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.

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.

AWS has reached its 20th anniversary! With a steady pace of innovation, AWS has grown to offer over 240 comprehensive cloud services and continues to launch thousands of new features annually for millions of customers. During this time, over 4,700 posts have been published on this blog—more than double the number since Jeff Barr wrote the 10th anniversary post.

AWS changed my life

Reflecting on what I was doing 20 years ago, I met Jeff in Seoul on March 13, 2006, when he came as the keynote speaker for the Korea NGWeb conference. At that time, Amazon was one of the first pioneers to initiate an API economy, introducing ecommerce API services. After the keynote speech, he returned home that evening, and I believe he wrote the Amazon S3 launch blog post on the flight back to the United States.

That short meeting with him brought significant changes to my life. He became my role model as a blogger, and I began building API-based services in my company and opening them to third-party developers. When I was a PhD student while taking a break from work, I realized that for individual researchers like me, AWS Cloud services are powerful tools for conducting large-scale research projects. After returning to work, my company became one of the first AWS customers in Korea in 2014. Countless developers—myself included—have embraced cloud computing and actively used its capabilities to accomplish what was previously impossible.

Over the past decade, the technology landscape has transformed dramatically. Deep learning emerged as a breakthrough in AI, evolving through generative AI based on large language models (LLMs) to today’s agentic AI technology. Jeff wrote, “When looking into the future, you need to be able to distinguish between flashy distractions and genuine trends, while remaining flexible enough to pivot if yesterday’s niche becomes today’s mainstream technology.” This principle guides how AWS approaches innovation—we start by listening to what customers truly need. The real trend isn’t pursuing every emerging technology, but rather reimagining solutions that address customers’ most critical challenges.

20 years of AWS

For the first 10 years, Jeff selected his favorite AWS launches and blog posts. Amazon S3, Amazon EC2 (2006), Amazon Relational Database Service, Amazon Virtual Private Cloud (2009), Amazon DynamoDB, Amazon Redshift (2012), Amazon WorkSpaces, Amazon Kinesis (2013), AWS Lambda (2014), and AWS IoT (2015).

While I also hate to play favorites, I want to choose some of my favorite AWS blog posts of the past decade.

• Deploying containers easily (2014) – Amazon Elastic Container Service makes it straightforward for you to run any number of containers across a managed cluster of Amazon EC2 instances using powerful APIs and other tools. In 2017, we launched Amazon Elastic Kubernetes Service as a fully managed Kubernetes service and AWS Fargate as a serverless deployment option.
• High availability database at global scale (2017) – Amazon Aurora is a modern relational database service offering performance and high availability at scale. In 2018, we launched Amazon Aurora Serverless v1, and this serverless database evolved to Amazon Aurora Serverless v2 to scale down to zero. In 2025, we also launched Amazon Aurora DSQL is the fastest serverless distributed SQL database for always available applications.
• Machine learning (ML) at your fingertips (2017) – Amazon SageMaker is a fully managed end-to-end ML service that data scientists, developers, and ML experts can use to quickly build, train, and host machine learning models at scale. In 2024, we launched the next generation of Amazon SageMaker, a unified platform for data, analytics, and AI and introduced Amazon SageMaker AI to focus specifically on building, training, and deploying AI and ML models at scale.
• Best price performance for cloud workloads (2018) – We launched Amazon EC2 A1 instances powered by the first generation of Arm-based AWS Graviton Processors designed to deliver the best price performance for your cloud workloads. Last year, we previewed EC2 M9g instances powered by AWS Graviton5 processors. Over 90,000 AWS customers have reaped the benefits of Graviton supporting popular AWS services such as Amazon ECS and Amazon EKS, AWS Lambda, Amazon RDS, Amazon ElastiCache, Amazon EMR, and Amazon OpenSearch Service.
• Run AWS Cloud in your data center (2019) – AWS Outposts is a family of fully managed services delivering AWS infrastructure and services to virtually any on-premises or edge location for a truly consistent hybrid experience. Now, AWS Outposts is available in a variety of form factors, from 1U and 2U Outposts servers to 42U Outposts racks, and multiple rack deployments. Customers such as DISH, Fanduel, Morningstar, Philips, and others use Outposts in workloads requiring low latency access to on-premises systems, local data processing, data residency, and application migration with local system interdependencies.
• Best price performance for ML workloads (2019) – We launched Amazon EC2 Inf1 instances powered by the first generation of AWS Inferentia chips designed to provide fast, low-latency inferencing. In 2022, we launched Amazon EC2 Trn1 instances powered by the first generation of AWS Trainium chips optimized for high performance AI training. Last year, we launched Amazon EC2 Trn3 UltraServers powered by Trainium3 to deliver the best token economics for next-generation generative AI applications. Customers such as Anthropic, Decart, poolside, Databricks, Ricoh, Karakuri, SplashMusic, and others are realizing performance and cost benefits of Trainium-based instances and UltraServers.
• Build your generative AI apps on AWS (2023) – Amazon Bedrock is a fully managed service that offers a choice of industry leading AI models along with a broad set of capabilities that you need to build generative AI applications, simplifying development with security, privacy, and responsible AI. Last year, we introduced Amazon Bedrock AgentCore, an agentic platform for building, deploying, and operating effective agents securely at scale. Now, more than 100,000 customers worldwide choose Amazon Bedrock to deliver personalized experiences, automate complex workflows, and uncover actionable insights.
• Your AI coding companion (2023) – We launched Amazon CodeWhisperer as the industry’s first cloud-based AI coding assistant service. The service delivered code generation from comments, open-source code reference tracking, and vulnerability scanning capabilities. In 2024, we rebranded the service to Amazon Q Developer and expanded its features to include a chat-based assistant in the console, project-based code generation, and code transformation tools. In 2025, this service evolved into Kiro, a new agentic AI development tool that brings structure to AI coding through spec-driven development, taking projects from prototype to production. Recently, Kiro previewed an autonomous agent, a frontier agent that works independently on development tasks, maintaining context and learning from every interaction.
• Broaden your AI model choices (2024) – We launched Amazon Titan models further increasing cost-effective AI model choice for text and multimodal needs in Amazon Bedrock. At AWS re:Invent 2024, we announced Amazon Nova models that delivers frontier intelligence and industry leading price performance. Now Amazon Nova has a portfolio of AI offerings—including Amazon Nova models, Amazon Nova Forge, a new service to build your own frontier models; and Amazon Nova Act, a new service to build agents that automate browser-based UI workflows powered by a custom Amazon Nova 2 Lite model.

