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.

Today, Amazon EC2 R9g and R9gd instances are generally available, powered by AWS Graviton5 processors. R9g instances are memory-optimized and deliver up to 25% better compute performance compared to Graviton4-based R8g instances, powered by the most energy efficient processor AWS has ever built.

R9g instances are ideal for memory-intensive workloads including databases, in-memory caches (Valkey, Redis, MemCached), real-time big data analytics, Linux-based workloads including containerized and micro-service-based applications (e.g. Kubernetes, Docker, EKS, ECS), as well as applications written in popular programming languages such as C/C++, Rust, Go, Java, Python, .NET Core, Node.js, Ruby, and PHP.

R9gd instances include local NVMe-based SSD block-level storage, ideal for memory-intensive workloads requiring fast, low-latency local storage such as open-source databases, distributed real-time big data analytics, large in-memory databases, and large caching workloads.

If you’re running workloads on R8g instances today, R9g gives you more performance per vCPU with faster memory, higher network and Amazon EBS bandwidth, and a larger L3 cache, all while using less energy.

What makes R9g different
Graviton5 processors bring several hardware improvements over Graviton4:

• Up to 25% higher compute performance per vCPU
• DDR5 8800 MT/s memory (up from 5600 MT/s in Graviton4), the fastest memory available in the cloud
• 5x larger L3 cache for better data locality
• Up to 2x higher network and EBS bandwidth for the largest instance sizes (up to 100 Gbps network, up to 72 Gbps EBS on the 48xlarge)
• Up to 3x higher packet-processing performance

R9g and R9gd instances support Instance Bandwidth Configuration (IBC), which lets you adjust the allocation of bandwidth between Amazon EBS and Amazon VPC networking by 25%. This helps optimize performance for workloads with specific bandwidth requirements such as databases and caching.

All R9g and R9gd instances run on the AWS Nitro System, which offloads virtualization, storage, and networking to dedicated hardware. This gives your applications near-bare-metal performance while maintaining strong security isolation between instances.

R9g and R9gd instances feature the Nitro Isolation Engine (NIE), the same enhancement to the Nitro System introduced with C9g and M9g instances earlier this year, which enforces isolation of instances and harnesses formal verification to provide assurances of isolation with mathematical precision. Nitro Isolation Engine is a purpose-built component that is responsible for enforcing isolation between virtual machines, including mediation of all access to virtual machine memory, CPU register state, and I/O devices through a minimal set of APIs. Nitro Isolation Engine leverages formal verification, a technique to mathematically demonstrate that the hardware or software behaves as intended, and not just in specific test cases. This intensive verification technique establishes Nitro as the first formally verified cloud hypervisor, pioneering a new standard for mathematically proven cloud security. To learn more about the Nitro Isolation Engine, visit the blog post. For details on the formal verification results, including scope and assumptions, see the technical white paper.

EC2 R9g and R9gd instance specifications
R9g and R9gd instances are each available in 11 sizes, from medium to metal-48xl. The following tables show the full specifications for each size.

R9gd instances offer the same compute and networking performance as R9g, with the addition of local NVMe-based SSD storage for workloads that need fast, low-latency scratch space or temporary caches.

Getting started
You can launch R9g and R9gd instances from the Amazon EC2 console using any supported Arm-based AMI. R9g instances support Amazon Linux 2023, Amazon Linux 2, Ubuntu 22.04+, RHEL 8.4+, SUSE Linux Enterprise Server 15 SP3+, Debian 12+, and other major Linux distributions.

If you’re migrating from R8g, no code changes are required for most applications. Select the equivalent R9g instance size and your application runs with better performance. For containerized workloads, R9g works with Amazon EKS, Amazon ECS, and standard Kubernetes deployments. Multi-arch container images built for Arm64 run without changes.

Several resources help you get started: the AWS Graviton Getting Started Guide covers how to build, run, and optimize workloads on Graviton-based instances. The Graviton Savings Dashboard helps you track cost savings. AWS Transform automates code transformations for migrating Java applications from x86 to Graviton. To learn more, visit AWS Graviton Processors or Level up your compute with AWS Graviton.

