AWS has signed a definitive agreement to acquire DuckLabs, the Amsterdam-based company behind DuckDB, the popular open source analytical database that runs in-process and executes SQL directly against files like Parquet, CSV, and JSON. DuckDB stays open source under its independent foundation and the MIT license, and over time AWS plans to combine its speed at everyday queries with the enterprise scale of services like Amazon S3, Amazon Redshift, and Amazon Athena.

Co-founded by Hannes Mühleisen and Mark Raasveldt, DuckDB runs locally or on Amazon S3, which makes it remarkably fast for the everyday queries (a terabyte or less) that make up the bulk of real-world analytics. It also happens to pair beautifully with AI agents, which “poke” and experiment their way through data much like humans do. The co-founders will continue leading its technical direction while AWS combines DuckDB’s speed with analytics services like Amazon EMR, AWS Glue, and Amazon SageMaker. For the bigger picture on why this matters, Andy Warfield, Vice President and Distinguished Engineer shared his thoughts on the post DuckDB and the changing physics of analytics on All Things Distributed.

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

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

• Amazon ECS now automatically detects and recovers container instances that lose agent connectivity – Amazon ECS now continuously monitors agent connectivity to the control plane and surfaces a new AGENT_CONNECTIVITY health event across AWS Fargate, Amazon ECS Managed Instances, and Amazon ECS on EC2. On Fargate and Managed Instances, ECS handles recovery automatically, draining tasks, launching replacements, and deregistering the impaired instance. On EC2, you can wire the event into your own workflow. Available at no additional cost in all AWS Commercial and AWS GovCloud (US) Regions.
• AWS Lambda introduces public preview runtimes, starting with Node.js 26 and Python 3.15 – You can now test upcoming Lambda runtimes before they reach general availability. Preview runtimes use the same identifier as the eventual GA version, so your functions graduate automatically with no action required. Third-party tools and deployment frameworks can also validate compatibility ahead of GA. Not meant for production yet (breaking changes are possible), but a great way to get ahead of your next upgrade. Available in all AWS commercial, AWS GovCloud (US), and China Regions.
• AWS IoT Core adds a native InfluxDB rule action – You can now route time-series data from your IoT devices straight into InfluxDB (Amazon Timestream-managed or self-hosted) without writing custom code or standing up an intermediate service. IoT Core formats data into InfluxDB’s line protocol and supports device-side and server-side batching. Available in all AWS Regions where Amazon Timestream for InfluxDB is offered.
• Amazon GameLift Servers now includes enhanced DDoS protection – Your game servers now get automatic protection against network and transport layer (layers 3 and 4) DDoS attacks – UDP reflection, SYN floods, and similar vectors – with nothing to enable or opt into. Built on top of AWS Shield Standard with gaming-optimized traffic shaping, it turns on the moment your servers start running (Server SDK 5) at no extra cost. It’s available in all supported GameLift Servers Regions except China (Beijing) and China (Ningxia).
• Amazon SageMaker HyperPod expands support for Ray – You can now run Ray workloads on SageMaker HyperPod with built-in observability, resilient training, and accelerated inference. Create and manage Ray clusters from Amazon SageMaker Studio, attach JupyterLab or your local IDE so a multi-node cluster behaves like a local dev environment, and get auto-provisioned Grafana dashboards. Node auto recovery, hung job detection, and tiered checkpointing keep large training runs healthy, while Ray Serve adds a tiered KV cache for inference. Your existing open source Ray code runs unchanged. Available for HyperPod clusters orchestrated by Amazon EKS.

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:

• Happy 20th birthday, Amazon EC2! – Amazon EC2 turns 20. Channy Yun looks back at how EC2 grew from a single m1.small instance type in one Region to more than 1,200 instance types across 39 Regions, along with the custom silicon journey from the first Graviton to Graviton5 and Trainium3. A fun and worthwhile read on the service that still underpins so much of AWS – including Amazon ECS, Amazon EKS, AWS Lambda, Amazon SageMaker, and Amazon Bedrock.
• Agentic Resource Discovery (ARD): an open specification for agent discovery – As organizations scale up agents, tools, and MCP servers, those resources end up scattered across clouds, on-premises infrastructure, and SaaS platforms – each with its own registry and metadata. ARD is a new open specification (Apache 2.0) that defines a common way to describe and discover agentic resources, so publishers “describe once” and consumers “discover everywhere” – think DNS, but for agents. AWS contributed feedback but doesn’t own the spec, and it complements the AWS Agent Registry by letting you federate across catalogs without migrating.
• Get started with the Agent Toolkit for AWS in the AWS CLI – A single AWS CLI command (aws configure agent-toolkit) now equips AI coding agents like Kiro, Claude Code, Codex, and Cursor with curated, up-to-date AWS knowledge and a secure connection to thousands of AWS APIs through the AWS MCP Server. If you build with an AI coding assistant, this helps it choose the right services, use modern APIs, and follow security best practices – so it gets AWS code right more often the first time.