Build with AI: Your path forward

A decade ago, AWS responded to the emergence of deep learning by launching the broadest and deepest ML services, such as Amazon SageMaker, democratizing AI for a wide range of customers—from individual developers and startups to large enterprises—regardless of their technical expertise.

AI technology has advanced significantly, but building and deploying AI models and applications still remains complex for many developers and organizations. AWS offers the broadest selection of AI models through Amazon Bedrock, including leading providers such as Anthropic and OpenAI. By using our model training and inference infrastructure and responsible AI both practical and scalable, you can accelerate trusted AI innovation while maintaining control of your data and costs—all built on our global infrastructure’s operational excellence.

Reinvent your idea, keep on learning, build confidently with AI you can trust, and share your successes with us! New AWS customers receive up to $200 in credits to try AWS AI for free. If you’re a student, start building with Kiro for free using 1,000 credits per month for one year.

— Channy

The post 20 years in the AWS Cloud – how time flies! appeared first on The NOKIA Blog.

Today, we’re announcing the ability to access your data in Amazon FSx for NetApp ONTAP file systems using Amazon Simple Storage Service (Amazon S3). With this capability, you can use your enterprise file data to augment generative AI applications with Amazon Bedrock Knowledge Bases for Retrieval Augmented Generation (RAG), train machine learning (ML) models with Amazon SageMaker, generate insights with Amazon S3 integrated third-party services, use comprehensive research capabilities in AI-powered business intelligence (BI) tools such as Amazon Quick Suite, and run analyses using Amazon S3 based cloud-native applications, all while your file data continues to reside in your FSx for NetApp ONTAP file system.

Amazon FSx for NetApp ONTAP is the first and only fully AWS managed NetApp ONTAP file system in the cloud to migrate on-premises applications that rely on NetApp ONTAP or other network-attached storage (NAS) appliances to AWS without having to change how you manage your data. FSx for NetApp ONTAP provides the popular capabilities, high performance, and data management APIs of ONTAP file systems with the added benefits of the AWS Cloud, such as simplified management, on-demand scaling, and seamless integration with other AWS services.

Over the years, AWS has developed a broad range of industry-leading AI, ML, and analytics services and applications that work with data in Amazon S3 that organizations use to innovate faster, discover new insights, and make even better data-driven decisions. However, some organizations want to use these services with their enterprise file data stored in NetApp ONTAP or other NAS appliances.

How to get started

You can create and attach an S3 Access Point to your FSx for ONTAP file system using the Amazon FSx console, the AWS Command Line Interface (AWS CLI), or the AWS SDK.

I have an existing FSx for ONTAP file system demo-create-s3access which I created by following the steps in the Creating file systems in the FSx for ONTAP documentation. Using the Amazon FSx console I now choose the file system ID fs-0c45b011a7f071d70 to access the full details of the file system.

I’ll attach the access point to the volume of the file system. I choose the volume vol1 and then select Create S3 Access Point from the Actions dropdown menu.

I enter details such as the access point name, the type of file system user identity and the network configuration, then choose Create s3 Access Point to finalize the process.

After it’s created, the access point my-s3-accesspoint is ready to allow access to the file data stored in my file system demo-create-s3access from Amazon S3. Amazon Access Points are S3 endpoints that can be attached to Amazon FSx volumes and used to perform Amazon S3 object operations.

I can now bring proprietary data stored in the file system demo-create-s3access to Amazon S3 for use in applications that work with Amazon S3 while my file data continues to reside in the FSx for NetApp ONTAP file system using the access point my-s3-accesspoint (this data remains accessible through the file protocols).

For the walkthrough in this post, I’ll integrate with Quick Suite.

Integrating decades of enterprise file data with the latest AI powered BI tools on AWS

In the Quick Suite Console, in the left navigation pane, I choose Connections, then select Integrations. Before you begin, make sure that you have the correct permissions to the Amazon S3 AWS resource. You can control the AWS resources that Quick Suite can access by following the Amazon Quick Suite user guide.

After I’ve selected the Amazon S3 integration I enter my Amazon S3 Access Point alias as the S3 bucket URL, leave the rest of the information as default, then choose Create and continue.

I finalize the process by providing the Name of the knowledge base, the Description, then choose Create.

After the knowledge base has been created it’s automatically synchronized, it’s now available for interaction.

I want to learn more about the AWS European Sovereign Cloud so I’ve updated the file system (accessed through the S3 Access Point my-s3-accesspoin-iyytkgz83djdjj7abn3u711supfgkuse1b-ext-s3alias) with the AWS whitepaper on this topic. In the chat in Amazon Quick Suite. I start asking the first question “do we have any documentation on the europe sovereignty cloud?“. To answer my question, the chat agent accesses and analyzes various types of data sources I have permission to use, including uploaded files in my current conversation, spaces I have access to, knowledge bases from my integrations, and more.

When I verify the source, I see that the document I uploaded to my file system is listed as one of the sources.

Other use cases of Amazon S3 Access Points for Amazon FSx for NetApp ONTAP

Earlier, we looked at use cases such as connecting an organization’s proprietary file data to Amazon Quick Suite for advanced business intelligence. Additionally, Amazon S3 Access Points for Amazon FSx for NetApp ONTAP can be used to seamlessly integrate enterprise file data with comprehensive analytics services, such as Amazon Athena for serverless SQL queries or AWS Glue for ETL processing, to name a few.

Amazon S3 Access Points for Amazon FSx for NetApp ONTAP are also suitable for data access from serverless compute workloads that are cloud-native with containerized microservices that require flexible access to shared enterprise datasets, such as configuration files, reference data, content libraries, model artifacts, and application assets.

Now available

You can get started today using the Amazon FSx console, AWS CLI, or AWS SDK to attach Amazon S3 Access Points to your Amazon FSx for NetApp ONTAP file systems. The feature is available in the following AWS Regions: Africa (Cape Town), Asia Pacific (Hong Kong, Hyderabad, Jakarta, Melbourne, Mumbai, Osaka, Seoul, Singapore, Sydney, Tokyo), Canada (Central, Calgary), Europe (Frankfurt, Ireland, London, Milan, Paris, Spain, Stockholm, Zurich), Israel (Tel Aviv), Middle East (Bahrain, UAE), South America (Sao Paulo), US East (N. Virginia, Ohio), and US West (N. California Oregon). You’re billed by Amazon S3 for the requests and data transfer costs through your S3 Access Point, in addition to your standard Amazon FSx charges. Learn more on the Amazon FSx for NetApp ONTAP pricing page.

PS: Writing a blog post at AWS is always a team effort, even when you see only one name under the post title. In this case, I want to thank Luke Miller, for his expertise and generous help with technical guidance, which made this overview possible and comprehensive.

