Amazon Prime Day 2026 was exclusively for Prime members and ran June 23–26, 2026 with millions of deals across more than 35 categories.

As part of our annual tradition of sharing how AWS powered Prime Day (2016, 2017, 2019, 2020, 2021, 2022, 2023, 2024, and 2025), I want to share the services and chart-topping metrics from AWS that made your amazing shopping experience possible.

Prime Day 2026 – all the numbers
As always, Prime Day was powered by AWS. Here are some of the most interesting and/or mind-blowing metrics:

Amazon Elastic Compute Cloud (Amazon EC2) and AWS Graviton – During Amazon Prime Day 2026, AWS Graviton powered up to 49% of the Amazon EC2 compute used by Amazon.com.

Amazon Elastic Block Store (Amazon EBS) – During Prime Day 2026, Amazon EBS, our high-performance block storage service, peaked at over 24.8 trillion I/O operations, moving over an exabyte of data daily.

AWS Lambda – AWS Lambda handled over 2.3 trillion invocations per day during Prime Day 2026.

Amazon Elastic Container Service (ECS) and Fargate – During Prime Day 2026, Amazon ECS launched an average of 158.3 million tasks per day on AWS Fargate, representing a 47.7 percent increase from the previous year’s Prime Day average.

Amazon CloudFront – Amazon CloudFront delivered over 2.1 trillion HTTP requests during the global week of Prime Day 2026, a 5 percent increase in total requests compared to Prime Day 2025.

Amazon DynamoDB – Amazon DynamoDB, a serverless, fully managed, distributed NoSQL database, powers multiple high-traffic Amazon properties and systems including Alexa, the Amazon.com sites, and all Amazon fulfillment centers. Over the course of Prime Day 2026, between June 23 and June 26, 2026, DynamoDB processed over 59 trillion requests. DynamoDB maintained high availability while delivering single-digit millisecond responses and peaking at 192 million requests per second.

Amazon Aurora – On Prime Day, Amazon Aurora, a relational database management system (RDBMS) built for high performance and availability at global scale for PostgreSQL, MySQL, and DSQL, processed hundreds of billions of transactions, stored 5,491 terabytes of data, and transferred 1,194 terabytes of data.

Amazon ElastiCache – During Prime Day, Amazon ElastiCache peaked at serving over 2.3 quadrillion daily requests and 2.1 trillion requests in a minute.

Amazon Kinesis Data Streams – Amazon Kinesis Data Streams, a fully managed serverless data streaming service, processed a peak of 988 million records per second during Prime Day 2026.

Amazon Simple Notification Service (SNS) – Amazon SNS, a fully managed pub/sub messaging service for application-to-application and application-to-person communication, delivered 5 trillion messages in a single day during Prime Day 2026.

Amazon Simple Queue Service (SQS) – Amazon SQS, a fully managed message queuing service for microservices, distributed systems, and serverless applications, received a peak of 213 million messages per second during Prime Day 2026

AWS CloudTrail – AWS CloudTrail processes billions of API activity events per day for governance, compliance, and operational auditing. During Prime Day 2026, that volume surged to 3.6 trillion events in just four days, a 44% increase over Prime Day 2025.

AWS CloudWatch – Amazon CloudWatch processed over 2.15 quadrillion metric observations per day during Prime Day 2026.

Amazon GuardDuty – During Prime Day 2026, Amazon GuardDuty monitored an average of 14.08 trillion log events per hour, a 59% increase from last year’s Prime Day.

AWS Fault Injection Service (FIS) – We ran over 44,000 AWS FIS experiments – more than six times what we conducted in 2025 – to help ensure Amazon.com remains highly available on Prime Day.

Prepare to scale
If you’re preparing for similar business-critical events, product launches, and migrations, I recommend that you take advantage of AWS Countdown Premium. From retail peak seasons to major sporting events, elections, and healthcare enrollment periods, we help you deliver flawless experiences when it matters most. Our experts help you manage your infrastructure to handle massive traffic spikes while maintaining security and performance. We work alongside your team to scale infrastructure, optimize costs during demand surges, strengthen security measures, and monitor real-time demands. To learn more, visit AWS Countdown Premium for business critical events.

I look forward to seeing what other records will be broken next year!

— Channy

The post All the numbers: Amazon Prime Day 2026 powered by AWS 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.

Amazon CloudWatch now offers CloudWatch Omni, an AI-powered observability experience for the applications and AI agents you run together. You reach Omni through a dedicated URL for your organization and sign in with the identities you already manage, so working in Omni does not require access to the AWS Management Console. Omni is built on OpenTelemetry: the telemetry you already send to CloudWatch appears in Omni with nothing to reconfigure, and any other workload you instrument with OpenTelemetry sends its telemetry to an OpenTelemetry Protocol (OTLP) endpoint.

CloudWatch Omni offers both agent observability and application observability in a single experience. In our companion post, we introduced the agent observability capabilities of Omni for generative AI and agentic workloads. In this post, we present the application observability experience.

Engineering teams spend a significant portion of their observability time maintaining dashboards, tuning thresholds, and switching between tools to piece together what happened during an incident. When an issue crosses team boundaries, context gets lost in Slack threads and screenshots rather than flowing naturally to the next engineer. CloudWatch Omni changes this by organizing observability around your applications rather than individual signals, and bringing your whole team into the same workspace.

What CloudWatch Omni brings
CloudWatch Omni addresses three problems that engineering teams told us they face today.

One collaborative experience for your whole team. Every engineer accesses CloudWatch Omni through a single URL with enterprise SSO (via IAM Identity Center, supporting Okta, Azure AD, and other providers). No AWS Console access is required. SREs, developers, database engineers, and managers share the same data and investigation context. When an investigation escalates, the next person joins the same session with full context already in front of them.