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

• AWS Summits – Free in-person events where builders come together to learn, connect, and explore the latest in cloud and AI. Upcoming stops include Zurich (September 2), São Paulo (September 3), Tel Aviv (September 10), and Dubai (September 30). Can’t attend in person? You can stream sessions through the Global Livestream and On-Demand Hub. I’ll be presenting two sessions on generative AI and Amazon Bedrock at the São Paulo Summit – if you’re there, come say hello.
• AWS Community Days – Community-led conferences where content is planned, sourced, and delivered by community leaders. Upcoming events include JAWS SONIC 2026 in Tokyo (September 5) and Warsaw, Poland (September 8).

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: Welcome DuckLabs to the team, Agentic Resource Discovery (ARD), and more (August 31, 2026) appeared first on The NOKIA Blog.

Last week, we brought together AWS Heroes from around the world to connect, collaborate, and celebrate the builders who go above and beyond for the AWS community.

The AWS Heroes Summit, an invite-only annual gathering, brings global experts specializing in fields like AI, serverless, and containers together for direct collaboration, technical deep-dives, and feedback sessions with internal AWS product and service teams.

Day 1 started with an inspiring fireside chat from AWS CEO Matt Garman. From an insightful AMA with James Hamilton on Day 2 to breakout sessions from various product teams that sparked new ideas, our AWS Heroes excelled at sharing knowledge, lifting each other up, and turning conversations into collaborations. To learn more, read the attendee feedback on LinkedIn.

Last week’s launches
Here are some launches that got my attention:

• Web Search on Amazon Bedrock: Amazon Bedrock now enables OpenAI models (GPT-5.4, GPT-5.5, and GPT-5.6 Sol/Terra/Luna) to browse and retrieve information from the internet, allowing AI applications to access up-to-date information beyond their training data. This capability opens new possibilities for building AI agents and applications that can answer questions using real-time web content while maintaining data residency within your secured AWS environment with zero data egress. To get started, visit the AI blog post and the Amazon Bedrock User Guide.
• Runtime Instances on Amazon Bedrock AgentCore: You can now deploy and run AI agents on dedicated runtime instances through Amazon Bedrock AgentCore, providing more control over agent execution environments with predictable performance and cost. To get started, visit Sébastien’s blog post and AgentCore documentation.
• Vector search for Amazon DynamoDB: You can store and query vector embeddings alongside your existing data in DynamoDB without managing a separate vector database. DynamoDB already supports storing memory for AI agents, and with vector search you can now add semantic retrieval over that memory for agentic grounding, with predictable performance. To learn more, visit Esra’s blog post and Amazon DynamoDB Developer Guide.
• AWS Transform continuous modernization now generally available: This capability helps engineering teams analyze and remediate technical debt across source code repositories at scale. You can modernize mainframe and legacy workloads with an ongoing, automated approach rather than a one-time migration event. To learn more, visit Micah’s preview blog post. You can also try the AWS Transform Kiro Power and agent plugins.
• Up to 3,000 Mbps for AWS Lambda function bandwidth: AWS Lambda functions now support increased network bandwidth, enabling data-intensive workloads and faster communication between Lambda functions and other AWS services. This feature enables functions outside a VPC that are configured with 2 GB of memory or more to access network bandwidth that scales proportionally, from 625 Mbps at 2 GB up to 3,000 Mbps at 10 GB.

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

Other AWS news
Here are some additional projects and news items that you may find interesting:

• Introducing Dogwood: Runtime Verification for AI Agents: AWS open-sourced Dogwood, a purpose-built governance language for AI agents to support Cedar policies and add temporal conditions. Powering Dogwood, Amazon Bedrock AgentCore introduced temporal policies whose decisions depend on the history of an agent’s actions within a session, not on the current request alone.
• AWS supports Agent Plugins: An Open Standard for Portable Agent Extensions: AWS announced support for Agent Plugins, an open source, vendor-neutral specification that gives AI agent extensions a common packaging format so you can package an extension once and ship it to any client, including Kiro, VS Code, Cursor, or any tool that implements the spec.
• Introducing Kiro Crew: Kiro Crew is a persistent, self-evolving workspace that keeps work moving, online or off, enabling collaborative multi-agent development workflows within the Kiro IDE. It’s built for engineering work that goes beyond a single chat session, and spans repos, tools, and days. You can run several efforts in parallel or hand work to subagents that report back, so nothing waits in line.