– Veliswa Boya.

The post Amazon FSx for NetApp ONTAP now integrates with Amazon S3 for seamless data access appeared first on The NOKIA Blog.

Last week I met Jeff Barr at the AWS Shenzhen Community Day. Jeff shared stories about how builders around the world are experimenting with generative AI and encouraged local developers to keep pushing ideas into real prototypes. Many attendees stayed after the sessions to discuss model grounding, evaluation, and how to bring generative AI into real applications.

Community builders showcased creative Kiro-themed demos, AI-powered IoT projects, and student-led experiments. It was inspiring to see new developers, students, and long-time Amazon Web Services (AWS) community leaders connecting over shared curiosity and excitement for generative AI innovation.

Project Rainier, one of the world’s most powerful operational AI supercomputers is now online. Built by AWS in close collaboration with Anthropic, Project Rainier brings nearly 500,000 AWS custom-designed Trainium2 chips into service using a new Amazon Elastic Compute (Amazon EC2) UltraServer and EC2 UltraCluster architecture designed for high-bandwidth, low-latency model training at hyperscale.

Anthropic is already training and running inference for Claude on Project Rainier, and is expected to scale to more than one million Trainium2 chips across direct usage and Amazon Bedrock by the end of 2025. For architecture details, deployment insights, and behind-the-scenes video of an UltraServer coming online, refer to AWS activates Project Rainier for the full announcement.

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

• Amazon Nova – Adds Web Grounding as a new built-in tool for real-time, citation-based web retrieval, and introduces Multimodal Embeddings, a state-of-the-art model that produces unified cross-modal vectors, improving accuracy for Retrieval Augmented Generation (RAG) and semantic search. Both capabilities are available in Amazon Bedrock.
• Amazon Bedrock – TwelveLabs’ Marengo Embed 3.0 is now available for long-form, video-native multimodal embeddings across video, images, audio, and text with improved domain accuracy. Stability AI Image Services added four new tools: Outpaint, Fast Upscale, Conservative Upscale, and Creative Upscale for high-resolution upscaling, outpainting, and controlled variations.
• Model Context Protocol (MCP) Proxy for AWS – Now generally available as a client-side proxy that connects MCP clients to remote AWS hosted MCP servers using SigV4 authentication. It works with tools like Amazon Q Developer CLI, Kiro, Cursor, and Strands Agents, and provides safety controls such as read-only mode, retry logic, and logging. The Proxy is open-source. You can visit the AWS GitHub repository to view the installation and configuration options and start connecting with remote AWS MCP servers.
• Amazon Elastic Container Service (Amazon ECS) – Now supports built-in linear and canary deployment strategies, providing gradual traffic shifting, canary testing with small production slices, deployment bake times for safe rollback, and Amazon CloudWatch alarm-based automated rollbacks.
• Amazon DocumentDB – Adds a new query planner in Amazon DocumentDB 5.0 that delivers up to 10 times faster query performance with more optimal index plans and support for $neq, $nin, and nested $elementMatch, and can be enabled through cluster parameter groups without downtime.
• Amazon Elastic Block Store (Amazon EBS) – You can now use new per-volume CloudWatch metrics, VolumeAvgIOPS and VolumeAvgThroughput, to get minute-level visibility into average IOPS and throughput for EBS volumes on AWS Nitro based instances. These metrics help monitor performance trends, troubleshoot bottlenecks, and optimize provisioned capacity.
• Amazon Kinesis Data Streams – You can now send individual records up to 10 MiB, a tenfold increase from the previous limit, helping support larger Internet of Things (IoT), change data capture (CDC), and AI-generated payloads.
  Amazon SageMaker – Unified Studio search results now provide additional search context, showing matched metadata fields and ranking rationale to improve transparency and relevance in data discovery.

Additional updates
Here are some additional projects, blog posts, and news items that I found interesting:

• Building production-ready 3D pipelines with AWS VAMS and 4D Pipeline – A reference architecture for creating scalable, cloud-based 3D asset pipelines using AWS Visual Asset Management System (VAMS) and 4D Pipeline, supporting ingest, validation, collaborative review, and distribution across games, visual effects (VFX), and digital twins.
• Amazon Location Service introduces new API key restrictions – You can now create granular security policies with bundle IDs to restrict API access to specific mobile applications, improving access control and strengthening application-level security across location-based workloads.
• AWS Clean Rooms launches advanced SQL configurations – A performance enhancement for Spark SQL workloads that supports runtime customization of Spark properties and compute sizes, plus table caching for faster and more cost-efficient processing of large analytical queries.
• AWS Serverless MCP Server adds event source mappings (ESM) tools – A capability for event-driven serverless applications that supports configuration, performance tuning, and troubleshooting of AWS Lambda event source mappings, including AWS Serverless Application Model (AWS SAM) template generation and diagnostic insights.
• AWS IoT Greengrass releases an AI agent context pack – A development accelerator for cloud-connected edge applications that provides ready-to-use instructions, examples, and templates, helping teams integrate generative AI tools such as Amazon Q for faster software creation, testing, and fleet-wide deployment. It’s available as open source on the GitHub repository.
• AWS Step Functions introduces a new metrics dashboard – You can now view usage, billing, and performance metrics at the state-machine level for standard and express workflows in a single console view, improving visibility and troubleshooting for distributed applications.

Upcoming AWS events
Check your calendars so that you can sign up for these upcoming events:

• AWS Builder Loft – A community tech space in San Francisco where you can learn from expert sessions, join hands-on workshops, explore AI and emerging technologies, and collaborate with other builders to accelerate their ideas. Browse the upcoming sessions and join the events that interest you.
• AWS Community Days – Join community-led conferences that feature technical discussions, workshops, and hands-on labs led by experienced AWS users and industry leaders from around the world: Hong Kong (November 2), Abuja (November 8), Cameroon (November 8), and Spain (November 15).
• AWS Skills Center Seattle 4th Anniversary Celebration – A free, public event on November 20 with a keynote, learned panels, recruiter insights, raffles, and virtual participation options.

Join the AWS Builder Center to learn, build, and connect with builders in the AWS community. Browse here for upcoming in-person events, developer-focused events, and events for startups.

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

– Betty

The post AWS Weekly Roundup: Project Rainier online, Amazon Nova, Amazon Bedrock, and more (November 3, 2025) appeared first on The NOKIA Blog.

Amazon Prime Day 2025 was the biggest Amazon Prime Day shopping event ever, setting records for both sales volume and total items sold during the 4-day event. Prime members saved billions while shopping Amazon’s millions of deals during the event.