The system adapts as your applications evolve. CloudWatch Omni discovers your services, maps dependencies, and adjusts alarms automatically. Instead of manually curating dashboards and tuning thresholds, you declare what matters (availability targets, latency budgets, error rate thresholds) and Omni adapts as your system changes. When you deploy new services, Omni updates the application topology automatically.

AI-powered investigation with Amazon DevOps Agent. Amazon DevOps Agent participates alongside your team in investigation sessions, correlating signals and suggesting next steps. The agent works from the same telemetry your engineers see, so its suggestions are grounded in the actual state of your application. It identifies correlated events across services, traces root cause paths through your dependency graph, and maintains investigation history for post-incident review.

How an investigation works
When something breaks, CloudWatch Omni opens an investigation session pre-loaded with context. Here is a typical incident workflow:

An alarm fires on elevated error rates in your checkout service. Omni opens a session showing the service topology, correlated signals (a deployment 10 minutes earlier, increased latency from a downstream payment API), and DevOps Agent’s initial analysis.

Your on-call SRE confirms the deployment correlation, pulls in the trace view to identify failing endpoints, and checks if the payment API latency correlates with a capacity limit.

The SRE escalates to the payments team. The payments engineer joins the same session and sees everything found so far, plus DevOps Agent’s correlation with a configuration change in the payment provider’s API gateway. They identify the root cause and roll back.

The entire investigation history is captured automatically. No separate incident report needed.

Walkthrough: setting up your first Space
To set up CloudWatch Omni for your team, open the CloudWatch console and click “Try CloudWatch Omni.”

Figure 1. CloudWatch console — Omni setup page

Next, connect your identity provider through IAM Identity Center (supporting Okta, Azure AD, and other SAML 2.0 providers). Once connected, your team members access Omni directly at your dedicated URL without needing AWS Console credentials.

Create a Space for your team. A Space groups the applications your team owns and the telemetry associated with them.

Figure 2. CloudWatch Omni Home — your team’s workspace with application monitoring, analytics, and agent observability

Once created, Omni discovers your services automatically and maps the dependencies between them. You see your application topology immediately.

Figure 3. Application topology — services and dependencies mapped automatically

You can ask CloudWatch Omni any question about your applications in plain English, and Omni will analyze your telemetry data and surface insights.

Figure 4. Interact with your telemetry in natural language

You can also set up service health alerts, configure what matters to your team, and trigger an AWS DevOps agent investigation to identify the root cause and develop a mitigation plan.

Figure 5. Investigation session — DevOps Agent identifies root causes and suggests next steps

Application-centric organization
CloudWatch Omni organizes telemetry by application rather than by infrastructure component. The system automatically discovers services from the telemetry data and AWS Config resource discovery, maps dependencies, and lets you see your application as a connected system rather than a collection of isolated resources.

Each team gets a Space that contains the applications they own. A Space points at existing CloudWatch data (logs, metrics, traces, and alarms) with no additional data movement required. Dynamic views replace the maintenance burden of static dashboards, providing ongoing visibility into SLOs and application health.

Getting started
Getting started takes minutes and doesn’t require reconfiguration of your existing CloudWatch setup.

If you’re an existing CloudWatch customer: Click “Try CloudWatch Omni” in the CloudWatch console. All your existing telemetry (logs, metrics, traces, and alarms) is immediately available. Workloads are discovered automatically, and you can start an investigation or browse your application topology right away.

For organization-wide deployment: An administrator configures a domain, connects your identity provider via IAM Identity Center, defines Spaces for teams and environments, and invites users. Each Space points at existing CloudWatch data with no additional data movement required.

For applications in other environments: CloudWatch Omni provides connectors that make it easy to bring in telemetry from additional environments. All ingested telemetry appears alongside your AWS data in the same Spaces and investigation sessions.

For generative AI and agentic workloads: The same CloudWatch Omni experience delivers purpose-built observability for AI agents, including trace exploration, evaluation frameworks, and real-time monitoring. In our companion post, we introduced the agent observability capabilities of Omni; for that walkthrough, see Introducing Amazon CloudWatch Omni: AI-powered observability for generative AI and agentic workloads.

Things to know

• CloudWatch Omni extends CloudWatch. Existing alarms, dashboards, APIs, and console workflows continue unchanged.
• Access is through a dedicated web application with enterprise SSO. Engineers don’t need AWS Console access to use it.
• Once you setup, DevOps Agent is enabled by default in every Omni investigation session.

Pricing and availability
Amazon CloudWatch Omni is now available. Existing CloudWatch customers can try it directly from the CloudWatch console. For pricing details, visit the Amazon CloudWatch pricing page.

To get started, visit Amazon CloudWatch Omni or click “Try CloudWatch Omni” in the Amazon CloudWatch console.

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.

— Daniel Abib

The post Introducing Amazon CloudWatch Omni: collaborative AI-powered observability for your applications 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.

Since the first launch of AWS Elastic Beanstalk in 2011, customers have deployed full-stack applications in Java, .NET, Python, Node.js, PHP, Ruby, and Go, trusting Elastic Beanstalk to manage deployment and infrastructure operations so they could focus on business logic. Fifteen years later, that trust has only deepened, and the service has been rebuilt to match it. Now, AWS Elastic Beanstalk is the application management service on AWS that takes full operational responsibility for your production environments. Bring applications however they exist today: source code, Dockerfiles, or container images. Elastic Beanstalk creates and manages the production environment underneath. You manage your application. AWS manages everything else, deploying, scaling, patching, monitoring, and maintaining it continuously. That operational responsibility stays with AWS, for the life of the application.

We have been rebuilding the operational engine underneath and delivering a series of capabilities that make it more powerful than ever. Elastic Beanstalk now uses AI-powered environment analysis to diagnose health issues and recommend fixes automatically. A new official GitHub Action lets teams deploy directly from their existing CI/CD workflows with a single YAML configuration. And we rebuilt the infrastructure foundation to deliver OpenTelemetry-based observability, traffic-splitting deployments with automatic rollback, event-driven autoscaling, secrets management through AWS Secrets Manager, and HTTPS by default via AWS Certificate Manager.