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 and AWS Community Days. Join the AWS Builder Center to connect with builders, share solutions, and access content that supports your development.

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

— Channy

The post AWS Weekly Roundup: AWS Heroes Summit, Web Search on Amazon Bedrock, Dogwood, Kiro Crew, and more (August 10, 2026) appeared first on The NOKIA Blog.

Last week, my team visited Seoul to meet AWS Korea User Group (AWSKRUG) leaders. AWSKRUG is the largest cloud developer community in Korea, with 20 meetup groups organized by topic and area that collectively host over 100 events each year, primarily in Seoul.

My team regularly visits countries across the Asia-Pacific region, listens to feedback from user group leaders, and works to support their communities. At this meeting, leaders honestly shared what they did well in the first half of the year, what needs improvement, and what they asked of AWS Developer Experience team. We also enjoyed a pleasant conversation during our Chimaek time together.

Now, let’s take a closer look at key launches of last week.

A one-click Lambda setup prompt for coding agents caught my eye most last week. This prompt configures your agent with AWS Serverless skills and the Serverless Model Context Protocol (MCP) server, embedding serverless best practices from the start. This prompt references the Lambda agent setup guide, which includes installation commands for Claude Code, Kiro, Cursor, GitHub Copilot, Codex, Devin Desktop, and OpenCode.

To get started, choose the Copy agent prompt button on the Lambda console screen or copy fetch https://docs.aws.amazon.com/lambda/latest/dg/samples/aws-lambda-agent-setup.md directly, and paste this URL in your preferred AI agent.

You can also use Agent Toolkit for AWS to give your coding agent current AWS knowledge and safe resource access. Use fetch https://raw.githubusercontent.com/aws/agent-toolkit-for-aws/refs/heads/main/setup-instructions/setup.md for installing AWS MCP Server.

Last week’s launches

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

• OpenAI GPT-5.6 Sol, Terra, and Luna on Amazon Bedrock: You can use the smartest family of models from OpenAI yet on Bedrock’s next-generation inference engine built for high performance, security, and reliability. The three models span capability tiers from flagship reasoning (Sol) to balanced performance (Terra) to fast, cost-efficient inference (Luna), all accessible through the Responses API on Amazon Bedrock.
• Same-day transitions to Amazon S3 Standard-IA and S3 One Zone-IA: You can now transition objects to S3 Standard-Infrequent Access (S3 Standard-IA) and S3 One Zone-Infrequent Access (S3 One Zone-IA) as soon as the day they are created, without the previous 30-day minimum retention period in S3 Standard. These storage classes offer up to 40% lower storage costs than S3 Standard while still providing millisecond access when needed, making them ideal for backups, log analytics, and compliance workloads where data becomes cold within hours or days.
• Self-managed code storage on AWS Lambda: With self-managed Amazon S3 buckets for code storage, you can reference source code directly from your own S3 buckets without Lambda creating intermediate copies. This eliminates code storage limits and reduces function activation time after function creates and updates by removing the copy step.
• Importing users with password hashes on Amazon Cognito: You can now import users with password hashes in CSV user imports. Previously, imported users had to reset their passwords on first sign-in. Now, you can include password hashes in the CSV import, enabling users to sign in immediately with their existing credentials. When creating a CSV import, you specify the password hashing algorithm used by your source system.

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:

• Amazon SQS turns 20: Two decades of reliable messaging at scale: When Amazon SQS launched publicly in July 2006, it made this pattern available to every AWS customer. Twenty years later, that core function, decoupling producers from consumers, remains the reason customers use SQS. Let’s look back important milestones after Jeff’s 15th anniversary post.
• Open Protocols with the Strands Agents SDK: Learn how open AI protocols such as MCP, A2A, UTCP, AG-UI, and x402 work together using Strands Agents SDK for building AI agents as an example implementation, though the patterns apply to any agent framework.
• Open source Bulk Executor for Amazon DynamoDB: Performing bulk operations against all items in a DynamoDB table has historically required custom coding. The Bulk Executor for DynamoDB simplifies bulk tasks like these. You can use this feature to invoke commands like count, find, delete, or update. No coding is required, even when running at large scale.
• Transform AWS Support Case Workflows with Kiro CLI: Explore how Kiro CLI’s MCP integration accelerates support case workflows by combining investigation, documentation lookup, and case creation into a single conversational interface across three real-world scenarios: AWS Glue job failures, AWS Lambda cold start investigation, and AWS WAF false positive analysis.