This year marked a significant transformation in the Prime Day experience through advancements in the generative AI offerings from Amazon and AWS. Customers used Alexa+—the Amazon next-generation personal assistant now available in early access to millions of customers—along with the AI-powered shopping assistant, Rufus, and AI Shopping Guides. These features, built on more than 15 years of cloud innovation and machine learning expertise from AWS, combined with deep retail and consumer experience from Amazon, helped customers quickly discover deals and get product information, complementing the fast, free delivery that Prime members enjoy year-round.

As part of our annual tradition to tell you about how AWS powered Prime Day for record-breaking sales, I want to share the services and chart-topping metrics from AWS that made your amazing shopping experience possible.

Prime Day 2025 – all the numbers
During the weeks leading up to big shopping events like Prime Day, Amazon fulfillment centers and delivery stations work to get ready and ensure operations run efficiently and safely. For example, the Amazon automated storage and retrieval system (ASRS) operates a global fleet of industrial mobile robots that move goods around Amazon fulfillment centers.

AWS Outposts, a fully managed service that extends the AWS experience on-premises, powers software applications that manage the command-and-control of Amazon ASRS and supports same-day and next-day deliveries through low-latency processing of critical robotic commands.

During Prime Day 2025, AWS Outposts at one of the largest Amazon fulfillment centers sent more than 524 million commands to over 7,000 robots, reaching peak volumes of 8 million commands per hour—a 160 percent increase compared to Prime Day 2024.

Here are some more interesting, mind-blowing metrics:

• Amazon Elastic Compute Cloud (Amazon EC2) – During Prime Day 2025, AWS Graviton, a family of processors designed to deliver the best price performance for cloud workloads running in Amazon EC2, powered more than 40 percent of the Amazon EC2 compute used by Amazon.com. Amazon also deployed over 87,000 AWS Inferentia and AWS Trainium chips – custom silicon chips for deep learning and generative AI training and inference – to power Amazon Rufus for Prime Day.
• Amazon SageMaker AI — Amazon SageMaker AI, a fully managed service that brings together a broad set of tools to enable high-performance, low-cost machine learning (ML), processed more than 626 billion inference requests during Prime Day 2025.
• Amazon Elastic Container Service (Amazon ECS) and AWS Fargate– Amazon Elastic Container Service (Amazon ECS) is a fully managed container orchestration service that works seamlessly with AWS Fargate, a serverless compute engine for containers. During Prime Day 2025, Amazon ECS launched an average of 18.4 million tasks per day on AWS Fargate, representing a 77 percent increase from the previous year’s Prime Day average.
• AWS Fault Injection Service (AWS FIS) – We ran over 6,800 AWS FIS experiments—over eight times more than we conducted in 2024—to test resilience and ensure Amazon.com remains highly available on Prime Day. This significant increase was made possible by two improvements: new Amazon ECS support for network fault injection experiments on AWS Fargate, and the integration of FIS testing in continuous integration and continuous delivery (CI/CD) pipelines.
• AWS Lambda – AWS Lambda, a serverless compute service that lets you run code without managing infrastructure, handled over 1.7 trillion invocations per day during Prime Day 2025.
• Amazon API Gateway – During Prime Day 2025, Amazon API Gateway, a fully managed service that makes it easy to create, maintain, and secure APIs at any scale, processed over 1 trillion internal service requests—a 30 percent increase in requests on average per day compared to Prime Day 2024.
• Amazon CloudFront – Amazon CloudFront, a content delivery network (CDN) service that securely delivers content with low latency and high transfer speeds, delivered over 3 trillion HTTP requests during the global week of Prime Day 2025, a 43 percent increase in requests compared to Prime Day 2024.
• Amazon Elastic Block Store (Amazon EBS) – During Prime Day 2025, Amazon EBS, our high-performance block storage service, peaked at 20.3 trillion I/O operations, moving up to an exabyte of data daily.
• 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 500 billion transactions, stored 4,071 terabytes of data, and transferred 999 terabytes of data.
• 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, these sources made tens of trillions of calls to the DynamoDB API. DynamoDB maintained high availability while delivering single-digit millisecond responses and peaking at 151 million requests per second.
• Amazon ElastiCache – During Prime Day, Amazon ElastiCache, a fully managed caching service delivering microsecond latency, peaked at serving over 1.5 quadrillion daily requests and over 1.4 trillion requests in a minute.
• Amazon Kinesis Data Streams – Amazon Kinesis Data Streams, a fully managed serverless data streaming service, processed a peak of 807 million records per second during Prime Day 2025.
• Amazon Simple Queue Service (Amazon SQS) – During Prime Day 2025, Amazon SQS – a fully managed message queuing service for microservices, distributed systems, and serverless applications – set a new peak traffic record of 166 million messages per second.
• Amazon GuardDuty – During Prime Day 2025, Amazon GuardDuty, an intelligent threat detection service, monitored an average of 8.9 trillion log events per hour, a 48.9 percent increase from last year’s Prime Day.
• AWS CloudTrail – AWS CloudTrail, which tracks user activity and API usage on AWS, as well as in hybrid and multicloud environments, processed over 2.5 trillion events during Prime Day 2025, compared to 976 billion events in 2024.

Prepare to scale
If you’re preparing for similar business-critical events, product launches, and migrations, I recommend that you take advantage of our newly branded AWS Countdown (formerly known as AWS Infrastructure Event Management, or IEM). This comprehensive support program helps assess operational readiness, identify and mitigate risks, and plan capacity, using proven playbooks developed by AWS experts. We’ve expanded to include: generative AI implementation support to help you confidently launch and scale AI initiatives; migration and modernization support, including mainframe modernization; and infrastructure optimization for specialized sectors including election systems, retail operations, healthcare services, and sports and gaming events.

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

— Channy

The post AWS services scale to new heights for Prime Day 2025: key metrics and milestones appeared first on The NOKIA Blog.

Starting today, you can use enhanced logging capability in Amazon EventBridge to monitor and debug your event-driven applications with comprehensive logs. These new enhancements help improve how you monitor and troubleshoot event flows.

Here’s how you can find this new capability on the Amazon EventBridge console:

The new observability capabilities address microservices and event-driven architecture monitoring challenges by providing comprehensive event lifecycle tracking. EventBridge now generates detailed log entries every time a matched event against rules is published, delivered to subscribers, or encounters failures and retries.

You gain visibility into the complete event journey with detailed information about successes, failures, and status codes that make identifying and diagnosing issues straightforward. What used to take hours of trial-and-error debugging now takes minutes with detailed event lifecycle tracking and built-in query tools.

Using Amazon EventBridge enhanced observability
Let me walk you through a demonstration that showcases the logging capability in Amazon EventBridge.