Today, we’re announcing the next chapter of AWS Elastic Beanstalk: a new fully-managed Cluster Mode that deploys, scales, patches, monitors, and upgrades your applications continuously for the life of the workload. You bring your application. AWS runs it.

A new Cluster Mode is built for teams running a portfolio of applications. Instead of operating each application in isolation, you run multiple applications that share infrastructure powered by Amazon Elastic Kubernetes Service (Amazon EKS), fully managed with a single operational baseline. Multiple applications share resources, so per-application cost decreases as your portfolio grows without adding operational complexity. Whether you run ten applications or a hundred, you manage them through one experience, with the same operational guarantees across every stack.

Elastic Beanstalk Cluster Mode benefits for your workloads:

• Source code to production, any runtime. Upload source code in Java, .NET, Python, Node.js, PHP, Ruby, or Go. Elastic Beanstalk handles containerization automatically through Cloud Native Buildpacks when needed. No Dockerfile and no rearchitecting required. You can bring legacy applications from on-premises or deploy new services in any supported language.
• Enterprise compliance built in. Elastic Beanstalk is HIPAA eligible, PCI DSS compliant, and aligned to SOC 1/2/3 with no additional configuration, so teams in regulated industries can deploy production workloads with the compliance posture they already require.
• Production-grade deployment strategies. All-at-once, rolling, immutable, and traffic-splitting deployments with automatic rollback on failure. Event-driven autoscaling. AWS Secrets Manager integration. All native OpenTelemetry enabling easy integration with most observability backends, including Amazon CloudWatch.
• AI-powered troubleshooting. When something goes wrong, Elastic Beanstalk collects service-side logs and provides AI-generated recommendations to help you resolve issues faster without digging through infrastructure.

A first look of Elastic Beanstalk Cluster Mode
To get started, go to the Elastic Beanstalk console, create a new environment, and choose the Cluster in the Deployment type.

Elastic Beanstalk accepts source code, docker file, or container image to deploy your application. For example, you can provide the application code for your environment by selecting Local file and specifying container image build options. For the rest of the sections, the default values should be good for most scenarios.

Choose Create button and the deployment will begin! Note that the first deployment for a given set of subnets triggers EKS cluster creation, which takes about ten-ish minutes. Subsequent deployments are faster because they reuse an existing EKS cluster.

Here’s what it looks like when deployment is successful:

You can also use AWS Command Line Interface (AWS CLI), the EB CLI, or AWS SDKs. For example, consider deploying an application made up of several microservices to Kubernetes. Create an application first.

aws elasticbeanstalk create-application 
    --application-name "my-microservice" 
    --description "Multi-services demo" 

Each microservice may have pre-built images in Amazon Elastic Container Registry (Amazon ECR). Register them as application versions:

IMAGES=(
    "frontend-v1|public.ecr.aws/my-microservices/frontend:v1"
    "cartservice-v1|public.ecr.aws/my-microservices/cart:v1"
    "paymentservice-v1|public.ecr.aws/my-microservices/payment:v1"
    "shippingservice-v1|public.ecr.aws/my-microservices/shipping:v1"
)

for entry in "${IMAGES[@]}"; do
    IFS='|' read -r label uri <<< "$entry"
    aws elasticbeanstalk create-application-version 
        --application-name $APP_NAME 
        --version-label "$label" 
        --image-configuration Source="{Uri=$uri}" 
	--region "us-west-2
    echo "Registered: $label"
done

You can set and deploy the corresponding service options for each service. For example, the frontend service is the only service that needs a public internet interface such as Application Load Balancer and also sets a health check path since it’s an HTTP service:

[
    {"Namespace": "aws:elasticbeanstalk:eks", "OptionName": "cluster-role", "Value": "arn:aws:iam::0123456789012:rol<...>"},
    {"Namespace": "aws:elasticbeanstalk:eks", "OptionName": "node-role", "Value": "arn:aws:iam::0123456789012:role/E<...>"},
    {"Namespace": "aws:elasticbeanstalk:eks:environment", "OptionName": "observability-role", "Value": "arn:aws:iam::0123456<...>"},
    {"Namespace": "aws:elasticbeanstalk:eks:environment", "OptionName": "subnets", "Value": "subnet-1,subnet-2,subnet-3,<...>"},
    {"Namespace": "aws:elasticbeanstalk:eks:environment:autoscaling", "OptionName": "min-replica", "Value": "1"},
    {"Namespace": "aws:elasticbeanstalk:eks:environment:autoscaling", "OptionName": "max-replica", "Value": "2"},
    {"Namespace": "aws:elasticbeanstalk:eks:environment", "OptionName": "cpu", "Value": "0.5"},
    {"Namespace": "aws:elasticbeanstalk:eks:environment", "OptionName": "memory", "Value": "256Mi"},
    {"Namespace": "aws:elasticbeanstalk:eks:environment", "OptionName": "memory-limit", "Value": "512Mi"},
    {"Namespace": "aws:elasticbeanstalk:eks:environment", "OptionName": "service-port", "Value": "8080"},
    {"Namespace": "aws:elasticbeanstalk:eks:alb", "OptionName": "scheme", "Value": "internet-facing"},
    {"Namespace": "aws:elasticbeanstalk:eks:alb", "OptionName": "healthcheck-path", "Value": "/_healthz"}
] #frontend-options.json namespaces

Now, create the frontend service environment with these options. You can continue to deploy each service environment in a similar manner.

aws elasticbeanstalk create-environment 
    --application-name my-microservice 
    --environment-name frontend 
    --version-label frontend-v1 
    --tier Name=Cluster,Type=EKS 
    --option-settings file:///tmp/frontend-options.json 

Here’s a look at the console once all services are deployed:

Elastic Beanstalk Standard powered by Amazon Elastic Compute Cloud (EC2) continues to be fully supported. Standard and Cluster Mode environments run side by side within the same Elastic Beanstalk application, enabling teams to migrate one environment at a time at their own pace. Validation checks confirm compatibility before any changes are made, so no environment is forced to move.

