Tag Archives: AWS

AWS Weekly Roundup: AWS Step Functions, AWS CloudFormation, Amazon Q Developer, and more (February 10, 2024)

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We are well settled into 2025 by now, but many people are still catching up with all the exciting new releases and announcements that came out of re:Invent last year. There have been hundreds of re:Invent recap events around the world since the beginning of the year, including in-person all-day official AWS events with multiple tracks to help you discover and dive deeper into the releases you care about, as well as community and virtual events.

Last month, I was lucky to be a co-host for AWS EMEA re:Invent re:Cap which was a nearly 4-hour livestream with experts featuring demos, whiteboard sessions, and a live Q&A. The good news is that you can now watch it on-demand! We had a great team and thousands of people enjoyed learning through the virtual experience. I recommend you check it out or share it with colleagues who have not been able to attend any re:Invent re:Cap events.

The Korean team also did an amazing job hosting their own virtual re:Invent re:Cap event, and it’s also now available on-demand. So if you speak Korean I do recommend you check it out.

If you’re more of a reader, then we have a treat for you. You can download the full official re:Invent re:Cap deck with all the slides covering releases across all areas by visiting community.aws! While there, you can also check all the upcoming in-person re:Invent re:Cap community events remaining across the globe for a chance to still attend one of those in a city near you.

But as we know, new releases, announcements, and updates don’t stop at re:Invent. Every week there are even more, and this is why we have this Weekly Roundup series that you can read every Monday to get the AWS news highlights from the week before.

So here’s what caught my attention last week.

Last week’s AWS Launches
If you use AWS Step Functions you may be interested in these:

Amazon Q Developer also got a couple of updates:

Here are some other releases that caught my attention this week from a variety of other AWS services:

AWS CloudFormation introduces stack refactoring – You can now split your CloudFormation stacks, move resources from one stack to another, and change the logical name of resources within the same stack. This adds a lot of flexibility enabling you to keep up with changes within your organization and architectures, such as streamlining resource lifecycle management for existing stacks, keeping up with naming convention changes, and other cases. You can refactor your stacks by using the AWS command line interface (CLI) or AWS SDK.

AWS Config now supports 4 new release typesAWS Config is great for monitoring resources across your AWS environment and help you towards ensuring alignment with your company and security policies as well as compliance requirements. It now has four new types of resources enabling you to monitor Amazon VPC block public access settings, any exceptions made within those settings, as well as monitor S3 Express One Zone bucket policies and directory bucket settings.

Automated recovery of Microsoft SQL Server on EC2 instan ces with VSS – You can now use a new feature called Volume Shadow Copy Services (VSS) to backup Microsoft SQL Server databases to Amazon Elastic Block Store (EBS) snapshots while the database is running. You can then use AWS Systems Manager Automation Runbook to set a recovery point of time of your preference and it will restore the database automatically from your VSS-based EBS snapshot without incurring any downtime.

Other updates
Upcoming changes to the AWS Security Token Service (AWS STS) global endpoint – To help improve the resiliency and performance of your applications, we are making changes to the AWS STS global endpoint (https://sts.amazonaws.com), with no action required from customers. Starting in early 2025, requests to the STS global endpoint will be automatically served in the same Region as your AWS deployed workloads. For example, if your application calls sts.amazonaws.com from the US West (Oregon) Region, your calls will be served locally in the US West (Oregon) Region instead of being served by the US East (N. Virginia) Region. These changes will be released in the coming weeks and we will gradually roll it out to AWS Regions that are enabled by default by mid-2025.

Upcoming AWS and community events

AWS Public Sector Day London, February 27 — Join public sector leaders and innovators to explore how AWS is enabling digital transformation in government, education, and healthcare.

AWS Innovate GenAI + Data Edition — A free online conference focusing on generative AI and data innovations. Available in multiple Regions: APJC and EMEA (March 6), North America (March 13), Greater China Region (March 14), and Latin America (April 8).

Browse more upcoming AWS led in-person and virtual developer-focused events.