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.

Finally, some customers experienced an issue with Cost Explorer displaying inaccurate estimated billing data in last weekend. They may have received erroneous budget and cost anomaly detection alerts, and observed inflated estimated cost and usage data. The issue has been resolved, and all AWS services are operating normally. We apologize for the concern this incident caused our customers and are conducting a thorough retrospective to prevent events like this from reoccurring, as well as improving our response when billing incidents occur. For more information, visit the AWS Health Dashboard.

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

— Channy

The post AWS Weekly Roundup: One-click Lambda setup prompt, OpenAI GPT-5.6 models on Bedrock, and more (July 20, 2026) appeared first on The NOKIA Blog.

AWS Builder Center turned one year old last week. Launched on July 9, 2025, the platform has grown from a community hub with Wishlist voting, community profiles, and a toolbox into a full ecosystem with sandbox environments, workshops, Spaces, and a Builders’ Library. To mark the anniversary, Rick Suttles published a full feature timeline covering everything shipped over the past year: AWS Capabilities by Region (1,500+ services across 37 Regions), Spaces for community-created groups, workshops with category and complexity filters, badges and streaks, article series, view counts, saved items, student status, availability notifications, sign-in with GitHub and Amazon, and sandbox environments.

Jeff Barr published a retrospective summarizing Builder Center’s first year. Since launch, 5,548 authors have published 6,448 articles with more than 10.4 million page views combined. Builders have earned 99,226 badges since the badge system launched in March 2026. Community members have submitted 565 wishes, 10 of which have shipped with another 20 on the near-term roadmap.

The top community article Building an AWS Study Buddy with MCP + Strands Agents SDK by Dineshraj Dhanapathy reached 50,000+ views. Chris Miller’s Migrating an EOL Linux Server to AWS in 8 Hours with Kiro followed at 45,000+, and Yash Aggarwal’s AIdeas: NeuroVoice – Multimodal AI for Early Screening of Neurological Diseases article reached 38,000+.

The week’s headline addition is Sandbox Environments by Rick Suttles. Sandboxes give you a free, pre-provisioned AWS account to complete a workshop exercise. Each environment is active for 8 hours, after which the account and all its resources are automatically de-provisioned. You can have one active sandbox at a time and request one per week. No personal AWS account, credit card, or manual cleanup required.

Last week’s launches

Here’s what else happened this week.

• AWS Security Hub introduces Network Scanning – Security Hub introduced Network Scanning, a capability that identifies resources in your environment that are reachable from the public internet. Network Scanning probes your resources from the internet to detect actual reachability, complementing the existing network reachability findings in Security Hub that identify configurations that could make a resource reachable. It discovers public IP addresses, virtual machines, and load balancers across your AWS and Azure environments, identifies reachable ports, and determines what services are running behind them. Each reachable port generates a Security Hub finding with evidence of the port and service discovered. Security Hub Exposures then automatically correlates these findings with other findings and resource configurations to determine broader risk. Existing customers can enable Network Scanning in individual accounts and Regions, or across an organization through a configuration policy. For new customers, Network Scanning is on by default. It is included with Security Hub Essentials at no additional cost.
• Security Hub also extends unified security management to Microsoft Azure – Security Hub now monitors Microsoft Azure resources, providing unified posture management, vulnerability management, and security response across both clouds. It automatically discovers Azure VMs, container images, Function Apps, and identities, and evaluates them for misconfigurations, internet exposure, and software vulnerabilities. AWS and Azure findings appear in the same prioritized view with the same formats and automation workflows.
• Amazon SageMaker Studio integrates with Hugging Face for one-click model deployment and customization – You can now go from discovering a model on Hugging Face to working with it in SageMaker Studio in a single click. Select any supported model on Hugging Face and choose “Customize on SageMaker AI” or “Deploy on SageMaker AI” to land directly on the corresponding workflow page with the model pre-loaded. New customers receive a Studio environment created in seconds with pre-configured permissions for serverless model customization (including fine-tuning with custom reward functions for reinforcement learning), model evaluation, and deployment to SageMaker or Bedrock endpoints. Verified customers receive default GPU access to G5, G6, and G4dn instances without requesting quota increases, and quota utilization is visible directly inside the Studio environment.
• Amazon EKS Auto Mode and Amazon ECS Managed Instances reduce GPU management fees by up to 60% – Beginning July 1, 2026, EKS Auto Mode and ECS Managed Instances reduce management fees for accelerated instance types: G-series fees are down 35%, and P-series and AWS Trainium fees are down 60%. The reductions apply automatically to existing clusters and require no action from customers. Both services include capabilities built for accelerated workloads. EKS Auto Mode provides automatic parallel image pulling on GPU instances with local NVMe storage and accelerator-aware node repair. ECS Managed Instances provides GPU metrics through Amazon CloudWatch Container Insights and automatic health monitoring for GPU hardware failures.
• Amazon Aurora DSQL change data capture (CDC) is now generally available – Aurora DSQL CDC streams the results of insert, update, and delete operations as change events to Amazon Kinesis Data Streams. You can use it to synchronize data across microservices, trigger Lambda functions, or deliver changes to S3, Redshift, and OpenSearch Service through Amazon Data Firehose. CDC streaming is designed to have zero impact on database workload performance and requires no infrastructure to manage.