Pricing and availability
Amazon EC2 R9g and R9gd instances are available in US East (N. Virginia, Ohio), US West (Oregon), and Europe (Frankfurt) Regions.

R9g and R9gd instances are available for purchase through Savings Plans, On-Demand, Spot Instances, Dedicated Instances, or Dedicated Hosts. For detailed pricing, visit the Amazon EC2 pricing page.

Ready to get started? Launch R9g instances from the Amazon EC2 console. For more details, visit the Amazon EC2 R9g instances page.

If you want to call APIs, search documentation, find regional availability, and check troubleshooting about this feature, try using the AWS MCP Server and plugins with your preferred AI tool. Share your feedback on AWS re:Post for Amazon EC2 or reach out through your usual AWS Support contacts.

— Daniel Abib

The post Amazon EC2 R9g and R9gd instances powered by AWS Graviton5 processors are now generally available 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 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.

Today at the AWS Summit in New York City, Swami Sivasubramanian, AWS VP of Agentic AI, provided the day’s keynote.

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

New in agents customers create

We’re introducing new capabilities on Amazon Bedrock AgentCore: connecting AI agents to organizational, web, and paid knowledge, helping teams find and fix what’s going wrong in production, and enforcing controls that scale as agents grow more capable.

Together, these capabilities help you build more capable agents faster, govern those agents with controls that scale, and improve them continuously. To learn more, read our blog post covering all the new features.

• Introducing Amazon Bedrock Managed Knowledge Base for faster, more accurate enterprise AI applications — You can build enterprise RAG pipelines with the managed Knowledge Base on Bedrock. It provides native data connectors, Smart Parsing for automatic multi-format data preparation, and an Agentic Retriever for complex multi-step queries—all integrated with AgentCore Gateway so developers can focus on business outcomes rather than infrastructure management.
• Announcing Web Search on Amazon Bedrock AgentCore: Ground your AI agents in current, accurate web knowledge — You can use a fully managed web search tool that enables agents to ground responses in current, cited web knowledge with zero data egress from customer’ secured AWS environment. You can focus on building agents instead of manually adding web search to agents on Bedrock AgentCore and managing its infrastructure.
• AWS WAF adds AI traffic monetization capability to help content owners charge AI bots for content access — You can use a new Bot Control capability that enables content providers and publishers price, meter, and collect payment from AI bots and agents accessing their content and APIs. AWS WAF now lets you set a price for that access, accept payment through third-party providers, and grant scoped access directly at the edge.
• Amazon Bedrock AgentCore harness in now generally available — You can do building and running production-grade AI agents in minutes—without coding orchestration loops—by defining your agent’s model, tools, skills, and instructions in configuration, with Bedrock AgentCore harness.
• Coming soon: AWS Context — This is a new service that automatically maps the relationships across your existing data into a knowledge graph and provides agentic search so AI agents in the organization can access governed data relationships, business rules, and domain knowledge at runtime.

New in agents for securing

• Introducing AWS Continuum: Security at machine speed — AWS Continuum for code vulnerabilities, available in a gated preview, takes findings from across your environment, prioritizes by business impact, proves which are exploitable, and drives a fix through your own process.
• AWS Security Agent (now part of AWS Continuum) adds threat modeling, Kiro power and Claude Code plugin, and more — You can generate the new threat modeling (preview) to understand the full context of your application and identify threats with recommended mitigations using the STRIDE framework. You can also use pull request code scanning with remediation across major Git platforms, and IDE integrations via Kiro power, Claude Code plugin, and MCP — letting developers run security reviews and fix issues without context switching.