Looking for some reading recommendations? At the beginning of every year Dr. Werner Vogles, VP and CTO of Amazon, publishes a list of recommended books that he believes should have your attention. This year’s list is looking particularly good in my opinion!

That’s it for this week! For a full list of AWS announcements, be sure to keep an eye on the What’s New with AWS page.

See you next time 🙂

Matheus Guimaraes | @codingmatheus

AWS Weekly Roundup: DeepSeek-R1, S3 Metadata, Elastic Beanstalk updates, and more (February 3, 2024)

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Last week, I had an amazing time attending AWS Community Day Thailand in Bangkok. This event came at an exciting time, following the recent launch of the AWS Asia Pacific (Bangkok) Region. We had over 300 attendees and featured 15 speakers from the community, including an AWS Hero and 4 AWS Community Builders who shared their technical expertise and experiences.

The highlight was definitely Jeff Barr, AWS Vice President & Chief Evangelist, delivering an inspiring keynote titled “Next-Generation Software Development”, which set the perfect tone for the day. The day kicked off with welcoming remarks from Vatsun Thirapatarapong, AWS Country Manager for Thailand, and was made even more special thanks to the tremendous support from both the AWS User Group volunteers and the AWS Thailand team.

Here’s a photo capturing the excitement from the event: 

Last week’s AWS Launches
There are 30+ launches last week and here are some launches that caught my attention:

DeepSeek-R1 models now available on AWS — Channy wrote on how you can now deploy DeepSeek-R1 models in Amazon Bedrock and Amazon SageMaker AI. This helps you to build and scale generative AI applications with minimal infrastructure investment.

Amazon S3 Tables increases table limit to 10,000 per bucket — S3 Tables now supports creating up to 10,000 tables in each table bucket, allowing you to scale up to 100,000 tables across 10 buckets within an AWS Region per account.

Amazon S3 Metadata now generally available — S3 Metadata provides automated and easily queried metadata that updates in near real-time, simplifying business analytics and real-time inference applications. It supports both system-defined and custom metadata, including integration with AWS analytics services.

AWS Amplify adds TypeScript Data client support for Lambda functions — Developers can now use the Amplify Data client within AWS Lambda functions, enabling consistent type-safe data operations across frontend and backend applications.

AWS Elastic Beanstalk adds Python 3.13, .NET 9, and PHP 8.4 support on Amazon Linux 2023 — AWS Elastic Beanstalk brings the latest language features and improvements to application deployments while benefiting from Amazon Linux 2023 enhanced security and performance features.

From community.aws
Here’s my top 5 personal favorites posts from community.aws:

Upcoming AWS and community events
Check your calendars and sign up for upcoming AWS and community events:

  • AWS Korea re:Invent reCap Online, February 2-4 — A virtual event recapping key announcements and innovations from re:Invent 2023 for the Korean audience.
  • AWS Community Days – Join community-led conferences that feature technical discussions, workshops, and hands-on labs. Upcoming AWS Community Day is in Ahmedabad (February 8).
  • AWS Public Sector Day London, February 27 — Join public sector leaders and innovators to explore how AWS is enabling digital transformation in government, education, and healthcare.
  • AWS Innovate GenAI + Data Edition — A free online conference focusing on generative AI and data innovations. Available in multiple Regions: APJC and EMEA (March 6), North America (March 13), Greater China Region (March 14), and Latin America (April 8).

Browse more upcoming AWS led in-person and virtual developer-focused events.

AWS Community re:Invent re:Caps

Lastly, if you want to learn about top announcements and innovations from AWS re:Invent, the AWS Community shares a summary from a community perspective of these announcements so you can get up to speed. Download the AWS Community re:Invent re:Caps deck

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

Donnie

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

AWS Weekly roundup: EventBridge, SNS FIFO, Amazon Corretto, Amazon Connect, Amazon Bedrock, and more

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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 targetsAmazon 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 desktopsAmazon 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 integrationsThis 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!

