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.

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

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

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

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

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

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

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

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

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

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

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

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

— Daniel Abib

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

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

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.

Today, we are announcing the general availability of AWS Glue 6.0, delivering 30% lower pricing than previous AWS Glue versions and introducing full support for Apache Iceberg v3 features. AWS Glue 6.0 is built on a fully modernized runtime, Apache Spark 4.1, Python 3.12, and Scala 2.13, delivering faster performance.

With this release, AWS Glue provides the most complete Iceberg v3 implementation on any fully serverless managed Spark service, along with new capabilities that simplify ETL authoring, improve PySpark performance, and enable real-time streaming with single-digit millisecond latency.

What is new in AWS Glue 6.0
AWS Glue 6.0 delivers the complete Apache Iceberg v3 specification, built on Iceberg 1.11.0. The headline feature is the VARIANT data type with shredding support, which achieves faster query read performance compared to traditional string data type columns for semi-structured data.

With VARIANT shredding, you can store and query JSON, logs, and event data without flattening schemas, eliminating duplicate data copies, custom parsing code, and pipeline breakage when schemas change. This capability transforms how teams handle semi-structured data at scale.

Additional Iceberg v3 capabilities include:

• Geometry and Geography data types: Enable native spatial processing for GIS analytics, location intelligence, and geospatial data pipelines directly on managed Spark.
• Nanosecond-precision timestamps: Support IoT sensor data, scientific computing, and high-frequency financial workloads that require precision beyond standard milliseconds.
• Unknown type handling: Process data with unexpected or evolving schemas without pipeline failures, providing resilience against upstream schema changes.

AWS Glue 6.0 also includes most significant upgrade in Spark 4.1, the modern runtime engine:

• Spark declarative pipelines: Spark Declarative Pipelines introduces a simplified approach to ETL authoring. Data engineers declare transformations, specifying what data should look like, while the engine automatically determines execution order and optimization. This reduces the complexity of pipeline development and eliminates manual orchestration overhead.
• Arrow-native Python UDFs and UDTFs: AWS Glue 6.0 introduces Arrow-native execution for Python User-Defined Functions (UDFs) and User-Defined Table Functions (UDTFs). This eliminates serialization overhead between Python and the JVM, improving PySpark performance for complex transformations.
• Real-time streaming mode: For stateless streaming use cases, AWS Glue 6.0 introduces a real-time streaming mode that achieves single-digit millisecond latency. Built on Spark 4.1’s Real-Time Mode with Glue-optimized execution, this capability supports real-time event processing, low-latency data transformation pipelines, and time-sensitive data routing.

Getting started with AWS Glue 6.0
No API changes are required to use AWS Glue 6.0. You can select the new version using the existing --glue-version parameter in the create-job or update-job APIs through AWS Command Line Interface (AWS CLI), AWS SDK, AWS Glue Studio, Amazon SageMaker Unified Studio, and your preferred IDE.

To get started with AWS Glue 6.0 jobs in the AWS Glue Studio console, open the AWS Glue job and on the Job Details tab, choose the version Glue 6.0 – Supports Spark 4.1, Scala 2, Python 3. You can create new AWS Glue jobs on AWS Glue 6.0 to get the benefit from the improvements, or migrate your existing AWS Glue jobs.

To start using AWS Glue 6.0 on an AWS Glue Studio notebook or an interactive session through a Jupyter notebook, set 6.0 in the %glue_version magic. You can also upgrade existing jobs to Glue 6.0 using the Spark upgrade agent on AWS Glue Studio or use the auto-upgrade feature in their existing Glue jobs to automatically upgrade them to Glue 6.0.

To learn more, visit the AWS Glue 6.0 version detail and Migrating AWS Glue for Spark jobs to AWS Glue version 6.0 in the AWS documentation.

Now available
AWS Glue 6.0 is generally available today in all AWS Regions where AWS Glue operates. For Regional availability and a future roadmap, visit the AWS Capabilities by Region. If you want to call APIs, search documentation, find regional availability, and check troubleshooting about this new feature, try using the AWS MCP Server and plugins with your preferred AI tool.