I can enable logging for an existing event bus or when creating a new custom event bus. First, I navigate to the EventBridge console and choose Event buses in the left navigation pane. In Custom event bus, I choose Create event bus.

I can see this new capability in the Logs section. I have three options to configure the Log destination: Amazon CloudWatch Logs, Amazon Data Firehose Stream, and Amazon Simple Storage Service (Amazon S3). If I want to stream my logs into a data lake, I can select Amazon Kinesis Data Firehose Stream. Logs are encrypted in transit with TLS and at rest if a customer-managed key (CMK) is provided for the event bus. CloudWatch Logs supports customer-managed keys, and Data Firehose offers server-side encryption for downstream destinations.

For this demo, I select CloudWatch logs and S3 logs.

I can also choose Log level, from Error, Info, or Trace. I choose Trace and select Include execution data because I need to review the payloads. You need to be mindful as logging payload data may contain sensitive information, and this setting applies to all log destinations you select. Then, I configure two destinations, one each for CloudWatch log group and S3 logs. Then I choose Create.

After logging is enabled, I can start publishing test events to observe the logging behavior.

For the first scenario, I’ve built an AWS Lambda function and configured this Lambda function as a target.

I navigate to my event bus to send a sample event by choosing Send events.

Here’s the payload that I use:

{
  "Source": "ecommerce.orders",
  "DetailType": "Order Placed",
  "Detail": {
    "orderId": "12345",
    "customerId": "cust-789",
    "amount": 99.99,
    "items": [
      {
        "productId": "prod-456",
        "quantity": 2,
        "price": 49.99
      }
    ]
  }
}

After I sent the sample event, I can see the logs are available in my S3 bucket.

I can also see the log entries appearing in the Amazon CloudWatch logs. The logs show the event lifecycle, from EVENT_RECEIPT to SUCCESS. Learn more about the complete event lifecycle on What Amazon EventBridge logs for event buses documentation page.

Now, let’s evaluate these logs. For brevity, I only include a few logs and have redacted them for readability. Here’s the log from when I triggered the event:

{
    "resource_arn": "arn:aws:events:us-east-1:123:event-bus/demo-logging",
    "message_timestamp_ms": 1751608776896,
    "event_bus_name": "demo-logging",
// REDACTED FOR BREVITY //
    "message_type": "EVENT_RECEIPT",
    "log_level": "TRACE",
    "details": {
        "caller_account_id": "123",
        "source_time_ms": 1751608775000,
        "source": "ecommerce.orders",
        "detail_type": "Order Placed",
        "resources": [],
        "event_detail": "REDACTED FOR BREVITY"
    }
}

Here’s the log when the event was successfully invoked:

{
    "resource_arn": "arn:aws:events:us-east-1:123:event-bus/demo-logging",
    "message_timestamp_ms": 1751608777091,
    "event_bus_name": "demo-logging",
// REDACTED FOR BREVITY //
    "message_type": "INVOCATION_SUCCESS",
    "log_level": "INFO",
    "details": {
// REDACTED FOR BREVITY //
        "total_attempts": 1,
        "final_invocation_status": "SUCCESS",
        "ingestion_to_start_latency_ms": 105,
        "ingestion_to_complete_latency_ms": 183,
        "ingestion_to_success_latency_ms": 183,
        "target_duration_ms": 53,
        "target_response_body": "<REDACTED FOR BREVITY>",
        "http_status_code": 202
    }
}

The additional log entries include rich metadata that makes troubleshooting straightforward. For example, on a successful event, I can see the latency timing from starting to completing the event, duration for the target to finish processing, and HTTP status code.

Debugging failures with complete event lifecycle tracking
The benefit of EventBridge logging becomes apparent when things go wrong. To test failure scenarios, I intentionally misconfigure a Lambda function’s permissions and change the rule to point to a different Lambda function without proper permissions.

The attempt failed with a permanent failure due to missing permissions. The log shows it’s a FIRST attempt that resulted in NO_PERMISSIONS status.

{
    "message_type": "INVOCATION_ATTEMPT_PERMANENT_FAILURE",
    "log_level": "ERROR",
    "details": {
        "rule_arn": "arn:aws:events:us-east-1:123:rule/demo-logging/demo-order-placed",
        "role_arn": "arn:aws:iam::123:role/service-role/Amazon_EventBridge_Invoke_Lambda_123",
        "target_arn": "arn:aws:lambda:us-east-1:123:function:demo-evb-fail",
        "attempt_type": "FIRST",
        "attempt_count": 1,
        "invocation_status": "NO_PERMISSIONS",
        "target_duration_ms": 25,
        "target_response_body": "{"requestId":"a4bdfdc9-4806-4f3e-9961-31559cb2db62","errorCode":"AccessDeniedException","errorType":"Client","errorMessage":"User: arn:aws:sts::123:assumed-role/Amazon_EventBridge_Invoke_Lambda_123/db4bff0a7e8539c4b12579ae111a3b0b is not authorized to perform: lambda:InvokeFunction on resource: arn:aws:lambda:us-east-1:123:function:demo-evb-fail because no identity-based policy allows the lambda:InvokeFunction action","statusCode":403}",
        "http_status_code": 403
    }
}

The final log entry summarizes the complete failure with timing metrics and the exact error message.

{
    "message_type": "INVOCATION_FAILURE",
    "log_level": "ERROR",
    "details": {
        "rule_arn": "arn:aws:events:us-east-1:123:rule/demo-logging/demo-order-placed",
        "role_arn": "arn:aws:iam::123:role/service-role/Amazon_EventBridge_Invoke_Lambda_123",
        "target_arn": "arn:aws:lambda:us-east-1:123:function:demo-evb-fail",
        "total_attempts": 1,
        "final_invocation_status": "NO_PERMISSIONS",
        "ingestion_to_start_latency_ms": 62,
        "ingestion_to_complete_latency_ms": 114,
        "target_duration_ms": 25,
        "http_status_code": 403
    },
    "error": {
        "http_status_code": 403,
        "error_message": "User: arn:aws:sts::123:assumed-role/Amazon_EventBridge_Invoke_Lambda_123/db4bff0a7e8539c4b12579ae111a3b0b is not authorized to perform: lambda:InvokeFunction on resource: arn:aws:lambda:us-east-1:123:function:demo-evb-fail because no identity-based policy allows the lambda:InvokeFunction action",
        "aws_service": "AWSLambda",
        "request_id": "a4bdfdc9-4806-4f3e-9961-31559cb2db62"
    }
}

The logs provide detailed performance metrics that help identify bottlenecks. The ingestion_to_start_latency_ms: 62 shows the time from event ingestion to starting invocation, while ingestion_to_complete_latency_ms: 114 represents the total time from ingestion to completion. Additionally, target_duration_ms: 25 indicates how long the target service took to respond, helping distinguish between EventBridge processing time and target service performance.