New in agents for building

• Introducing Kiro for iOS — Kiro introduces a native iOS app, available in a gated preview, built for real engineering work that gives developers a new surface to kick off, monitor, steer, and interact with their Kiro sessions directly from their phone. That means you can now start sessions, check back when they’re done, review diffs, and approve changes all while staying connected to your work with no laptop running.
• AWS DevOps Agent adds release management capabilities to assess code changes before production — You can use a new release readiness review of code changes and autonomous release testing. These new features verify every change against the natural language standards you give to the DevOps Agent and run change-specific tests in production-like environments.
• Proactively reduce tech debt autonomously with AWS Transform – continuous modernization — You can use continuous analysis (preview) to automatically scan your code repositories against configurable baselines and generates findings in hours, not weeks. Once you’ve identified and prioritized findings, you can configure autonomous remediations that generate pull requests for affected repositories automatically.

In addition to the keynote announcements, we have other important launches this week:

The post Top announcements of the AWS Summit in New York, 2026 appeared first on The NOKIA Blog.

Today, we’re announcing AWS Transform – continuous modernization (preview), a new capability of AWS Transform for continuous, autonomous tech debt analysis and remediation at scale. AWS Transform already helps enterprises migrate out of data centers, modernize mainframe and Windows applications, and handle the undifferentiated work of software maintenance: upgrading Java versions, swapping deprecated frameworks, and updating AWS Lambda runtimes before they reach end of life. This new experience builds on this. Customers get full visibility into the state of their codebase across thousands of repositories, prioritized findings, and the pull requests that make the fixes.

Engineering organizations typically consume up to 30% of IT budgets. Customers stitch together point tools: one to detect dependency issues, another to flag vulnerabilities, another for code quality. But no existing tool detects, prioritizes, and remediates tech debt continuously and at scale. The result is a manual, app-by-app cycle that drains engineering capacity. Leaders fall back on self-reported team status that lags reality and hides regressions. AI-assisted development makes this worse: as coding agents accelerate the pace of change, tech debt accumulates faster than developers can keep up. Customers need a capability that detects, prioritizes, and remediates tech debt continuously, autonomously, and at scale.

Continuous analysis

To address the visibility challenge, this new capability within AWS Transform automatically scans your code repositories against configurable baselines and generates findings in hours, not weeks. Out of the box, AWS Transform – continuous modernization includes policies for detecting end of life dependencies, deprecated frameworks, and other common sources of technical debt. You can also extend these with your own remediation patterns specific to your organization, including approved libraries, internal coding standards, or tech debt policies your platform team already enforces. For example, if your team has deprecated an internal library or prefers a particular logging pattern, you can codify that as a policy and run it across all your repositories continuously.

Unlike periodic manual efforts, continuous analysis provides ground truth directly from your code. When a repository falls behind your baseline, you know immediately, showing which components are behind and by how much, regardless of how the team chooses to address it. This eliminates the need for status check-ins and manual compliance tracking, giving platform teams an always current view of their technical debt landscape.

Autonomous remediation at scale

Once you’ve identified and prioritized findings, you can configure autonomous remediations that generate pull requests for affected repositories automatically. This new AWS Transform capability provides out-of-the-box remediation transformations for common scenarios such as Java version upgrades, SDK migrations, and library updates. You can also create custom transformations for organization-specific patterns.

When you launch a remediation, the continuous modernization capability creates pull requests for each affected repository, notifying the owning team with a message like: “This repository is behind on your organization’s baseline for this dependency. Here’s a PR that resolves it.” Teams can review and merge the PR, or choose to remediate using their own approach. Either way, continuous analysis detects when the fix is in place, providing ground truth without requiring manual confirmation.

AWS Transform – continuous modernization integrates with AWS Security Agent to detect and remediate security vulnerabilities at the source-code level, so security findings flow into the same prioritized list and pull-request workflow as other tech debt.

Let’s try it out

To get started with, I navigated to the AWS Transform web application. From the dashboard, I can see an overview of my organization’s repositories and their current status against my configured baselines.

First, I connected my source control system and initiated an analysis against my specified policies. Within hours, the analysis returned findings across my repositories, showing which ones were behind the baseline and by how much. I could see the severity, the number of affected files, and the specific tech debt patterns detected.