You pay an hourly rate, billed by the second, for crawlers (discovering data) and extract, transform, and load (ETL) jobs (processing and loading data). For the AWS Glue Data Catalog, you pay a simplified monthly fee for storing and accessing the metadata. The first million objects stored are free, and the first million accesses are free. To learn more, visit AWS Glue Pricing page.

Give it a try in the AWS Glue Studio console, and send feedback to AWS re:Post for AWS Glue or through your usual AWS support contacts.

— Channy

The post AWS Glue 6.0 now available with 30% lower price and full Apache Iceberg v3 support appeared first on The NOKIA Blog.

Last week, AWS contributors joined the OpenSearch and Valkey communities at Open Source Summit Korea 2026 and MCP DevSummit Seoul 2026 to meet open source developers and contributors. At the four-day event, community leaders and users of these Linux Foundation open source projects gathered to share knowledge, collaborate on solutions, and push the projects forward.

Leaders of the Korean OpenSearch communities volunteered to participate in the booth, and also had time to network and interact in the user group meetup.

OpenSearch is an open source, enterprise-grade search and observability suite that brings order to unstructured data at scale. On June 9, 2026, OpenSearch 3.7 introduced new tools designed to query, alert, and track SLOs across logs, traces, and metrics through a single interface and retrieve vectors up to 5.5x faster for improved search performance. Since July 30, 2026, you can run OpenSearch version 3.7 on Amazon OpenSearch Service for improvements in vector search performance, search relevance, and Query Insights.

Valkey is an open source high-performance key/value datastore that supports a variety of workloads such as caching, message queues, and it can act as a primary database. On May 19, 2026, Valkey 9.1 introduced a redesigned I/O threading model that improves throughput by up to 17% and reduces memory usage for strings under 128 bytes by up to 20%. Since June 23, 2026, you can run Valkey 9.1 in Amazon ElastiCache for node-based clusters, delivering higher throughput, improved memory efficiency, and stronger access control for multi-tenant workloads.

You can connect with AWS contributors at upcoming OpenSearch and Valkey community events.

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

• Amazon EC2 application status checks: Amazon EC2 introduces a new status check that helps you detect and respond to application-level issues on your EC2 instances. With application status checks, EC2 monitors applications to detect issues such as a web server that has stopped accepting requests, a Docker daemon that is not running, an incorrect networking configuration, or a network interface that is no longer passing traffic. To learn more, visit the Application status checks documentation.
• AWS IAM role manager to set up IAM roles automatically: You can use a new role manager that automatically sets up the IAM roles your AWS services need. When you set up a supported service in the console, role manager creates a default role on your behalf, or reuses one that already exists in your account if it matches the required permissions. Role manager supports six AWS service consoles at launch. To learn more, read How AWS IAM role manager rethinks the starting point for IAM roles.
• OpenAI Daybreak available to eligible customers on Amazon Bedrock: Daybreak is the cyber defense initiative from OpenAI that gives defenders governed access to frontier AI for cybersecurity work. For most security teams, Daybreak Blue, powered by GPT-5.6 Sol, serves as the starting point across defensive workflows including vulnerability discovery, detection engineering, and incident response. Daybreak Red, powered by a new GPT-5.6 Cyber, is designed for advanced, authorized tasks such as vulnerability research, exploit reproduction, and mitigation development. To enroll, contact OpenAI or reach out to your AWS account team for guidance on eligibility. To learn more, read the AI Blog post.
• New foundation models in Amazon SageMaker JumpStart: We’re expanding the portfolio of foundation models available to AWS customers. These models address different enterprise AI challenges with specialized capabilities:

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 you may find interesting:

• The deprecation of email validation in AWS Certificate Manager: ACM will discontinue support for email-validated public certificates by September 30, 2027. If you use email validation for your ACM public certificates, you need to migrate to DNS validation before that date. For Amazon CloudFront distributions, HTTP validation is also available.
• The next-generation AWS VPN Client with CLI support and admin controls: You can use a new AWS VPN Client built on OpenVPN3. With the new client, you get full backward compatibility with existing AWS Client VPN endpoints while delivering the automation capabilities and security posture that enterprise networking teams have been asking for.
• Oracle Exadata on Exascale for Oracle AI Database@AWS: ExaDB-XS brings Exadata-class performance and availability through a consumption-based model. With ExaDB-XS, you can scale compute and storage independently in small increments and pay only for what you consume.