Elastic Beanstalk Standard Mode remains the best fit for:

• Single applications or single-environment use cases
• Windows/.NET Framework workloads on IIS
• Applications that cannot be containerized
• Workloads spending under $500/month where the EKS control plane fee and EKS Auto Mode premium add overhead that a single application cannot offset through bin-packing

To learn more about how to deploy and manage your applications in the Cluster Mode, visit the Elastic Beanstalk Cluster Mode documentation.

Now available
AWS Elastic Beanstalk Cluster Mode is generally available today in all AWS Regions that Elastic Beanstalk is available. 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 troubleshooting about this new feature, try using the AWS MCP Server and plugins with your preferred AI tool.

There is no additional charge for Elastic Beanstalk Cluster Mode. You pay only for the underlying AWS resources your applications consume, including the EKS control plane fee, EKS Auto Mode compute, Amazon ECR, and Amazon CloudWatch. Note Elastic Beanstalk Cluster Mode is not AWS Free Tier eligible. To learn more, visit the AWS Elastic Beanstalk Pricing page.

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

— Channy

The post AWS Elastic Beanstalk introduces Cluster Mode appeared first on The NOKIA Blog.

Twenty years ago today, Jeff Barr wrote a blog post that launched the Amazon EC2 Beta. That single post introduced resizable Linux virtual servers in the cloud, billed by the hour, with one instance type (m1.small) in one Region (US East). It was minimal yet useful, and it changed how the world thinks about computing infrastructure.

In 2021, Jeff covered the fifteen years of EC2 with the backstory and memorable EC2 launches. Over the last five years, AWS has continued to push the boundaries of what cloud computing can deliver, building custom silicon for general-purpose and AI workloads and expanding EC2 into new form factors and deployment models that our customers in 2006 could not have imagined.

The 20 years in brief
In his 15th anniversary post, Jeff chose important milestones of EC2 that established the foundational building blocks that customers still rely on today. Amazon Elastic Block Store (2008) provided persistent block storage. Elastic Load Balancing, Auto Scaling, and Amazon CloudWatch (2009) made applications scalable and highly available. Amazon Virtual Private Cloud (2009) gave customers logically isolated networks. AWS Nitro System (2017) enabled faster innovation and enhanced security. AWS Graviton processors (2018) were designed for cost-sensitive scale-out workloads.

Over 20 years, EC2 grew from one to over 1,200 instance types to meet customer needs across general-purpose, compute-, memory-, and storage-optimized, accelerated computing, and high-performance computing families. These instances expanded from one AWS Region to 39 Regions globally. AWS also extended EC2 beyond the Region boundary with AWS Outposts (2018) running EC2 instances locally, AWS Local Zones (2019) place globally, and AWS Wavelength (2019) inside global 5G telecommunications carrier networks.

While I hate to play favorites, I want to choose some of my favorite EC2 launches of the past five years:

• AWS Inferentia for ML inference at scale (2019): We introduced purpose-built ML inference instances (inf1) with AWS Inferentia chips. Amazon EC2 Inf2 instances became generally available in April 2023 for large-scale generative AI inference workloads. Together with the Inferentia family, AWS Trainium instances now give customers a full stack of AWS-designed silicon optimized for every phase of the AI lifecycle both inference and training.
• EC2 Mac instances (2020): The first Mac instances (mac1) were built on Apple Mac mini with Intel Core i7 (Coffee Lake) on the AWS Nitro System. Mac M1 (mac2) instances launched in July 2022 as the first Arm-based macOS instances on EC2. M2 Pro Mac instances followed in 2023, M4 and M4 Pro Mac instances in 2025, M3 Ultra Mac instances and M4 Max Mac instances in 2026, giving Apple developers a complete range of cloud-based build and test environments for macOS, iOS, iPadOS, tvOS, watchOS, and visionOS apps.
• AWS Trainium for full-stack AI workloads at scale (2021): In November 2021, we previewed Trn1 instances with AWS Trainium accelerators optimized for high-performance deep learning training. In December 2024, Trn2 instances powered by AWS Trainium2 launched, with Trn2 UltraServers linking 64 Trainium2 accelerators via NeuronLink for training trillion-parameter foundation models. At AWS re:Invent 2025, Trn3 UltraServers powered by AWS Trainium3 deliver the best token economics for next-generation agentic, reasoning, and video generation applications. A single Trn3 UltraServer interconnects up to 144 Trainium3 chips to train and serve the largest frontier models. Now, AWS Trainium3 delivers the leading price-performance for high-performance AI training and inference at scale.
• EC2 Capacity Blocks for ML (2023): This new EC2 usage model further democratizes ML democratizes ML by making it easy to access GPU instances to train and deploy ML and generative AI models. You reserve the GPU capacity you need (initially P5 instances) for a future date and only for the duration you require. In November 2024, EC2 Capacity Blocks for ML added supported for provisioning in a matter of minutes and extending up to six months. Now, EC2 Capacity Blocks for ML supports P6-B300, P6-B200, P5e, P5en, P4d, P4de, Trn1, Trn2, and Trn3 instances in addition to P5.
• AWS Graviton5 (2025): Building on eight years of Graviton innovation since 2018, we previewed Graviton5 chips in AWS re:Invent 2025 and launched M9g and M9gd instances powered by Graviton5 and built on the sixth-generation AWS Nitro System. C9g and C9gd followed in June 2026. Now, Graviton5 features 192 cores, a 5x larger cache, and up to 33% lower inter-core latency, making it well suited for the growing demands of agentic AI workloads such as real-time reasoning, code generation, and multi-step task orchestration that require continuous, high-throughput CPU compute at scale.
• AWS Nitro Isolation Engine (2026): Customers wanted to see, not just hear from us, proof of workload isolation in the Nitro Hypervisor. The Nitro Isolation Engine is a purpose-built component inside the Nitro Hypervisor, harnessing formal verification to provide mathematical assurance that customer workloads are isolated from each other and AWS operators, pioneering a new standard for mathematically proven cloud security. This feature is also based on the sixth-generation AWS Nitro System which has continued to evolve since our introduction in 2017.