From here, I selected a group of high-priority findings and launched a remediation campaign. AWS Transform – continuous modernization generated pull requests for each affected repository. I could monitor the campaign’s progress in real time, seeing which PRs were created, which were merged, and which repositories returned to compliance.

Image 1: AWS Transform – continuous modernization dashboard showing a portfolio overview of your technical debt findings across all connected repositories.

Image 2: The detailed findings view listing individual tech debt items by severity, category, and repository with their available remediation options.

Image 3: The sources view showing connected repositories from GitHub and local environments that continuous modernization is tracking for analysis.

Faster ways to modernize

These capabilities support two distinct approaches to code modernization. In continuous mode, you can use continuous modernization to keep your codebases current as baselines evolve. Think of this as the day-to-day work of upgrading libraries, applying security patches, and enforcing coding standards across your organization.

For larger modernization projects, such as migrating from one framework to another or upgrading a major runtime version across hundreds of applications, you can use campaign mode for targeted, project-based modernization. AWS Transform custom continues to provide the flexible primitive for these larger efforts. AWS Transform – continuous modernization is purpose-built for the recurring, high-volume work that platform teams manage every day.

Now available

AWS Transform – continuous modernization (preview) is available today. You can get started through the AWS Transform web application, via the AWS Transform Kiro Power, or through MCP and skills for integration with your existing coding agents. To learn more, visit the AWS Transform documentation.

The post Proactively reduce tech debt autonomously with AWS Transform – continuous modernization (preview) appeared first on The NOKIA Blog.

AWS Graviton processors have improved steadily across generations, with each iteration delivering advances in compute performance, price-performance, and energy efficiency. At re:Invent 2025, we announced Amazon EC2 M9g, the first Graviton5-powered instances, in preview. Since then, customers have tested M9g across a wide range of workloads and shared their results. ClickHouse saw a 36% performance boost compared to M8g, with zero code changes. Honeycomb achieved 36% better throughput per core compared to Graviton4, across a 6-month A/B test of production observability workloads. HubSpot deployed M9g for MySQL databases and saw query duration drop by up to 60%. Today, M9g instances are generally available, alongside the new M9gd instances for customers who need high-speed, low-latency local NVMe SSD storage. Both are powered by Graviton5, the most powerful and most energy efficient processor AWS has ever built.

While many Arm-based instances have been introduced across the industry, no one comes close to the breadth and depth of the AWS Graviton footprint. After five generations of custom silicon and eight years of continuous investment, Graviton powers over 350 instance types serving more than 120,000 customers, from startups to large enterprises, a robust ISV partner ecosystem, and a broad set of managed services. You can use Graviton for a broad variety of workloads, including web applications, microservices, analytics, databases, machine learning (ML) inference, electronic design automation (EDA), gaming, and video encoding. As workloads grow more compute-intensive and data-driven, many have asked for more processing power, along with greater network and storage bandwidth to move more data and complete workloads faster. We’ve also designed these instances to efficiently package compute, memory, and I/O to maximize energy utilization.

As AI shifts from answering questions to taking actions, running code, using tools, evaluating results, and orchestrating multi-step tasks, the demand for CPU compute is growing rapidly. Graviton5 is built for this shift. With 192 cores, a 5x larger L3 cache, up to 33% lower inter-core latency, and DDR5 memory delivering high bandwidth, Graviton5 helps agents spend less time waiting on CPU-bound steps, processing more instructions, handling large numbers of concurrent environments, and keeping accelerators moving.

Meta is deploying Graviton at scale starting with tens of millions of cores to support its agentic AI efforts, making Meta one of the largest Graviton customers in the world. Agentic AI workloads, including real-time reasoning, code generation, and the orchestration of multi-step tasks, are CPU-intensive and benefit from the higher compute performance, larger caches, higher memory bandwidth, and core density in Graviton5.