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

Other AWS news

Here are some additional posts you may find useful:

• Building secure AI agents at scale: Introducing Loom for AWS – Loom is an open-source enterprise platform for building agents with AWS Strands Agents and deploying them on Amazon Bedrock AgentCore Runtime. It provides a unified management UI and backend API with identity provider integration, scope-based authorization, multi-persona navigation, and full lifecycle management for agents, memory, MCP servers, and agent-to-agent integrations. Loom enforces automated resource tagging for cost attribution, implements RBAC and ABAC for multi-tenant security, uses paved-path blueprints for agent deployments, manages identity propagation through delegated actor chains, integrates with AWS Agent Registry for discovery and governance, and supports human-in-the-loop review before sensitive actions. The project is available in AWS Labs on GitHub.
• Introducing Claude apps gateway for AWS – The Claude apps gateway is a self-hosted control plane that gives organizations centralized control over access, cost, and policy for Claude Code and Claude Desktop. It connects to any OIDC-compliant identity provider, enforces managed settings on every request, routes inference to Amazon Bedrock or Claude Platform on AWS, and supports per-user and per-group spend caps. The gateway runs as a stateless container in your private network, backed by a PostgreSQL database for short-lived sign-in state. No long-lived secrets are stored on developer machines. Deploy it through Amazon Bedrock to keep data within the AWS security boundary, or through Claude Platform on AWS for the native Claude platform experience.
• Introducing OAuth support for AWS MCP Server – You can now connect agents to the AWS MCP Server using browser-based OAuth with the same credentials you use for the AWS Console or CLI. The new sign-in path supports IAM federation, AWS IAM Identity Center, and root or IAM users. AWS Sign-In issues short-lived access tokens and refresh tokens, with automatic token management so developers stay authenticated across restarts. For headless use cases, a non-interactive flow lets applications with existing AWS credentials obtain OAuth access tokens through the create-oauth2-token-with-iam API. New governance controls include OAuth-specific IAM condition keys, token introspection and revocation, dynamic client registration, and CloudTrail audit elements.

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

Upcoming AWS events

Check your calendar and sign up for upcoming AWS events:

• AWS Summits – Free in-person events for builders and innovators to learn, think big, and make new connections. Coming up: Taipei (July 15), Bogotá (July 30), Jakarta (August 6), Ciudad de México (August 12), Johannesburg (August 19), and Zurich (September 2).
• AWS Community Days – Community-led conferences planned and delivered by community leaders. Upcoming events include Yaoundé, Cameroon (July 25), Ahmedabad, India (July 25), Belo Horizonte, Brazil (August 22), Ottawa, Canada (August 22), Tulsa, USA (August 22), and Toronto, Canada (August 29).

Visit the AWS Builder Center to meet other builders, contribute solutions, and find resources that help you keep building.

Wishing everyone a restful and enjoyable summer. Whether you’re building, learning, or recharging, I hope you find time for all three. I’ll be heading to Scandinavia for a few weeks to trade the heat for some cooler weather and longer evenings. Come back next week for more news!

— Esra

The post AWS Weekly Roundup: AWS Builder Center at 1 year, Network Scanning in Security Hub, Loom for AWS, and more (July 13, 2026) appeared first on The NOKIA Blog.

Today, we’re announcing AWS CloudFormation Express mode, a new deployment mode that accelerates deployments for developers and AI tools iterating on infrastructure. Express mode accelerates deployments by completing when CloudFormation confirms resource configuration is applied, rather than waiting for extended stabilization checks. This reduces deployment time by up to 4 times for iterative development workflows and production scenarios.

How it works

Every CloudFormation deployment performs stabilization checks after resource configuration is applied. These checks serve an important purpose when you need to confirm resources can serve traffic before shifting load.