The error message clearly states what failed, lambda:InvokeFunction action, why it failed, (no identity-based policy allows the action), which role was involved (Amazon_EventBridge_Invoke_Lambda_1428392416), and which specific resource was affected, which was indicated by the Lambda function Amazon Resource Name (ARN).

Debugging API Destinations with EventBridge Logging
One particular use case that I think EventBridge logging capability will be helpful is to debug issues with API destinations. EventBridge API destinations are HTTPS endpoints that you can invoke as the target of an event bus rule or pipe. HTTPS endpoints help you to route events from your event bus to external systems, software-as-a-service (SaaS) applications, or third-party APIs using HTTPS calls. They use connections to handle authentication and credentials, making it easy to integrate your event-driven architecture with any HTTPS-based service. 

API destinations are commonly used to send events to external HTTPS endpoints and debugging failures from the external endpoint can be a challenge. These problems typically stem from changes to the endpoint authentication requirements or modified credentials.

To demonstrate this debugging capability, I intentionally configured an API destination with incorrect credentials in the connection resource.

When I send an event to this misconfigured endpoint, the enhanced logging shows the root cause of this failure.

{
    "resource_arn": "arn:aws:events:us-east-1:123:event-bus/demo-logging",
    "message_timestamp_ms": 1750344097251,
    "event_bus_name": "demo-logging",
    //REDACTED FOR BREVITY//,
    "message_type": "INVOCATION_FAILURE",
    "log_level": "ERROR",
    "details": {
        //REDACTED FOR BREVITY//,
        "total_attempts": 1,
        "final_invocation_status": "SDK_CLIENT_ERROR",
        "ingestion_to_start_latency_ms": 135,
        "ingestion_to_complete_latency_ms": 549,
        "target_duration_ms": 327,
        "target_response_body": "",
        "http_status_code": 400
    },
    "error": {
        "http_status_code": 400,
        "error_message": "Unable to invoke ApiDestination endpoint: The request failed because the credentials included for the connection are not authorized for the API destination."
    }
}

The log provides immediate clarity about the failure. The target_arn shows this involves an API destination, the final_invocation_status indicates SDK_CLIENT_ERROR, and the http_status_code of 400 , which points to a client-side issue. Most importantly, the error_message explicitly states that: Unable to invoke ApiDestination endpoint: The request failed because the credentials included for the connection are not authorized for the API destination.

This complete log sequence provides useful debugging insights because I can see exactly how the event moved through EventBridge — from event receipt, to ingestion, to rule matching, to invocation attempts. This level of detail eliminates guesswork and points directly to the root cause of the issue.

Additional things to know
Here are a couple of things to note:

• Architecture support – Logging works with all EventBridge features including custom event buses, partner event sources, and API destinations for HTTPS endpoints.
• Performance impact – Logging operates asynchronously with no measurable impact on event processing latency or throughput.
• Pricing – You pay standard Amazon S3, Amazon CloudWatch Logs or Amazon Data Firehose pricing for log storage and delivery. EventBridge logging itself incurs no additional charges. For details, visit the Amazon EventBridge pricing page .
• Availability – Amazon EventBridge logging capability is available in all AWS Regions where EventBridge is supported.
• Documentation — For more details, refer to the Amazon EventBridge monitoring and debugging Documentation.

Get started with Amazon EventBridge logging capability by visiting the EventBridge console and enabling logging on your event buses.

Happy building!
— Donnie 

The post Monitor and debug event-driven applications with new Amazon EventBridge logging appeared first on The NOKIA Blog.

I counted about 40 new launches from AWS since last week – back to our normal rhythm of releases. Services teams are listening to your feedback and developing little (or big) changes that makes your life easier when working with our services. The ability to support multiple sessions in the AWS Console is my favorite one so far in 2025.

But our teams didn’t stop there, let’s look at the last week’s new announcements.

Last week’s launches

Beside the usual Regional expansion (new capabilities that are now available in a new Region), here are the launches that got my attention.

Amazon EventBridge announces direct delivery to cross-account targets – Amazon EventBridge is now able to deliver events to targets in another AWS account directly without having to send them to the default bus in the target account first. This will simplify so many architectures out there! It supports any target that supports resource-based policies, including AWS Lambda, Amazon Simple Queue Service (Amazon SQS), Amazon Simple Notification Service (Amazon SNS), Amazon Kinesis, and Amazon API Gateway.

Amazon Corretto quaterly update – We announced quarterly security and critical updates for Amazon Corretto Long-Term Supported (LTS) and Feature Release (FR) versions of OpenJDK. Corretto 23.0.2, 21.0.6, 17.0.14, 11.0.26, 8u442 are now available for download. Amazon Corretto is a no-cost, multi-platform, production-ready distribution of OpenJDK. You can download the updates from the Corretto home page or just type apt-get or yum update.

High-throughput mode for Amazon SNS FIFO Topics – Amazon SNS now supports high-throughput mode for SNS FIFO topics, with default throughput matching SNS standard topics across all Regions. When you enable high-throughput mode, SNS FIFO topics will maintain order within message group, while reducing the deduplication scope to the message-group level. With this change, you can leverage up to 30K messages per second (MPS) per account by default in US East (N. Virginia) Region, and 9K MPS per account in US West (Oregon) and Europe (Ireland) Regions, and request quota increases for additional throughput in any Region.

Amazon Connect agent workspace now supports audio optimization for Citrix and Amazon WorkSpaces virtual desktops – Amazon Connect agent workspace now supports the ability to redirect audio from Citrix and Amazon WorkSpaces Virtual Desktop Infrastructure (VDI) environments to a customer service agent’s local device. Audio redirection improves voice quality and reduces latency for voice calls handled on virtual desktops, providing a better experience for both end customers and agents.

Amazon Redshift announces support for History Mode for zero-ETL integrations – This new capability enables you to build Type 2 Slowly Changing Dimension (SCD 2) tables on your historical data from databases, out-of-the-box in Amazon Redshift, without writing any code. History mode simplifies the process of tracking and analyzing historical data changes, allowing you to gain valuable insights from your data’s evolution over time.

Finally, Amazon Bedrock has its own set of announcements. First, for anyone investing in retrieval-augmented generation, Bedrock now support multimodal content with Cohere Embed 3 Multilingual and Embed 3 English models. This enables you to create embeddings to not only index text, but also images.