What’s new in M9g and M9gd

Built on the sixth-generation AWS Nitro System, M9g instances are powered by AWS Graviton5 processors that deliver higher compute performance, larger caches, and improved memory and I/O scalability compared to Graviton4 processors. Graviton5 offers up to 25% better compute performance compared to Graviton4-based instances, with up to 35% faster performance for web applications, up to 35% for machine learning inference, and up to 30% for databases. As the first CPU in the AWS fleet to support the latest generation of PCIe Gen6 and DDR5-8800 memory, AWS Graviton5 instances deliver the fastest memory of any processor instances in the cloud, and 5 times more L3 cache compared to the previous generation. These improvements also come with better energy efficiency, helping you meet sustainability targets without compromising capability.

Networking and storage bandwidth have been expanded to keep pace with compute growth. M9g and M9gd instances offer up to 15% higher network bandwidth and 20% higher Amazon Elastic Block Store (Amazon EBS) bandwidth on average across sizes, with up to twice the network bandwidth for the largest instance size. M9g and M9gd instances also support Instance Bandwidth Configuration (IBC), a feature that helps you adjust the allocation of bandwidth between Amazon EBS and Amazon Virtual Private Cloud (Amazon VPC) networking for an Amazon EC2 instance by up to 25%. IBC can help optimize performance for workloads with specific bandwidth requirements, such as database read and write performance, query processing, and logging. These enhancements support faster data movement and improved throughput for workloads that rely on high I/O performance.

Security and isolation are foundational requirements for running workloads in the cloud. Within the Nitro System, the AWS Nitro Hypervisor is designed to isolate instances from each other as well as AWS operators. With M9g and M9gd instances we are raising the bar on security even further with the introduction of Nitro Isolation Engine. Nitro Isolation Engine is an enhancement to the Nitro System, which enforces isolation of instances and harnesses formal verification to provide assurances of isolation with mathematical precision. Nitro Isolation Engine is a purpose-built component that is responsible for enforcing isolation between virtual machines, including mediation of all access to virtual machine memory, CPU register state, and I/O devices through a minimal set of APIs. Nitro Isolation Engine leverages formal verification, a technique to mathematically demonstrate that the hardware or software behaves as intended, and not just in specific test cases. This intensive verification technique establishes Nitro as the first formally verified cloud hypervisor, pioneering a new standard for mathematically proven cloud security.

M9g instances provide one vCPU for every four GiB of memory and are well suited for a broad range of general-purpose workloads, including application servers, microservices, midsize data stores, gaming servers, caching fleets, containerized applications, large-scale Java applications, code repositories, web applications, and agentic AI.

For workloads that need high-speed, low-latency local storage, M9gd instances provide up to 11.4 TB of NVMe SSD storage and 30% higher IOPS and storage performance compared to Graviton4-based M8gd instances. M9gd instances are well suited for general-purpose workloads that require a balance of compute and memory with high-speed, low-latency local storage, including application servers, microservices, gaming servers, midsize key-value data stores, caching fleets, data logging, media processing, batch and log processing, and applications that need temporary storage such as caches and scratch files.

Here are the key specifications across the family:

M9gd instances include local NVMe SSD storage. The table below shows the instance storage for each size. Compute, memory, network, and EBS bandwidth specifications are the same as M9g.

Now available

M9g and M9gd instances are available in the US East (N. Virginia), US East (Ohio), US West (Oregon), and Europe (Frankfurt) Regions. M9g and M9gd instances are available for purchase through Savings Plans, On-Demand, Spot Instances, Dedicated Instances, or Dedicated Hosts. For more information, visit Amazon EC2 pricing.

To get started with M9g and M9gd instances, several resources are available. The AWS Graviton Getting Started Guide is a technical guide covering how to build, run, and optimize workloads on Graviton-based instances. The Graviton Savings Dashboard helps you track and measure the cost savings from running workloads on Graviton-based instances. AWS Transform is an AI-powered service that automates code transformations for migrating Java applications from x86 to Graviton-based Amazon EC2 instances, handling compatibility analysis, automated recompilation, dependency updates, and validation.

To learn more about Graviton-based instances, visit AWS Graviton Processors or Level up your compute with AWS Graviton.

— Esra

The post Now available: Amazon EC2 M9g and M9gd instances powered by new AWS Graviton5 processors appeared first on The NOKIA Blog.