However, many workflows do not require full stabilization to proceed. Express mode benefits two primary use cases: iterative development workflows and production scenarios where you are comfortable with eventual stabilization. These use cases include iterating on infrastructure configurations during development, testing individual components of your application, and AI-assisted infrastructure development that benefits from sub-minute feedback loops.

With Express mode, CloudFormation completes deployments when resource configuration is applied, without waiting for stabilization checks. Resources continue becoming operational in the background. CloudFormation automatically retries dependent resources that encounter transient failures during provisioning within the same stack, without requiring any customer intervention. This built-in resilience handles timing issues between resources as they stabilize. Express mode changes when the deployment completes, not how resources are provisioned.

For example, when I create an Amazon Simple Queue Service (SQS) queue with a dead letter queue (DLQ), Standard mode takes 64 seconds, but Express mode completes in up to 10 seconds. In the case of deleting an AWS Lambda function with network interface attachment, Standard mode takes 20–30 minutes, but Express mode completes in up to 10 seconds based on my benchmarking test.

Get started with CloudFormation Express mode

When you create a CloudFormation stack in the AWS Management Console, choose Enable in the Express mode under Stack deployment options.

You can also use AWS Command Line Interface (AWS CLI), AWS SDKs, or IaC tools like AWS Cloud Development Kit (CDK), and AI tools such as Kiro.

Activate Express mode by setting the --deployment-config parameter to EXPRESS when creating, updating, or deleting stacks. No template changes are required. Express mode disables rollback by default for the fastest iteration experience. To re-enable rollback, set disableRollback to false in the deployment-config for production environments, or implement monitoring/cleanup mechanisms for failed deployments.

aws cloudformation create-stack  
   --stack-name my-app  
   --template-body file://template.yaml  
   --deployment-config '{"mode": "EXPRESS", "disableRollback": true}' 

For example, use the Express mode when you build infrastructure incrementally, adding resources one at a time. Ensure your IAM role templates follow the principle of least privilege.

# Iteration 1: Deploy IAM role
aws cloudformation create-stack 
--stack-name my-microservice 
--template-body file://iteration1-iam.yaml 
--deployment-config '{"mode": "EXPRESS"}' 
--capabilities CAPABILITY_IAM
--role-arn arn:aws:iam::123456789012:role/CloudFormationDeployRole

# Iteration 2: Add Lambda function
aws cloudformation update-stack 
--stack-name my-microservice 
--template-body file://iteration2-lambda.yaml 
--deployment-config '{"mode": "EXPRESS"}' 
--capabilities CAPABILITY_IAM
--role-arn arn:aws:iam::123456789012:role/CloudFormationDeployRole

# Iteration 3: Add SQS queue and event source mapping
aws cloudformation update-stack 
--stack-name my-microservice 
--template-body file://iteration3-sqs.yaml 
--deployment-config '{"mode": "EXPRESS"}' 
--capabilities CAPABILITY_IAM
--role-arn arn:aws:iam::123456789012:role/CloudFormationDeployRole

For AWS CDK, activate Express mode with the cdk deploy --express command when you deploy your CDK stack. This command retrieves your generated CloudFormation template and deploys it through the CloudFormation Express mode, which provisions your resources as part of a CloudFormation stack.

Express mode works with all existing CloudFormation templates and supports all CloudFormation features including change sets and nested stacks. When you enable Express mode on a parent stack, all nested stacks also use Express mode. If you need resources to be fully operational before proceeding with traffic or testing, continue using the default deployment behavior, which performs stabilization checks before completing.

Now available

AWS CloudFormation Express mode is available today in all AWS commercial Regions at no additional cost. For Regional availability and a future roadmap, visit the AWS Capabilities by Region. If you want to call APIs, search documentation, find regional availability, and check troubleshooting about this new feature, try using the AWS MCP Server and plugins with your preferred AI tool. To learn more, visit the CloudFormation documentation.

Start accelerating your deployments today, and send feedback to AWS re:Post for AWS CloudFormation or through your usual AWS Support contacts.

— Channy

The post Accelerate your infrastructure deployments by up to 4x with AWS CloudFormation Express mode appeared first on The NOKIA Blog.

It has been a busy stretch on the AWS Summit circuit. At the New York City Summit, I delivered a workshop called Building AI architectures with AWS Serverless, and it was a lot of fun watching builders wire up agents and serverless services to solve real problems in a single afternoon. This week I am heading down to the Washington, DC Summit, which always puts a spotlight on innovation in the public sector. If you are going to be there, come say hello.