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: EC2 application status checks, IAM role manager, OpenAI Daybreak on Bedrock, and more (August 17, 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.

Today, we’re announcing a new metadata capability for Amazon Simple Storage Service (Amazon S3) called annotations, enabling you to attach rich, large-scale business context directly to your objects. You can store up to 1,000 named annotations per object, each up to 1 MB in size, totaling up to 1 GB per object, in flexible formats like JSON, XML, YAML, or plain text. You can modify or delete an annotation at any time, without re-writing your objects, making it easy to keep your object context current.

Organizations are building AI agents and autonomous workflows that need to find, understand, and act on data without human intervention. To support these agentic workflows, you need metadata that can evolve alongside the data, scale to petabytes of objects, and remain queryable without expensive retrieval.

With S3 annotations, you can store context such as AI-generated transcripts, content ratings, or technical specifications directly alongside your objects. Your context moves automatically with the object during copy, replication, and cross-region transfers, and S3 removes it when you delete the object. When you enable S3 Metadata, annotations automatically flow into fully managed annotation tables that you can query with Amazon Athena and other analytics engines.

Common use cases

Annotations solve complex metadata challenges across industries:

• Media & Entertainment: Track transcripts, content moderation results, subtitle files, and licensing metadata as separate annotations on video assets, eliminating the need to synchronize metadata across multiple media asset management systems.
• Financial Services: Attach AI-generated investment summaries and sentiment analysis to research documents, enabling autonomous research agents to discover relevant datasets through natural-language queries without maintaining separate metadata databases.
• Life Sciences: Annotate clinical trial data with regulatory status, patient cohort details, and approval chains, making compliance audits faster while keeping full context accessible for archived data in Amazon S3 Glacier storage classes without retrieval charges.

How annotations address metadata challenges

Amazon S3 already supports several ways to describe your objects. System-defined metadata captures properties like size and storage class. Object tags support operational tasks like access control and lifecycle management. User-defined metadata lets you add small amounts of custom information at upload time.

While these capabilities work well for their intended purposes, they have limitations when you need to attach much richer context without building and maintaining separate metadata systems. Annotations address these needs by providing metadata capabilities at a fundamentally different scale and flexibility, offering mutable, queryable context per object compared to 10 immutable tags or 2 KB of headers.

Today, metadata describing S3 objects often lives in separate databases or sidecar files, requiring complex synchronization workflows that can exceed data storage costs. When you enable S3 Metadata annotation tables, this context becomes queryable at scale through Amazon Athena. AI agents can discover your data through natural language with the S3 Tables MCP server, which provides a standardized interface for AI models to query your annotations. You can query annotations for objects in any storage class, without restoring the objects or paying retrieval charges.

Getting started with annotations

To start using annotations, make sure your AWS Identity and Access Management (IAM) policy or bucket policy grants permissions for the s3:PutObjectAnnotation and s3:GetObjectAnnotation actions. You can then add annotations to any existing or new S3 object using the PutObjectAnnotation API.

For example, a media company can attach technical specifications and AI-produced summaries to a video asset using the AWS Command Line Interface (AWS CLI):

# Create a JSON file with technical metadata
cat > mediainfo.json << 'EOF'
{"codec":"H.265","resolution":"3840x2160","audio_tracks":8,"frame_rate":29.97}
EOF

# Attach it as an annotation
aws s3api put-object-annotation 
  --bucket my-media-bucket 
  --key videos/documentary-2026.mp4 
  --annotation-name mediainfo 
  --annotation-payload ./mediainfo.json

# Attach a plain-text AI-generated summary as a separate annotation
echo "A 90-minute nature documentary covering wildlife migration patterns across three continents, featuring aerial footage and underwater sequences. Languages: English, Spanish, Portuguese." > ai_summary.txt

aws s3api put-object-annotation 
  --bucket my-media-bucket 
  --key videos/documentary-2026.mp4 
  --annotation-name ai_summary 
  --annotation-payload ./ai_summary.txt

These commands attach two separate annotations to the same video object. The mediainfo annotation stores structured technical specifications as JSON, while the ai_summary annotation stores a text description. Each annotation is identified by a unique name, and you can read and modify each one independently. With unique names for each annotation, you can use different annotations to support multiple concurrent enrichment workflows, for example, one team adding technical metadata while another team adds content classifications, without interfering with each other.