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

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

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

Headlines

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

Last week’s launches

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

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

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

Other AWS news

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

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

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

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

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

-Micah

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

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) appeared first on The NOKIA Blog.

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

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

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

Headlines

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

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

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

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

Last week’s launches

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

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

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

Other AWS news

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

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

Upcoming AWS events

Check your calendar and sign up for upcoming AWS events:

• AWS Events — Browse upcoming AWS-led in-person and virtual events, startup events, and developer-focused events near you.
• AWS Power Hour — Weekly live training sessions on Twitch covering various AWS topics.
• Community.aws — Find community-led events, meetups, and user groups in your area.

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

— seb

The post AWS Weekly Roundup: Claude Opus 4.7 in Amazon Bedrock, AWS Interconnect GA, and more (April 20, 2026) appeared first on The NOKIA Blog.

Happy New Year! I hope the holidays gave you time to recharge and spend time with your loved ones.

Like every year, I took a few weeks off after AWS re:Invent to rest and plan ahead. I used some of that downtime to plan the next cohort for Become a Solutions Architect (BeSA). BeSA is a free mentoring program that I, along with a few other Amazon Web Services (AWS) employees, volunteer to host as a way to help people excel in their cloud and AI careers. We’re kicking off a 6-week cohort on “Agentic AI on AWS” starting February 21, 2026. Visit the BeSA website to learn more.

There is still time to submit your idea for the Global 10,000 AIdeas Competition and compete for $250,000 in cash prizes, AWS credits, and recognition, including potential featured placement at AWS re:Invent 2026 and across AWS channels.

You will gain hands-on experience with next-generation AI development tools, connect with innovators globally, and access technical enablement through biweekly workshops, AWS User Groups, and AWS Builder Center resources.

The deadline is January 21, 2026, and no code is required yet. If you’re selected as a semifinalist, you’ll build your app then. Your finished app needs to use Kiro for at least part of development, stay within AWS Free Tier limits, and be completely original and not yet published.

If you haven’t yet caught up with all the new releases and announcements from AWS re:Invent 2025, check out our top announcements post or watch the keynotes, innovation talks, and breakout sessions on-demand.

Launches from the last few weeks

I’d like to highlight some launches that got my attention since our last Week in Review on December 15, 2025:

• Amazon EC2 M8gn and M8gb instances – New M8gn and M8gb instances are powered by AWS Graviton4 processors to deliver up to 30% better compute performance than AWS Graviton3 processors. M8gn instances feature the latest 6th generation AWS Nitro Cards, and offer up to 600 Gbps network bandwidth, the highest network bandwidth among network-optimized EC2 instances. M8gb offer up to 150 Gbps of Amazon EBS bandwidth to provide higher EBS performance compared to same-sized equivalent Graviton4-based instances.
• AWS Direct Connect supports resilience testing with AWS Fault Injection Service – You can now use AWS Fault Injection Service to test how your applications handle Direct Connect Border Gateway Protocol (BGP) failover in a controlled environment. For example, you can validate that traffic routes to redundant virtual interfaces when a primary virtual interface’s BGP session is disrupted and your applications continue to function as expected.
• New AWS Security Hub controls in AWS Control Tower – AWS Control Tower now supports 176 additional Security Hub controls in the Control Catalog, covering use cases including security, cost, durability, and operations. With this launch, you can search, discover, enable, and manage these controls directly from AWS Control Tower to govern additional use cases across your multi-account environment.
• AWS Transform supports network conversion for hybrid data center migrations – You can now use AWS Transform for VMware to automatically convert networks from hybrid data centers. This removes manual network mapping for environments running both VMware and other workloads. The service analyzes VLANs and IP ranges across all exported source networks and maps them to AWS constructs such as virtual private clouds (VPCs), subnets, and security groups.
• NVIDIA Nemotron 3 Nano available on Amazon Bedrock – Amazon Bedrock now supports NVIDIA Nemotron 3 Nano 30B A3B model, NVIDIA’s latest breakthrough in efficient language modeling that delivers high reasoning performance, built-in tool calling support, and extended context processing with 256K token context window.
• Amazon EC2 supports Availability Zone ID across its APIs – You can specify the Availability Zone ID (AZ ID) parameter directly in your Amazon EC2 APIs to guarantee consistent placement of resources. AZ IDs are consistent and static identifiers that represent the same physical location across all AWS accounts, helping you optimize resource placement. Prior to this launch, you had to use an AZ name while creating a resource, but these names could map to different physical locations. This mapping made it difficult to ensure resources were always co-located, especially when operating with multiple accounts.
• Amazon ECS Managed Instances supports Amazon EC2 Spot Instances – Amazon ECS Managed Instances now supports Amazon EC2 Spot Instances, extending the range of capabilities available with AWS managed infrastructure. You can use spare EC2 capacity at up to 90% discount compared to On-Demand prices for fault-tolerant workloads in Amazon ECS Managed Instances.