Second, read Luma AI’s Ray2 visual AI model now available in Amazon Bedrock. Luma Ray2 is a large-scale video-generation model capable of creating realistic visuals with fluid, natural movement. With Luma Ray2 in Amazon Bedrock, you can generate production-ready video clips with seamless animations, ultrarealistic details, and logical event sequences with natural language prompts, removing the need for technical prompt engineering. Ray2 currently supports 5- and 9-second video generations with 540p and 720p resolution.

And finally, Amazon Bedrock Flows announces preview of multi-turn conversation support. Amazon Bedrock Flows enables you to link foundation models (FMs), Amazon Bedrock Prompts, Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, Amazon Bedrock Guardrails and other AWS services together to build and scale pre-defined generative AI workflows. This week, the team announced preview of multi-turn conversation support for agent nodes in Flows. This capability enables dynamic, back-and-forth conversations between users and flows, similar to a natural dialogue.

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

Other AWS events
Check your calendar and sign up for upcoming AWS events.

AWS Summits season is starting! I’m already working with the local team to prepare content for the Summits in Paris and London. Summits are free online and in-person events that bring the cloud computing community together to connect, collaborate, and learn about AWS. Stay updated by visiting the official AWS Summit website and sign up for notifications to learn when registration opens for events in your area.

AWS GenAI Lofts are collaborative spaces and immersive experiences that showcase AWS expertise in cloud computing and AI. They provide startups and developers with hands-on access to AI products and services, exclusive sessions with industry leaders, and valuable networking opportunities with investors and peers. Find a GenAI Loft location near you, and don’t forget to register.

Browse all upcoming AWS led in-person and virtual events here.

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

— seb

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: EventBridge, SNS FIFO, Amazon Corretto, Amazon Connect, Amazon Bedrock, and more appeared first on The NOKIA Blog.

Happy New Year! We are witnessing technology augment human ingenuity in inspiring ways. In the coming years, using technology for positive impact will redefine the way we think about success. Amazon CTO, Dr. Werner Vogels, offers five forward-looking tech predictions for 2025, and beyond:

• The workforce of tomorrow is mission-driven
• A new era of energy efficiency drives innovation
• Technology tips the scales in the discovery of truth
• Open data drives decentralized disaster preparedness
• Intention-driven consumer technology takes hold

Download the Werner Vogels’ Tech Predictions for 2025 and Beyond ebook, or read Werner’s All Things Distributed blog to learn more about how these technological trends are shaping our world and paving the way for a more innovative, efficient, and purposeful future.

AWS re:Invent 2025 videos and re:Caps
If you’re looking to catch up on re:Invent announcements or delve deeper into the latest AWS innovations, you have several options available:

Launches from the last few weeks
Since our last week in review on December 16, 2024, I’d like to highlight some launches from year end, as well as from last week:

Availability of Llama 3.3 70B in Amazon SageMaker JumpStart and in Amazon Bedrock – Meta’s Llama 3.3 70B represents a significant advancement in model efficiency and performance optimization. Llama 3.3 70B is a text-only instruction-tuned model that provides enhanced performance relative to Llama 3.1 70B and Llama 3.2 90B, when used for text-only applications. You can now use the model in both Amazon SageMaker JumpStart, as well as Amazon Bedrock.

Availability of Stable Diffusion 3.5 Large in Amazon Bedrock – Stable Diffusion 3.5 Large by Stability AI is the most powerful model in the Stable Diffusion family at 8.1 billion parameters trained on Amazon SageMaker HyperPod. You can now use Stable Diffusion 3.5 Large in Amazon Bedrock to generate high-quality images from text descriptions.

New Amazon Kinesis source connector for Apache Flink – The Apache Flink community has released version 5.0.0 of AWS services connectors, an AWS open source contribution. This release introduces the Kinesis Streams Source, a new connector for reading data from Amazon Kinesis Data Streams, replacing the previous Kinesis Consumer.

Support of AWS Global Accelerator in Amazon WorkSpaces Personal – Amazon WorkSpaces Personal now integrates with AWS Global Accelerator (AGA) to enhance WorkSpaces connection performance by optimizing streaming traffic through the AWS Global Network and edge locations. This feature particularly benefits customers whose end users connect to WorkSpaces across long distances. You can enable the AGA feature at either the WorkSpaces directory level or for individual WorkSpaces running Amazon DCV protocol.

New resource insights in AWS Resource Explorer – With the enhanced Resource Explorer experience, relevant data and insights from multiple AWS services is centralized for supported resource types. You can use the new features to take actions on resources directly from the Resource Explorer console, such as manage tags, add resources to applications, and get additional information about a resource with Amazon Q.

General availability of custom billing view in AWS Billing and Cost Management – Custom billing view allows you to provide application and business unit owners access to relevant cost management data across multiple AWS accounts using a single view in AWS Cost Explorer without granting access to the AWS management account. You can create filtered views of cost management data based on cost allocation tags or specific AWS accounts.

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

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

AWS at CES 2025 (January 7-10) – AWS will be representing some of the latest cloud services and solutions that are purpose built for the automotive, mobility, transportation, and manufacturing industries. Join us to learn about the latest cloud capabilities across generative AI, software define vehicles, product engineering, sustainability, new digital customer experiences, connected mobility, autonomous driving, and so much more, in Amazon Experience Area.

AWS at NRF 2025 (January 12-14) – Join AWS at the retail’s big show to see generative AI and cutting-edge technologies in action. Listen to innovative big ideas sessions, curated TechTalks, and experience the latest in retail trends, technologies, and more.

Amazon QuickSight Learning Series – Kick off your 2025 by supercharging your data skills. Join the online Learning Series in January to learn about the cutting-edge features of Amazon QuickSight unveiled at re:Invent 2024.

You can browse all upcoming in-person and virtual 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 Happy New Year! AWS Weekly Roundup: 2025 Tech Predictions, Llama 3.3 70B, Stable Diffusion 3.5 Large, custom billing view, and more (January 6, 2025) appeared first on The NOKIA Blog.

Happy 20th Anniversary of the AWS News Blog! 🎉🥳🎊 On November 9, 2004, Jeff Barr published his first blog post. At the time, he started a personal blog site using TypePad. He wanted to speak to his readers with his personal voice, not the company or team.

On April 29, 2014, we created a new AWS blog site and migrated all posts to that page. There are currently over 4,300 posts on the AWS News Blog, with Jeff contributing over 3,200 of them.

Since December 2016, the AWS News Blog has added new writers, but we are still following Jeff’s leadership principals for AWS News Bloggers in accordance with Day One. What’s unique about the AWS News Blog is that the blog writers get to use the features of the product team in advance, following the Customer Obsession leadership principle, and focus on walk-throughs of how customers can quickly use them to save time, with the Frugality principle.