Retrieve a specific annotation using the GetObjectAnnotation API:

aws s3api get-object-annotation 
  --bucket my-media-bucket 
  --key videos/documentary-2026.mp4 
  --annotation-name mediainfo 
  ./mediainfo-output.json

To see all annotations attached to an object, use the ListObjectAnnotations API:

aws s3api list-object-annotations 
  --bucket my-media-bucket 
  --key videos/documentary-2026.mp4

When you no longer need a specific annotation, remove it using the DeleteObjectAnnotation API:

aws s3api delete-object-annotation 
  --bucket my-media-bucket 
  --key videos/documentary-2026.mp4 
  --annotation-name mediainfo

You can update an existing annotation at any time by calling PutObjectAnnotation again with the same annotation name. For large objects uploaded using multipart upload, attach annotations after completing the multipart upload using the PutObjectAnnotation API.

Querying annotations at scale with S3 Metadata tables

Attaching annotations to individual objects is useful, but the real power comes when you query across all your annotations at scale. When you enable S3 Metadata annotation tables on your bucket, S3 automatically indexes your annotations into a fully managed Apache Iceberg table, called an annotation table. You can query annotation tables with Amazon Athena or any Iceberg-compatible engine.

To enable annotation tables, use the S3 console or the CreateBucketMetadataConfiguration API. The following example creates a new metadata configuration with annotation tables enabled while keeping journal tables for change tracking and disabling the live inventory table:

{
  "JournalTableConfiguration": {
    "RecordExpiration": { "Expiration": "DISABLED" }
  },
  "InventoryTableConfiguration": { "ConfigurationState": "DISABLED" },
  "AnnotationTableConfiguration": {
    "ConfigurationState": "ENABLED",
    "Role": "arn:aws:iam::123456789012:role/S3MetadataAnnotationRole"
  }
}

This configuration tells S3 to automatically capture all your annotations in a queryable table. Once applied, any annotation you attach to objects in this bucket will appear in the table within approximately one hour.

If the bucket already has a metadata configuration, use the UpdateBucketMetadataAnnotationTableConfiguration API:

aws s3api update-bucket-metadata-annotation-table-configuration 
  --bucket my-media-bucket 
  --annotation-table-configuration '{"ConfigurationState":"ENABLED","Role":"arn:aws:iam::123456789012:role/S3MetadataAnnotationRole"}'

Once enabled, your annotations automatically flow into the annotation table. Journal tables update in near real time, while annotation tables refresh within an hour. Unlike traditional metadata tables that require predefined schemas, annotation tables automatically adapt to any JSON, XML, or YAML structure you write. Each annotation becomes a row in the table with its content stored in a text_value column, letting you query across all annotations without schema migrations.

If you enable annotation tables on a bucket that already has annotated objects, S3 automatically backfills existing annotations into the table. The backfill process runs in the background and can take several hours to days depending on the number of objects.

For example, to find all video assets with more than 8 audio tracks across your entire bucket using Amazon Athena:

SELECT DISTINCT bucket, object_key
FROM "s3tablescatalog/aws-s3"."b_my_media_bucket"."annotation"
WHERE name = 'mediainfo'
AND CAST(json_extract_scalar(text_value, '$.audio_tracks') AS INTEGER) > 8

This query scans the annotation table for all annotations named mediainfo, extracts the audio_tracks field from the JSON content, and returns objects where the count exceeds 8.