See AWS What’s New for more launch news that I haven’t covered here. That’s all for this week. Check back next Monday for another Weekly Roundup!

Here’s to a fantastic start to 2026. Happy building!

– Prasad

The post Happy New Year! AWS Weekly Roundup: 10,000 AIdeas Competition, Amazon EC2, Amazon ECS Managed Instances and more (January 5, 2026) appeared first on The NOKIA Blog.

In May, 2025, we launched AWS Transform for mainframe, the first agentic AI service for modernizing mainframe workloads at scale. The AI-powered mainframe agent accelerates mainframe modernization by automating complex, resource-intensive tasks across every phase of modernization—from initial assessment to final deployment. You can streamline the migration of legacy mainframe applications, including COBOL, CICS, DB2, and VSAM to modern cloud environments—cutting modernization timelines from years to months.

Today, we’re announcing enhanced capabilities in AWS Transform for mainframe that include AI-powered analysis features, support for the Reimagine modernization pattern, and testing automation. These enhancements solve two critical challenges in mainframe modernization: the need to completely transform applications rather than merely move them to the cloud, and the extensive time and expertise required for testing.

• Reimagining mainframe modernization – This is a new AI-driven approach that completely reimagines the customer’s application architecture using modern patterns or moving from batch process to real-time functions. By combining the enhanced business logic extraction with new data lineage analysis and automated data dictionary generation from the legacy source code through AWS Transform, customers transform monolithic mainframe applications written in languages like COBOL into more modern architectural styles, like microservices.
• Automated testing – Customers can use new automated test plan generation, test data collection scripts, and test case automation scripts. AWS Transform for mainframe also provides functional testing tools for data migration, results validation, and terminal connectivity. These AI-powered capabilities work together to accelerate testing timelines and improve accuracy through automation.

Let’s learn more about reimagining mainframe modernization and automated testing capabilities.

How to reimagine mainframe modernization

We recognize that mainframe modernization is not a one-size-fits-all proposition. Whereas tactical approaches focus on augmentation and maintaining existing systems, strategic modernization offers distinct paths: Replatform, Refactor, Replace, or the new Reimagine.

In the Reimagine pattern, AWS Transform AI-powered analysis combines mainframe system analysis with organizational knowledge to create detailed business and technical documentation and architecture recommendations. This helps preserve critical business logic while enabling modern cloud-native capabilities.

AWS Transform provides new advanced data analysis capabilities that are essential for successful mainframe modernization, including data lineage analysis and automated data dictionary generation. These features work together to define the structure and meaning to accompany the usage and relationships of mainframe data. Customers gain complete visibility into their data landscape, enabling informed decision-making for modernization. Their technical teams can confidently redesign data architectures while preserving critical business logic and relationships.

The Reimagining strategy follows the principle of human in the loop validation, which means that AI-generated application specifications and code such as AWS Transform and Kiro are continuously validated by domain experts. This collaborative approach between AI capabilities and human judgment significantly reduces transformation risk while maintaining the speed advantages of AI-powered modernization.