The foundation underneath it all
Despite two decades of innovation, the fundamental value proposition of Amazon EC2 has not changed. Customers use it to get secure, resizable compute capacity in minutes, pay only for what they consume, and scale on demand without long-term commitments. That same flexibility now extends to AI workloads at a scale no one anticipated in 2006.

EC2 remains the foundational compute layer of AWS. Amazon ECS, Amazon EKS, AWS Lambda, AWS Fargate, AWS Batch, Amazon EMR, Amazon SageMaker AI, and Amazon Bedrock ultimately run on EC2 capacity. Every architectural pattern customers have built over the past twenty years, from simple web servers to trillion-parameter foundation model training clusters, starts with a decision to launch an instance.

We made strong foundational decisions in 2006, and we left room for the service to grow. Twenty years later, that strategy of creating services that are minimal-yet-useful, launching quickly, and iterating rapidly in response to your feedback continues to guide how we build. The next twenty years of cloud computing will demand capabilities we have not yet imagined. Amazon EC2 will continue to be the foundation where your workloads run.

To learn more about Amazon EC2, visit the Amazon EC2 product page or check out what’s new with EC2.

— Channy

The post Happy 20th Birthday, Amazon EC2 appeared first on The NOKIA Blog.

During my time at AWS, I have always looked for opportunities to work with students. I have delivered over 50 talks at universities across the region, and watching the potential in the room is always a strong motivator. It reminds me of why I do this work, and that the students I meet today may well become our customers and collaborators tomorrow. That is why I am happy to open this week with Student Rewards on AWS Builder Center.

Rick Suttles published Introducing Student Rewards on AWS Builder Center, a new benefit for verified higher education students. When you verify your enrollment through SheerID and complete your Builder Center profile, you unlock 12 months of premium AWS Skill Builder access (900+ courses, hands-on labs, certification exam prep, and game-based learning). From there, you earn badges through actions on Builder Center: publishing articles, commenting, and maintaining engagement. At 7 badges, you unlock $10 in AWS Credits. At 14 badges, another $20 in credits. At 21 badges, you earn an AWS Foundational Certification exam voucher ($100 value).

This represents a commitment of over $500 million in resources during this back-to-school season, providing students with the training, tools, and certification needed to start building their careers in cloud and AI. Student Rewards is available to students 18 years or older and enrolled at accredited higher education institutions worldwide, subject to verification and applicable terms.

Verify your student status and start learning, earning badges, and unlocking rewards!

Last week’s launches
Here’s what else happened this week.

• A new AWS Local Zone in Las Vegas, Nevada – This new Local Zone supports Amazon EC2 C7i, M7i, R7i, and C8gn instances, Amazon EBS, Amazon ECS, Amazon EKS, Application Load Balancer, and AWS Direct Connect. AWS Local Zones are now available in more than 30 metropolitan areas worldwide. In addition, AWS added a fourth Availability Zone to the Europe (London) Region, delivering next-generation AI and ML capacity with Trn3 and P6 accelerated instances alongside general-purpose compute.
• Amazon EC2 Auto Scaling now supports batch instance termination – You can now pass up to 100 instance IDs to the TerminateInstanceInAutoScalingGroup API to terminate them as a batch, reducing the number of API calls needed to scale down your Auto Scaling groups. Batch termination is designed for workloads that need to rapidly scale down, such as AI/ML training jobs, container orchestrators, or event-driven architectures that spin up large fleets temporarily.
• AWS CloudShell now includes a built-in visual file editor – CloudShell now includes a visual file editor that you can launch directly from your shell session using a single edit command. The editor supports syntax highlighting, find-and-replace, multi-line selection, copy-paste, and undo-redo in a single browser session. Whether you are updating a deployment script, modifying an agent steering file, editing a CloudFormation template, or fixing a Lambda function, the editor provides a seamless edit-and-run experience without leaving CloudShell.
• Amazon Bedrock now supports SpaceXAI Grok 4.6 with cross-Region inference – Grok 4.6, a frontier model built for coding, agentic tasks, and knowledge work, is now available on Amazon Bedrock. The model runs on the bedrock-runtime endpoint with support for the Responses, Chat Completions, and Converse APIs, and works with existing account-level controls including model invocation logging, Amazon CloudWatch metrics, and cost itemization in AWS Cost Explorer.
• Amazon Bedrock expands API support and introduces cross-Region inference for OpenAI models – Amazon Bedrock now supports OpenAI GPT-5.6 models (Sol, Terra, and Luna) with the Responses, Converse, and Chat Completions APIs, and adds cross-Region inference. Geo cross-Region inference routes requests within a predefined geography (including new US Geo support with this launch), while Global cross-Region inference serves requests from any commercial AWS Region at a lower per-token cost.
• AgentCore payments is now generally available in Amazon Bedrock AgentCore – At general availability, AgentCore payments includes Quick Create for Coinbase credential provisioning directly within the AgentCore console, a curated Coinbase Bazar MCP server of pay-per-use x402 endpoints via AgentCore gateway, support for the Machine Payment Protocol (MPP), and the “upto” scheme in the x402 protocol for pay-per-inference and dynamic pricing use cases. To learn more, visit the AI Blog post.
• AWS Glue 6.0 delivers 30% price reduction and Iceberg v3 support – AWS Glue 6.0 is built on a fully modernized runtime, Apache Spark 4.1, Python 3.13, and Scala 2.13, delivering 30% lower pricing than previous AWS Glue versions. With Iceberg v3, Glue 6.0 adds the VARIANT data type with automatic shredding for faster reads on semi-structured data, deletion vectors for high-performance row-level updates, geometry and geography data types for spatial processing, and flexible schema evolution.