Or to find all objects that received new annotations in the last 24 hours through the journal table:

SELECT bucket, key, version_id, record_timestamp, annotation.name
FROM "s3tablescatalog/aws-s3"."b_my_media_bucket"."journal"
WHERE record_timestamp >= (current_date - interval '1' day)
AND annotation.name IS NOT NULL
AND record_type IN ('CREATE_ANNOTATION', 'DELETE_ANNOTATION')

This query uses the journal table to track annotation changes in near real time, which is ideal for building event-driven workflows that respond to new or deleted annotations.

You can also use natural language to search objects by their annotations using agents in Amazon SageMaker Unified Studio or any IDE with the S3 Tables MCP server. For example, asking “find all PG-rated movies with Spanish subtitles from 2023” returns results in seconds instead of the hours it would take querying multiple disconnected systems.

Get started today

You can start using Amazon S3 annotations today in all AWS Regions, including the AWS China Regions. Annotation tables are available in all AWS Regions where S3 Metadata is available.

Whether you’re building AI agents that need to discover data autonomously, managing petabytes of media assets with complex metadata, or tracking compliance context for archived datasets, annotations give you the scale and flexibility to attach rich metadata directly to your objects without managing separate systems.

Annotation storage is always billed at S3 Standard rates, even if the parent object is in S3 Glacier or another storage class. For full pricing details, visit the Amazon S3 pricing page.

To learn more and get started, visit the Amazon S3 Metadata overview page and the Amazon S3 documentation. Send feedback to AWS re:Post for S3 or through your usual AWS Support contacts.

Daniel Abib

The post Amazon S3 annotations: attach rich, queryable context directly to your objects appeared first on The NOKIA Blog.

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

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

Let’s dive into this week’s AWS news.

Headlines

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

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

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

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

Last week’s launches

Here are some launches and updates that caught my attention:

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

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

Other AWS news

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

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

Upcoming AWS events

Check your calendar and sign up for these events:

• AWS Summit Amsterdam — Join us in Amsterdam on May 27 for a full day of cloud and AI sessions, hands-on labs, and networking with builders and AWS experts from across Europe. Registration is free.
• AWS Summit Bangkok — AWS Summit Bangkok takes place on May 28. It’s a fantastic opportunity for builders and customers across Southeast Asia to connect and explore the latest in cloud innovation.
• AWS Summit Milan — Also on May 28, AWS Summit Milan brings the AWS community together in Italy. If you’re in Southern Europe, this is your event.
• AWS Summit Mumbai — Also on May 28, AWS Summit Mumbai brings cloud and AI content to builders across India. Check the link for the full agenda and registration.
• AWS Summit Los Angeles — Mark your calendar for June 10 in Los Angeles. The AWS Summit LA is coming up and it’s a great opportunity to connect with the West Coast builder community.
• AWS Community Days — Community-led conferences where content is planned, sourced, and delivered by community leaders. If you’re in Latin America, don’t miss AWS Community Day Belo Horizonte on August 22 — registration is open at awscommunityday.com.br.

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

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

— Daniel Abib

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

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

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

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

Headlines

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

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

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

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

Last week’s launches

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

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

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

Other AWS news

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

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

Upcoming AWS events

Check your calendar and sign up for upcoming AWS events:

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

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

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

— Daniel Abib

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

The post AWS Weekly Roundup: Anthropic & Meta partnership, AWS Lambda S3 Files, Amazon Bedrock AgentCore CLI, and more (April 27, 2026) appeared first on The NOKIA Blog.

Last week, what excited me most was the launch of the 2026 AWS AI & ML Scholars program by Swami Sivasubramanian, VP of AWS Agentic AI, to provide free AI education to up to 100,000 learners worldwide. The program has two phases: a Challenge phase where you’ll learn foundational generative AI skills, followed by a fully funded three-month Udacity Nanodegree for the top 4,500 performers. Anyone 18 or older can apply, with no prior AI or ML experience required. Applications close on June 24, 2026. Visit the AWS AI & ML Scholars webpage to learn more and apply.

I’m also excited about the start of AWS Summit season, kicking off with AWS Summit Paris on April 1, followed by London on April 22. AWS Summits are free in-person events where builders and innovators can learn about Cloud and AI, think big, and make new connections. Explore the AWS Summits near you and join us in person.