The pathway has a three-phase methodology to transform legacy mainframe applications into cloud-native microservices:

• Reverse engineering to extract business logic and rules from existing COBOL or job control language (JCL) code using AWS Transform for mainframe.
• Forward engineering to generate microservice specification, modernized source code, infrastructure as code (IaC), and modernized database.
• Deploy and test to deploy the generated microservices to Amazon Web Services (AWS) using IaC and to test the functionality of the modernized application.

Although microservices architecture offers significant benefits for mainframe modernization, it’s crucial to understand that it’s not the best solution for every scenario. The choice of architectural patterns should be driven by the specific requirements and constraints of the system. The key is to select an architecture that aligns with both current needs and future aspirations, recognizing that architectural decisions can evolve over time as organizations mature their cloud-native capabilities.

The flexible approach supports both do-it-yourself and partner-led development, so you can use your preferred tools while maintaining the integrity of your business processes. You get the benefits of modern cloud architecture while preserving decades of business logic and reducing project risk.

Automated testing in action

The new automated testing feature supports IBM z/OS mainframe batch application stack at launch, which helps organizations address a wider range of modernization scenarios while maintaining consistent processes and tooling.

Here are the new mainframe capabilities:

• Plan test cases – Create test plans from mainframe code, business logic, and scheduler plans.
• Generate test data collection scripts – Create JCL scripts for data collection from your mainframe to your test plan.
• Generate test automation scripts – Generate execution scripts to automate testing of modernized applications running in the target AWS environment.

To get started with automated testing, you should set up a workspace, assign a specific role to each user, and invite them to onboard your workspace. To learn more, visit Getting started with AWS Transform in the AWS Transform User Guide.

Choose Create job in your workspace. You can see all types of supported transformation jobs. For this example, I select the Mainframe Modernization job to modernize mainframe applications.

After a new job is created, you can kick off modernization for tests generation. This workflow is sequential and it is a place for you to answer the AI agent’s questions, providing the necessary input. You can add your collaborators and specify resource location where the codebase or documentation is located in your Amazon Simple Storage Service (Amazon S3) bucket.

I use a sample application for a credit card management system as the mainframe banking case with the presentation (BMS screens), business logic (COBOL) and data (VSAM/DB2), including online transaction processing and batch jobs.

After finishing the steps of analyzing code, extracting business logic, decomposing code, planning migration wave, you can experience new automated testing capabilities such as planning test cases, generating test data collection scripts, and test automation scripts.

The new testing workflow creates a test plan for your modernization project and generates test data collection scripts. You will have three planning steps:

• Configure test plan inputs – You can link your test plan to your other job files. The test plan is generated based on analyzing the mainframe application code and can provide more details optionally using the extracted business logic, the technical documentation, the decomposition, and using a scheduler plan.
• Define test plan scope – You can define the entry point, the specific program where the application’s execution flow begins. For example, the JCL for a batch job. In the test plan, each functional test case is designed to start the execution from a specific entry point.
• Refine test plan – A test plan is made up of sequential test cases. You can reorder them, add new ones, merge multiple cases, or split one into two on the test case detail page. Batch test cases are composed of a sequence of JCLs following the scheduler plan.

Generating test data collection scripts collects test data from mainframe applications for functional equivalence testing. This step actively generates JCL scripts that will help you gather test data from the sample application’s various data sources (such as VSAM files or DB2 databases) for use in testing the modernized application. The step is designed to create automated scripts that can extract test data from VSAM datasets, query DB2 tables for sample data, collect sequential data sets, and generate data collection workflows. After this step is completed, you’ll have comprehensive test data collection scripts ready to use.

To learn more about automated testing, visit Modernization of mainframe applications in the AWS Transform User Guide.

Now available

The new capabilities in AWS Transform for mainframe are available today in all AWS Regions where AWS Transform for mainframe is offered. For Regional availability, visit the AWS Services by Region. Currently, we offer our core features—including assessment and transformation—at no cost to AWS customers. To learn more, visit AWS Transform Pricing page.

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

— Channy

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