Luma AI’s Ray2 video model is now available in Amazon Bedrock

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As we preannounced at AWS re:Invent 2024, you can now use Luma AI Ray2 video model in Amazon Bedrock to generate high-quality video clips from text, creating captivating motion graphics from static concepts. AWS is the first and only cloud provider to offer fully managed models from Luma AI.

On January 16, 2025, Luma AI introduced Luma Ray2, the large–scale video generative model capable of creating realistic visuals with natural, coherent motion with strong understanding of text instructions. Luma Ray2 exhibits advanced capabilities as a result of being trained on Luma’s new multi-modal architecture. It scales to ten times compute of Ray1, enabling it to produce 5 second or 9 second video clips that show fast coherent motion, ultra-realistic details, and logical event sequences with 540p and 720p resolution.

With Luma Ray2 in Amazon Bedrock, you can add high-quality, realistic, production-ready videos generated from text in your generative AI application through a single API. Luma Ray2 video model understands the interactions between people, animals, and objects, and you can create consistent and physically accurate characters through state-of-the-art natural language instruction understanding and reasoning.

You can use Ray2 video generations for content creation, entertainment, advertising, and media use cases, streamlining the creative process, from concept to execution. You can generate smooth, cinematic, and lifelike camera movements that match the intended emotion of the scene. You can rapidly experiment with different camera angles and styles and deliver creative outputs for architecture, fashion, film, graphic design, and music.

Let’s take a look at the impressive video generations by Luma Ray2 that Luma has published.

Get started with Luma Ray2 model in Amazon Bedrock
Before getting started, if you are new to using Luma models, go to the Amazon Bedrock console and choose Model access on the bottom left pane. To access the latest Luma AI models, request access for Luma Ray2 in Luma AI.

To test the Luma AI model in Amazon Bedrock, choose Image/Video under Playgrounds in the left menu pane. Choose Select model, then select Luma AI as the category and Ray as the model.

For video generation models, you should have an Amazon Simple Storage Service (Amazon S3) bucket to store all generated videos. This bucket will be created in your AWS account, and Amazon Bedrock will have read and write permissions for it. Choose Confirm to create a bucket and generate a video.

I will generate a 5-second video with 720P and 24 frames per second with 16:9 aspect ratio for my prompt.

Here is an example prompt and generated video. You can download it stored in the S3 bucket.
a humpback whale swimming through space particles

Here are another featured examples to demonstrate Ray2 model.

Prompt 1: A miniature baby cat is walking and exploring on the surface of a fingertip

Prompt 2: A massive orb of water floating in a backlit forest

Prompt 3: A man plays saxophone by @ziguratt

Prompt 4: Macro closeup of a bee pollinating

To check out more examples and generated videos, visit the Luma Ray2 page.

By choosing View API request in the Bedrock console, you can also access the model using code examples in the AWS Command Line Interface (AWS CLI) and AWS SDKs. You can use luma.ray-v2:0 as the model ID.

Here is a sample of the AWS CLI command:

aws bedrock-runtime invoke-model 
    --model-id luma.ray-v2:0 
    --region us-west-2 
    --body "{"modelInput":{"taskType":"TEXT_VIDEO","textToVideoParams":{"text":"a humpback whale swimming through space particles"},"videoGenerationConfig":{"seconds":6,"fps":24,"dimension":"1280x720"}},"outputDataConfig":{"s3OutputDataConfig":{"s3Uri":"s3://your-bucket-name"}}}"
     invoke-model-output.txt

You can use Converse API examples to generate videos using AWS SDKs to build your applications using various programming languages.

Now available
Luma Ray2 video model is generally available today in Amazon Bedrock in the US West (Oregon) AWS Region. Check the full Region list for future updates. To learn more, check out the Luma AI in Amazon Bedrock product page and the Amazon Bedrock Pricing page.

Give Luma Ray2 a try in the Amazon Bedrock console today, and send feedback to AWS re:Post for Amazon Bedrock or through your usual AWS Support contacts.