A question I hear a lot at these events is how teams can put AI to work without waiting on a long engineering backlog, and this week’s biggest launch speaks directly to that, with Amazon Connect Customer introducing a no-code way for business teams to design AI powered customer experiences themselves. Now, let’s get into this week’s AWS news.

Headlines


Amazon Connect Customer launched the Agentic CX designer (NLX) in preview, a no-code canvas for designing and deploying AI powered self service experiences. Business teams can build and launch voice and digital experiences that bring agentic and deterministic AI together in one governed flow, going from design to testing and simulation to production ready experiences in weeks rather than months. The launch also includes Live Sync in preview, a patented technology that drives a customer’s web or mobile experience in real time as they speak or type. A caller can complete a form or pull up the right product page without ever leaving the conversation. To see how this reshapes who designs customer experience, read the blog post on how the business user is the new architect of customer experience.

Last week’s launches


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

• AWS Lambda MicroVMs – A new serverless compute primitive that gives each user or job VM level isolation with near instant launch and resume speeds, plus the ability to suspend and resume execution for up to 8 hours. Built on Firecracker, it is made for running user or AI generated code in multi-tenant applications without managing virtualization infrastructure or trading off isolation, speed, and state.
• Amazon EC2 AMI Watermarks – Lets you embed custom identifiers in your private AMIs that automatically carry forward to every derived AMI across copies, Regions, and account shares. You can combine watermarks with Allowed AMIs and Declarative Policies to restrict launches to approved images, available at no additional cost in all AWS Regions.
• AWS Outposts self-service lifecycle management – Adds self service configuration, quoting, ordering, subscription management, renewal, and decommissioning directly from the console, CLI, and API. A new quoting tool generates real time cost estimates in seconds and surfaces account and regional constraints before you submit an order.
• Amazon MSK AI Agent Skills – Gives AI coding assistants like Kiro, Claude Code, and Cursor expert, up-to-date guidance for operating Amazon MSK, covering troubleshooting, sizing, configuring, monitoring, and migrating external Kafka clusters to MSK Express. Tasks that once required specialized knowledge become a guided experience developers can complete on their own.
• Amazon OpenSearch Service AI-assisted migrations – Migration Assistant now includes an agent guided experience that helps you move self managed Apache Solr, Elasticsearch, or OpenSearch deployments to OpenSearch Serverless or Managed Clusters using tools like Kiro and Claude Code, with new live traffic capture and replay support for Solr.
• Amazon GuardDuty AI-powered investigations (preview) – Automatically analyzes findings and accounts to help you separate true threats from benign activity, examining context and related activity from the last 90 days with knowledge graphs and threat intelligence. Each investigation returns a disposition assessment with confidence scoring, MITRE ATT&CK classification, and actionable recommendations in minutes.

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:

• Open Governance for MySQL – Oracle announced a community governance model for MySQL that gives organizations outside Oracle a defined role in the project, including four non Oracle seats on a new Steering Committee and a public GitHub presence. AWS holds a seat and shares why it supports the move and how it already contributes fixes upstream for everyone running MySQL.
• A new way to keep your AWS Certification current -You can now maintain an eligible AWS Certification for an additional year by completing curated training and hands on labs on AWS Skill Builder instead of retaking a full exam. The option is available today in open beta for several Associate and Professional certifications, with more coming later this year.
• The All Builders Welcome Grant insider’s guide for 2026 applicants – A community guide on AWS Builder Center that walks early career builders through applying for the grant, which covers a full conference pass, airfare, and hotel for AWS re:Invent 2026. Applications are open now and close on July 14.

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

Looking for ways to connect with builders in person? Check out the AWS Summits coming to a city near you, find a local AWS Community Day led by user groups around the world, and explore tutorials, community content, and ways to grow your skills over at the AWS Builder Center.

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

-Micah

The post AWS Weekly Roundup: Agentic CX designer for Amazon Connect Customer, EC2 AMI Watermarks, Open Governance for MySQL, and more (June 29, 2026) appeared first on The NOKIA Blog.

Last week AWS Summit New York City brought together thousands of customers, partners, and builders for a free, one-day event showcasing the latest in cloud and AI innovation. Dr. Swami Sivasubramanian, VP of Agentic AI at AWS unveiled a stack of AI launches in his keynote, all built around one thesis: agents that compound value over time.