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:

• Updates to your AWS Sign-In experience – AWS is gradually introducing updates to the sign-in and sign-up experience. The redesigned sign-in page introduces a unified email entry point for root users and customers using the new email-based sign-in method, while IAM users continue signing in with their account ID, username, and password. The page also includes sign-in options for customers whose AWS account was created using a supported identity provider (Google, GitHub, Apple, or Amazon.com). A redesigned session selection page simplifies viewing and managing multiple active account and role sessions. If your organization relies on browser automation or scripted workflows that interact with the sign-in page, review the post to understand how these changes might affect your configuration.
• In the works: AWS Builder Lofts in Berlin, Hyderabad, and São Paulo – My colleague Channy announced plans to open new Builder Lofts in three cities. Since the first Builder Loft opened in San Francisco in July 2025, it has welcomed more than 22,500 developers through its doors. Each new location will be a permanent community space offering free workshops, networking events, pitch nights, content creation spaces, and co-working areas. Berlin will focus on digital sovereignty and security-readiness, Hyderabad on AI and cloud-native architecture, and São Paulo on supporting Latin America’s developer ecosystem.
• AWS and Amazon WorkSpaces recognized as a Leader in the 2026 Gartner Magic Quadrant for Desktop as a Service – AWS has been named a Leader in the 2026 Gartner Magic Quadrant for Desktop as a Service (DaaS) for the third consecutive year, evaluated on Completeness of Vision and Ability to Execute. Gartner noted strengths in operations, geographic strategy, and overall viability. This is also the first year the evaluation includes Amazon WorkSpaces for AI agents, a capability that runs AI agents within the same desktop environment, security perimeter, and audit trail as human users.

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, connect, and explore the latest in cloud. Coming up: Zurich (September 2), São Paulo (September 3), Tel Aviv (September 10), and Dubai (September 30). You can also watch keynotes and sessions on the AWS Summits Global Livestream + On-Demand Hub. To access live and on-demand content for a particular Summit, you need to be registered for that event.
• AWS Community Days – Community-led conferences planned and delivered by community leaders. Upcoming events include Bolivia, Santa Cruz (August 29), Toronto, Canada (August 29), JAWS SONIC, Tokyo (September 5), Warsaw, Poland (September 8).

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

Summer is slowly coming to an end, and I am already planning a few days off in the coming months to keep me motivated through the rainy autumn ahead. I hope you are doing the same. Come back next week for more!

— Esra

The post AWS Weekly Roundup: Student Rewards on AWS Builder Center, Local Zone in Las Vegas, and more (August 24, 2026) appeared first on The NOKIA Blog.

Last week I had the joy of participating in Amazon’s “Bring Your Kids to Work Day” with my 7 year old son. We commuted together into the New York City office, his first real rush hour train ride, and spent the day exploring how Amazon uses AI, machine learning, and robotics to deliver packages to customers all over the world. Watching his eyes light up as he saw robots navigating a fulfillment center reminded me why so many of us got into technology in the first place. There’s nothing quite like seeing that sense of wonder when something complex clicks.

That same energy carried into the week’s launches. We’ve got updates across AI pricing, observability, multicloud networking, and data management. Let’s dive in.

Headlines

Amazon Bedrock announces up to 80% lower prices for OpenAI GPT‑5.6 models – If you’re using OpenAI’s GPT‑5.6 family through Amazon Bedrock, your costs just dropped significantly. Effective July 30, on-demand inference prices for GPT‑5.6 Luna are reduced by 80%, while GPT‑5.6 Terra prices are reduced by 20%. Luna now costs $0.20 per million input tokens and $1.20 per million output tokens, making it one of the most affordable frontier-class models available. These price reductions apply automatically — no action required on your part. Read more

Last week’s launches

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

• Amazon CloudWatch announces managed Prometheus collectors – Amazon CloudWatch now supports collecting Prometheus metrics from your AWS infrastructure using fully managed collectors, enabling you to monitor Amazon EKS, Amazon EC2, Amazon ECS, Amazon MSK, and Amazon OpenSearch Service workloads without deploying or managing any agents. If you’ve been maintaining your own Prometheus scraping infrastructure, this removes a significant operational burden. Read more
• AWS Interconnect — multicloud connectivity with Oracle Cloud Infrastructure is now generally available – AWS Interconnect is the first purpose-built multicloud connectivity product of its kind, allowing you to quickly provision resilient, scalable private connections between AWS and other cloud providers. With this GA launch for Oracle Cloud Infrastructure (OCI), you can establish private cross-cloud networking without traversing the public internet, making it easier to run multicloud architectures with the security and performance your workloads demand. Read more
• AWS IAM Identity Center extends multi-Region support to Identity Center directory – You can now replicate IAM Identity Center from your primary AWS Region to additional Regions when using the Identity Center directory as your identity source. If IAM Identity Center is affected by a disruption in the primary Region, your users continue to have access to their AWS accounts using provisioned entitlements in additional Regions. This feature was previously available only for instances connected to external identity providers. Read more
• Amazon S3 Tables now supports the Variant data type for Apache Iceberg V3 – Amazon S3 Tables adds support for the Variant data type, introduced in the Apache Iceberg V3 table format specification. Variant provides a high-performance, native solution for managing semi-structured data within your data lake — think IoT sensor data, application logs, and other schema-flexible payloads — without resorting to JSON blobs. Read more

Other AWS news

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

Upcoming AWS events

Check your calendar and sign up for upcoming AWS events:

• AWS Summits – AWS Summits are free events that bring the cloud and AI community together to connect, learn, and explore the latest technologies. Browse the full calendar to find a Summit near you in the second half of 2026.
• AWS Community Days – Community-led conferences where content is planned, sourced, and delivered by community leaders.

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!

The post AWS Weekly Roundup: Price reduction of GPT models in Bedrock, CloudWatch managed collectors for Prometheus metrics, and more (August 3, 2026) appeared first on The NOKIA Blog.