I am very grateful for Jeff’s fundamental and pivotal role over the past 20 years, and I look forward to the next 20 years!

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

New Express brokers for Amazon MSK – Express brokers are a new broker type for Amazon MSK Provisioned designed to deliver up to three times more throughput per broker, scale up to 20 times faster, and reduce recovery time by 90 percent as compared to standard Apache Kafka brokers. Express brokers come preconfigured with Kafka best practices by default, support all Kafka APIs, and provide the same low-latency performance, so you can continue using existing client applications without any changes.

New Amazon Kinesis Client Library 3.0 – You can now reduce compute costs to process streaming data by up to 33 percent with Kinesis Client Library (KCL) 3.0, compared to previous KCL versions. KCL 3.0 introduces an enhanced load balancing algorithm that continuously monitors resource utilization of the stream processing workers and automatically redistributes the load from overutilized workers to other underutilized workers. To learn more, read the AWS Big Data Blog post.

Microsoft Windows Server 2025 images on Amazon EC2 – We now support Microsoft Windows Server 2025 with License Included (LI) Amazon Machine Images (AMIs), providing customers with an easy and flexible way to launch the latest version of Windows Server. By running Windows Server 2025 on Amazon EC2, customers can take advantage of the security, performance, and reliability of AWS with the latest Windows Server features. To learn more about running Windows Server 2025 on Amazon EC2, visit Windows Workloads on AWS.

Anthropic’s Claude 3.5 Haiku model in Amazon Bedrock – Claude 3.5 Haiku is the next generation of Anthropic’s fastest model, combining rapid response times with improved reasoning capabilities, making it ideal for tasks that require both speed and intelligence. Claude 3.5 Haiku improves across every skill set and surpasses even Claude 3 Opus, the largest model in Anthropic’s previous generation, on many intelligence benchmarks—including coding. To learn more, read the AWS News Blog post.

Amazon Bedrock Prompt Management GA – You can simplify the creation, testing, versioning, and sharing of prompts in Amazon Bedrock Prompt Management. At general availability, we added new features that provide enhanced options for configuring your prompts and enabling seamless integration for invoking them in your generative AI applications, such as structured prompts and Converse and InvokeModel API integration. To learn more, read the AWS Machine Learning blog post.

Six new synthetic generative voices for Amazon Polly – The generative engine is Amazon Polly’s most advanced text-to-speech (TTS) model leveraging the generative AI technology. We added six new synthetic female-sounding generative voices: Ayanda (South African English), Léa (French), Lucia (European Spanish), Lupe (American Spanish), Mía (Mexican Spanish), and Vicki (German). This extends thirteen voices and nine locales to provide you with more options of highly expressive and engaging voices.

Amazon OpenSearch Service Extended Support – We announce the end of Standard Support and Extended Support timelines for legacy Elasticsearch versions and OpenSearch Versions. Standard Support ends on Nov 7, 2025, for legacy Elasticsearch versions up to 6.7, Elasticsearch versions 7.1 through 7.8, OpenSearch versions from 1.0 through 1.2, and OpenSearch versions 2.3 through 2.9. With Extended Support, for an incremental flat fee over regular instance pricing, you continue to get critical security updates beyond the end of Standard Support. To learn more, read the AWS Big Data Blog post.

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

Other AWS news
Here are some additional news items that you might find interesting:

CEO’s visiting at AWS data center – Matt Garman, CEO of AWS, had a great time visiting one of our AWS data centers recently, and was able to get a look at the continuous innovation delivered by the team. Of course, it’s no surprise that Amazon’s senior executives visit fulfillment centers, contact centers, and data centers, to do real work for customers. AWS data centers are designed for customers in every aspect, for maximum resilience, performance, and energy efficiency.

AWS supports small businesses, creates jobs, sets up sustainability initiatives, and develops educational programs near AWS data centers. Get the latest updates – AWS in your community: Here’s what’s happening near data centers across the US on About Amazon News.

Amazon Q Business at Amazon – I introduced an Amazon story to use Code transformation in Amazon Q Developer to migrate more than old 30,000 Java applications to Java 17 version. It saved over 4,500 developer years of effort compared to previous manual jobs and saved the company $260 million in annual by moving to the latest Java version.

Here is another dogfooding story of Amazon Q Business at Amazon. Amazon built an internal chatbot with Amazon Q Business and it has resolved over 1 million internal Amazon developer questions, reducing time spent churning on manual technical investigations by more than 450,000 hours.

Our team onboarded Amazon Q Business with millions of internal documents and integrated Q Business into the tools our team use every day. Now, instead of waiting hours for responses to complex technical questions on Q&A boards or Slack channels, developers can get answers in seconds.

TOURCast at PGA TOUR – If you enjoy golf, this news will be of interest to you. The PGA TOUR debuted TOURCast in Japan at the 2024 ZOZO Championship to capture and disseminate better statistical data and bring fans closer to the game based on new scoring system called ShotLink, powered by CDW. This marks the first time the PGA TOUR has been able to bring this technology to Asia, leveraging the flexibility and scalability of AWS to overcome unique challenges.

PGA TOUR volunteer setting up GPS equipment on the fairway at ZOZO championship that will input specific shot data and feed back to Shotlink Select Plus. [IMAGE: PGA TOUR]

They’ve completely rebuilt their scoring system over the past two years on a new cloud stack. With AWS cloud, whether data comes from high-tech radar systems, cameras, or manual input, the system processes it all seamlessly.

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

AWS GenAI Lofts – AWS GenAI Lofts are about more than just the tech, they bring together startups, developers, investors, and industry experts. Whether you’re looking to gain deep insights, or get your questions answered by generative AI pros, our GenAI Lofts have you covered, and provide everything you need to start building your next innovation. Join events in São Paulo (through November 20), and Paris (through November 25).

AWS Community Days – Join community-led conferences that feature technical discussions, workshops, and hands-on labs led by expert AWS users and industry leaders from around the world: Jakarta, Indonesia (November 23), Kochi, India (December 14).

AWS re:Invent – You can still register for the annual learning event, taking place December 2–6 in Las Vegas. Surprisingly Andy Jassy, CEO of Amazon said he will come back and participate in AWS re:Invent this year. He said “As always, the priority is to make this a learning event so customers can take nuggets back and change their own customer experiences and businesses. We’ll also have a bunch of goodies for you that we’ll announce and that we think folks will like.” Let’s meet there!

You can browse all upcoming in-person and virtual events.

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

— Channy

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

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