• Agents for working – You can launch autonomous agents and access a smarter activity feed with new Amazon Quick features, which now let you create and run multi-step agents directly in the desktop app and consolidates email, Slack, calendar, and tasks into a single prioritized view with personalized rules.
• Agents for securing – You can shift from reactive to proactive security with AWS Continuum, a new AI-native security service that reasons, validates, and acts at machine speed across the full code vulnerability lifecycle. AWS Security Agent (now part of AWS Continuum) adds new features: threat modeling; pull request code scanning with remediation across major Git platforms; and IDE integrations via Kiro power, Claude Code plugin, and MCP.
• Agents for building – You can write, ship, and modernize code in one continuous loop with Kiro, AWS DevOps Agent, and AWS Transform. Kiro introduces a native iOS app; AWS DevOps Agent adds release management capabilities to assess code changes before production; and AWS Transform continuous modernization reduces tech debt autonomously.
• Agents customers create – You can go from agent idea to production in minutes with Amazon Bedrock AgentCore, which now includes a GA harness for infrastructure and orchestration, Web Search, Managed Knowledge Base, policy integrations with Guardrails, and the new AWS Context service for mapping organizational data relationships.

To learn more, visit the Summit recap from our top announcements blog post and Amazon News post.

Last week’s launches

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

• AWS Local Zone in Hanoi, Vietnam  —This new Local Zone is one of the first AWS Local Zones in the Asia Pacific with support for Amazon S3 and Amazon EBS Local Snapshots, enabling customers to meet data residency requirements by storing and backing up data locally. To get started, enable the Hanoi Local Zone (ap-southeast-1-han-1a) from the Regions and Zones tab in the AWS Global View or by using the ModifyAvailabilityZoneGroup API.
• AWS Blocks, an open-source TypeScript framework for application developers (preview) — AWS Blocks runs a fully functional local environment with Postgres, authentication, and real-time messaging, no AWS account required. When you’re ready to deploy, the same application code runs on production AWS services with zero changes, and you can drop into AWS CDK at any point for direct resource configuration.
• Grok 4.3 from xAI in Amazon Bedrock —You can use the Grok 4.3 model on Amazon Bedrock, giving you even more choice as you build generative AI applications across reasoning, agentic, and enterprise workflows. Grok 4.3 runs on a new inference engine in Bedrock designed for price performance, with support for tool calling, structured output, and response streaming.
• Amazon S3 annotations: attach rich, queryable context directly to your objects — Amazon S3 now lets you attach up to 1 GB of rich, mutable, and queryable context directly to your objects using annotations, purpose-built for AI agents and autonomous workflows that need to discover, understand, and act on data at scale without maintaining separate metadata systems.
• Amazon ECS announces faster service auto scaling — Amazon ECS service auto scaling now detects and responds to load changes faster with support for high resolution (20-second) metrics and metric publishing optimizations. In AWS benchmarking tests, time to trigger scale-out improved from 363 seconds to 86 seconds (76% faster), and total time to scale and provision new tasks improved from 386 seconds to 109 seconds (72% faster).
• Amazon EC2 G7 instances accelerated by NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs — AWS is the first major cloud provider to support NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs. G7 instances are accelerated by these GPUs with custom sixth-generation Intel Xeon Scalable processors, delivering up to 4.6x AI inference performance and up to 2.1x graphics performance compared to G6 instances.
• Strands Agents introduces new capabilities — Strands is an open source toolkit for building production agents. You can now use better context management in Harness SDK, a new isolated execution environment with Strands Shell, and chaos testing and red teaming in Strands Evals.
• AWS Management Console Private Access – You can access the AWS Console from VPCs without internet connectivity, allowing enterprises to manage their AWS infrastructure through the console while maintaining strict network security controls in air-gapped environments.
• AWS Marketplace Storefront is now generally available – AWS Partners can create and deploy their own branded catalog of solutions and services on their website or application in hours. Channel Partners and Independent Software Vendors can now simplify how they manage their cloud marketplace business and make it easier for customers to discover and purchase their solutions from AWS Marketplace.
• Palo Alto Networks (PANW) Advanced DNS Security on Amazon Route 53 Resolver DNS Firewall (preview) – You can now enforce DNS threat protections from Palo Alto Networks directly on Route 53 DNS Firewall rules, without deploying separate firewalls or modifying VPC configurations — by subscribing to PANW from the DNS Firewall console through the embedded AWS Marketplace widget.

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

Price reductions 

AWS continues to look for ways to increase performance and lower prices for our customers. I noticed a few such efforts last week, so I’d like to share them:

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

The post AWS Weekly Roundup: NY Summit recap, Local Zone in Hanoi, Grok 4.3 in Bedrock, price reductions, and more (June 22, 2026) appeared first on The NOKIA Blog.