That community spirit connects nicely to the week’s biggest infrastructure news, which is all about bringing AWS closer to where builders actually are.

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

Headlines

AWS Local Zone in Athens, Greece: AWS has opened a new Local Zone in Athens, Greece, the second Local Zone in EMEA with support for Amazon S3 and Amazon EBS Local Snapshots, so you can store and process data within Greece to help meet local data residency requirements. The Athens Local Zone supports Amazon EC2 (C7i, M7i, and R7i instances), Amazon S3 with the One Zone-Infrequent Access storage class, Amazon EBS, Amazon ECS, and more.

With this launch, you can process and store data in-country while delivering single-digit millisecond latency to your end users. AWS Local Zones place AWS infrastructure much closer to large population and industry hubs to support workloads such as financial services, healthcare, media production, and real-time gaming. For builders in Greece, this means running latency-sensitive workloads locally and meeting in-country data residency requirements, without managing your own data center infrastructure. To learn more, visit AWS Global Infrastructure and Sustainability Blog post.

Last week’s launches

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

• Claude Opus 5 on AWS: You can use Anthropic’s Claude Opus 5, the most advanced Opus model yet, matching Claude Fable 5’s top-tier intelligence in many domains at Opus-tier pricing. Amazon Bedrock offers Claude Opus 5 with zero data retention (ZDR) enabled by default, giving you Opus’ top-tier intelligence while meeting your data governance requirements unlike Claude Fable 5. You have two ways to access Claude Opus 5: Amazon Bedrock and Claude Platform on AWS. To learn more, visit the deep dive blog post.
• AWS Lambda durable execution SDK for .NET is now generally available: You can now build resilient, long-running workflows in C# using Lambda durable functions, without implementing custom progress tracking or integrating an external orchestration service. The SDK is a natural fit for multi-step applications like payment processing pipelines, AI agent orchestration, and human-in-the-loop approvals, it checkpoints progress automatically and can pause execution for up to a year. If you’re a .NET developer building serverless workflows, this removes a lot of the plumbing you used to write by hand.
• Amazon Bedrock AgentCore now delivers unified observability with traces and logs in a single log group: Amazon Bedrock AgentCore now delivers agent traces and prompts to the same Amazon CloudWatch log group as your agent’s logs. Previously, telemetry was split across destinations, trace spans went to a shared log group while prompts, inputs, and outputs went to a separate one, so debugging a single agent invocation meant searching in multiple places. You can now debug an invocation in one place, and apply fine-grained access control and customer-managed key (CMK) encryption at the individual agent level.
• Amazon Connect delivers more natural agentic voice experiences: Amazon Connect now supports more natural, human-sounding agentic voice experiences across 50+ languages, including Portuguese, Spanish, French, Italian, Japanese, Korean, and Thai, with over 100 new voice options and conversational improvements that make AI interactions sound more fluid. Connect’s agentic self-service lets AI agents understand, reason, and take action across voice and digital channels, adapting to a customer’s tone and sentiment. You can now build contact center experiences that feel natural to callers in far more of the languages your customers actually speak.
• Amazon SageMaker Unified Studio now supports Amazon OpenSearch: You can now query and analyze your search and log analytics data from Amazon OpenSearch directly alongside other data assets in Amazon SageMaker Unified Studio. With this connection, you can combine operational search data in OpenSearch with data from sources like Amazon Redshift, Amazon S3, and relational databases, all within a single, governed environment. It’s especially useful when you need to correlate analytical and operational workloads, such as joining application logs with transactional data to uncover insights.
• Amazon CloudWatch announces coding agent insights: Amazon CloudWatch now gives engineering leaders visibility into how AI coding tools are driving value across their organization. Coding agent insights integrates with the Claude apps gateway for AWS to collect telemetry from Claude Code without additional instrumentation, and also supports agents like Codex and GitHub Copilot. As teams scale AI coding adoption, you can now measure the return on that investment with metrics built on OpenTelemetry, no custom instrumentation required.

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:

Upcoming AWS events

Check your calendar and sign up for upcoming AWS events:

• AWS Summits: AWS Summits are free events that bring the cloud and AI community together to connect, learn, and explore the latest technologies. Browse the full calendar to find a Summit near you in the second half of 2026.
• AWS Community Days: Community-led conferences where content is planned, sourced, and delivered by community leaders. If you’re in Latin America, don’t miss AWS Community Day Belo Horizonte on August 22, registration is open at awscommunityday.com.br.

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

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

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: Local Zone in Athens, Claude Opus 5 on AWS, Lambda durable execution for .NET, and more (July 27, 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.

A couple of editions ago I wrote about what I find so energizing about working with startups. Last week I got a fresh dose of it: I spent a few days with the AWS Startups team, listening to stories of founders talking about the problems they’re actually solving. One story that stayed with me came from Marco Negreiros, founder of EyeCare Health, a Brazilian healthtech expanding access to eye care. He shared a striking fact: more than 70% of Brazilian municipalities don’t have a single ophthalmologist. His answer was to put a vision test on the one device almost everyone already carries, the smartphone, so a basic eye screening no longer depends on living near a clinic. Watching a founder turn a gap that big into something that concrete is exactly why I love this space.

This week, I’ll take a closer look at some key launches, and then cover the quarterly AWS Service Availability updates.