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

Last week’s launches

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

• Announcing Amazon Aurora PostgreSQL serverless database creation in seconds — Amazon Aurora PostgreSQL now offers express configuration, a streamlined setup with preconfigured defaults that supports creating and connecting to a database in seconds. With just two clicks, you can launch an Aurora PostgreSQL serverless database. You can modify certain settings during or after creation.
• Amazon Aurora PostgreSQL now available with the AWS Free Tier — Amazon Aurora PostgreSQL is now available on the AWS Free Tier. If you’re new to AWS, you receive $100 in AWS credits upon sign-up and can earn an additional $100 in credits by using services like Amazon Relational Database Service (Amazon RDS).
• Announcing Agent Plugin for AWS Serverless — With the new Agent Plugin for AWS Serverless, you can easily build, deploy, troubleshoot, and manage serverless applications using AI coding assistants like Kiro, Claude Code, and Cursor. This plugin extends AI assistants with structured capabilities by packaging skills, sub-agents, and Model Context Protocol (MCP) servers into one modular unit. It automatically loads the guidance and expertise you need throughout development to build production-ready serverless applications on AWS.
• Amazon SageMaker Studio now supports Kiro and Cursor IDEs as remote IDEs — You can now remotely connect from Kiro and Cursor IDEs to Amazon SageMaker Studio. This lets you use your existing Kiro and Cursor setup, including spec-driven development, conversational coding, and automated feature generation, while accessing the scalable compute resources of Amazon SageMaker Studio.
• Introducing visual customization capability in AWS Management Console — You can now customize your AWS Management Console with visual settings like account color and control which regions and services you see. Hiding unused regions and services helps you focus better and work faster by reducing cognitive load and unnecessary scrolling.
• Announcing Aurora DSQL connector to simplify building Ruby applications — You can now use the Aurora DSQL Connector for Ruby (pg gem) to easily build Ruby applications on Aurora DSQL. The Ruby Connector simplifies authentication and improves security by automatically generating tokens for each connection, eliminating the risks of traditional passwords while maintaining full compatibility with existing pg gem features.
• AWS Lambda increases the file descriptor limit for functions running on Lambda Managed Instances — AWS Lambda increases the file descriptor limit from 1,024 to 4,096, a 4x increase, for functions running on Lambda Managed Instances (LMI). You can now run I/O intensive workloads such as high-concurrency web services and file-heavy data processing pipelines without running into file descriptor limits.
• AWS Lambda now supports up to 32 GB of memory and 16 vCPUs for Lambda Managed Instances — AWS Lambda functions on Lambda Managed Instances now support up to 32 GB of memory and 16 vCPUs. You can run compute-intensive workloads like data processing, media transcoding, and scientific simulations without managing infrastructure. Plus, you can adjust the memory-to-vCPU ratio (2:1, 4:1, or 8:1) to fit your workload.
• Announcing Bidirectional Streaming API for Amazon Polly — Traditional text-to-speech APIs use a request-response pattern. The new Bidirectional Streaming API for Amazon Polly is designed for conversational AI applications that generate text or audio incrementally, like large language model (LLM) responses. This lets you start synthesizing audio before the full text is available.

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

Upcoming AWS events

Check your calendar and sign up for upcoming AWS events:

• AWS Summits — As I mentioned earlier, join AWS Summits in 2026 for free in-person events where you can explore emerging cloud and AI technologies, learn best practices, and network with industry peers and experts. Upcoming Summits include Paris (April 1), London (April 22), Bengaluru (April 23–24), Singapore (May 6), Tel Aviv (May 6), and Stockholm (May 7).
• AWS Community Days — Community-led conferences where content is planned, sourced, and delivered by community leaders, featuring technical discussions, workshops, and hands-on labs. Upcoming events include San Francisco (April 10) and Romania (April 23–24).

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

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

— Prasad

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

The post AWS Weekly Roundup: AWS AI/ML Scholars program, Agent Plugin for AWS Serverless, and more (March 30, 2026) appeared first on The NOKIA Blog.