Last week’s launches

Here are some of the launches covered from this past week in the AWS News Blog:

Here are some launches and updates that caught my attention:

• Claude Sonnet 5 is now available on AWS – Anthropic’s most capable Sonnet model brings top-tier intelligence at Sonnet pricing for coding, agents, and everyday professional work at scale. It navigates large codebases, calls tools precisely, and holds state across long agentic tasks. To learn more, visit the AI Blog post.
• Amazon WorkSpaces for AI agents is now generally available: AI agents can now securely access and operate desktop applications through managed WorkSpaces environments, without requiring application modernization or custom integrations. To learn more. visit the Desktop and Application Streaming Blog post.
• Amazon OpenSearch Service is now optimized for log analytics: This release introduces a new engine purpose-built for log analytics workloads that delivers up to 4x better price-performance on internal benchmarks, while keeping the full-text search capabilities OpenSearch is known for. Teams can now get aggregations and precise text search in one place. To learn more, visit the Big Data Blog post.
• Amazon SageMaker AI cuts generative AI inference scale-out time by up to half: SageMaker Inference now supports container image caching, enabling up to 2x faster end-to-end scaling for generative AI models during scale-out events. To learn more, visit the AI Blog post.
• Amazon CloudWatch supports creating alarms from log queries : You can now create alarms directly on log query results and set thresholds in a single workflow, eliminating the need to first create metric filters or custom metrics as intermediate steps.

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 June 30, 2026.

Services moving to Maintenance (no longer accessible to new customers starting July 30, 2026):

Services entering Sunset:

Services reaching End of Support (as of June 30, 2026):

• Amazon Chime SDK – Carrier Voice Focus
• Amazon SageMaker AI – Ground Truth Plus

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

Upcoming AWS events

Check your calendar and sign up for upcoming AWS events:

• AWS Summits – AWS Summits are free events that bring the cloud and AI community together to connect, learn, and explore the latest technologies. Browse the full calendar to find a Summit near you in the second half of 2026.
• AWS Community Days – Community-led conferences where content is planned, sourced, and delivered by community leaders. If you’re in Latin America, don’t miss AWS Community Day Belo Horizonte on August 22. Registration is open at awscommunityday.com.br.

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

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

– Daniel Abib

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

The post AWS Weekly Roundup: Claude Sonnet 5 on AWS, Amazon WorkSpaces for AI agents, AWS service availability updates, and more (July 6, 2026) appeared first on The NOKIA Blog.

When you run compute-intensive workloads like real-time analytics, batch processing, video encoding, scientific modeling, or CPU-based machine learning inference, every percentage point of performance matters. You need instances that deliver higher throughput per vCPU, faster memory access, and more network bandwidth, all while keeping your costs in check.

Today I am happy to announce the general availability of Amazon Elastic Compute Cloud (Amazon EC2) C9g and C9gd instances, powered by AWS Graviton5 processors. C9g instances are compute-optimized and deliver up to 25% higher performance per vCPU compared to previous-generation C8g instances. They feature the fastest memory of any processor instance in the cloud, with DDR5 8800MT/s DIMMs, 5x more L3 cache, and up to 3x higher packet-processing performance compared to Graviton4-based instances. The faster memory and larger caches mean your workloads spend less time waiting on data, translating into higher throughput for in-memory analytics, faster agentic loops, and more responsive real-time applications.

C9g instances are ideal for batch jobs, video encoding pipelines, or distributed analytics that can utilize Amazon Elastic Block Store (Amazon EBS) for storage. It is also a natural fit for agentic AI workloads, where concurrent environments and CPU-bound reasoning steps benefit from Graviton5’s higher core count and larger caches. As AI shifts from answering questions to taking actions, running code, and orchestrating multi-step tasks, the demand for CPU compute is growing, and C9g instances are built for this shift.

Some workloads also need fast local storage alongside that compute power. Choose C9gd when your application benefits from high-speed, low-latency local NVMe SSD storage, for example scratch space during HPC simulations, temporary caches for ML inference, or local buffers for ad-serving engines.

Graviton5-based instances with NVMe instance store volumes also support detailed performance statistics, providing high-resolution I/O metrics, including latency histograms broken down by I/O size, up to 1-second granularity and accessible via Amazon CloudWatch or nvme-cli at no additional cost.

C9g and C9gd instances at a glance

C9g and C9gd instances are available in 11 sizes ranging from medium to 48xlarge, plus a bare metal option. They offer up to 15% higher network bandwidth and 20% higher EBS bandwidth on average across sizes compared to the previous generation, with the largest 48xlarge size delivering up to 100 Gbps of network bandwidth and up to 72 Gbps of EBS bandwidth, a 2x increase.

C9gd instances add local NVMe SSD storage with up to 30% higher storage performance compared to previous-generation local storage instances.

Both families are well-suited for high-performance computing (HPC), batch processing, gaming, video encoding, scientific modeling, distributed analytics, CPU-based machine learning inference, and ad serving.

Here are some additional capabilities:

• Instance Bandwidth Configuration (IBC) lets you adjust the allocation of bandwidth between Amazon EBS and Amazon VPC networking by up to 25%, helping you optimize performance for workloads with specific bandwidth requirements such as databases and caching.
• ENA Express support for enhanced networking.
• Up to 128 EBS volumes can be attached to virtual instances.
• Support for Savings Plans, On-Demand, Spot Instances, Dedicated Instances, and Dedicated Hosts.

Nitro Isolation Engine

C9g and C9gd instances are the first compute optimized Amazon EC2 instances to feature the AWS Nitro Isolation Engine, a new capability of the AWS Nitro System. The Nitro Isolation Engine is a purpose-built component of the Nitro Hypervisor, implemented in Rust, that enforces isolation between virtual machines. It mediates all access to VM memory, CPU register state, and I/O devices through a minimal set of APIs.

To learn more about the Nitro Isolation Engine, visit the blog post. For details on the formal verification results, including scope and assumptions, see our technical white paper.

Now available

Amazon EC2 C9g and C9gd instances are now available in US East (Ohio, N. Virginia), US West (Oregon), and Europe (Frankfurt). Additional regions will follow.

You can launch C9g and C9gd instances today using the AWS Management Console, AWS Command Line Interface (AWS CLI), or AWS SDKs. For pricing information, visit the Amazon EC2 Pricing page.

To learn more, visit the Amazon EC2 C9g and C9gd instances page and send feedback to AWS re:Post for EC2 or through your usual AWS Support contacts.

— seb

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