Channy

AWS Weekly Roundup: New Asia Pacific Region, DynamoDB updates, Amazon Q developer, and more (January 13, 2025)

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As we move into the second week of 2025, China is celebrating Laba Festival (腊八节), a traditional holiday, which marks the beginning of Chinese New Year preparations. On this day, Chinese people prepare Laba congee, a special porridge combining various grains, dried fruits, and nuts. This

nutritious mixture symbolizes harmony, prosperity, and good fortune — with each ingredient representing the diversity and abundance of life. This traditional practice dates back to when Buddha achieved enlightenment after consuming rice porridge, making it a symbol of both material and spiritual nourishment. The festival, occurring on the eighth day of the twelfth lunar month, marks the countdown to Spring Festival, China’s most significant traditional holiday celebrating family reunion and renewal.

As our global tech community grows, such cultural celebrations remind us of the importance of inclusive innovation and shared progress.

Last week’s launches

Let’s take a look at what Amazon Web Services (AWS) launched in this week.

New AWS Asia Pacific (Thailand) Region– AWS has expanded its global infrastructure with the launch of the new Asia Pacific (Thailand) AWS Region, featuring three Availability Zones. With this addition, customers in Thailand and throughout Southeast Asia can serve customers with reduced latency while maintaining data residency within Thailand. The newly launched Region supports the complete range of AWS services and strengthens our presence in the rapidly growing ASEAN market.

New AWS Direct Connect location in Bangkok – Following the launch of our Thailand Region, we’ve established a new AWS Direct Connect location in Bangkok and expanded our existing infrastructure. This addition provides customers in Thailand with improved connectivity options and reduced network latency when accessing AWS services.

Database and analytics

Configurable point-in-time recovery periods for Amazon DynamoDBAmazon DynamoDB now enables customizable point-in-time recovery (PITR) periods, which means customers can specify recovery durations ranging from 1 to 35 days on a per-table basis. This enhancement enables organizations to meet precise compliance requirements while maximizing cost-efficiency. The feature is now available across all AWS Regions, including AWS GovCloud (US West) and China Regions. This flexibility in data recovery periods empowers customers to align their backup policies precisely with their business requirements and regulatory obligations.

Amazon MSK Connect APIs with AWS PrivateLinkAmazon Managed Streaming for Apache Kafka Connect (Amazon MSK Connect) APIs now support AWS PrivateLink, giving customers access to MSK Connect APIs through private endpoints within their virtual private cloud (VPC). This enhancement provides increased security and reduced data exposure by keeping traffic within the AWS network.

Generative AI and machine learning

Amazon Q Developer in SageMaker Code EditorAmazon Q Developer is now integrated into the Amazon SageMaker Code Editor integrated development environment (IDE), enhancing the developer’s experience with AI-powered code assistance. Intelligent code suggestions, documentation assistance, and contextual recommendations are now directly available within the SageMaker development environment.

Management and governance

AWS Systems Manager Automation in AWS ChatbotAWS Chatbot now offers 20 additional AWS Systems Manager Automation runbook recommendations, expanding its capabilities for automated operations management. These new recommendations help customers streamline their operational tasks and implement best practices more efficiently through chat-based interactions.

AWS Transit Gateway cost analysis enhancement – We’ve introduced new capabilities for analyzing Transit Gateway data processing charges using cost allocation tags. This feature provides improved visibility and control over networking costs, enabling organizations to track and optimize AWS Transit Gateway usage efficiently. The enhanced cost analysis tools deliver detailed insights into network traffic patterns and associated costs.

Other AWS news and highlights

2024’s most popular DevOps blog posts – The retrospective blog post “The most visited DevOps and Developer Productivity blog posts in 2024” has reached the top one position on this week’s AWS most popular articles chart. This compilation presents the most influential DevOps content from 2024, offering insights into trending topics and best practices. The collection examines key developments in continuous integration and continuous development (CI/CD), infrastructure as code (IaC), and automation practices.

New security course for generative AIAWS Skill Builder has released a new course focusing on securing generative AI applications on AWS. This comprehensive training teaches professionals to implement security best practices for artificial intelligence and machine learning (AI/ML) workloads, addressing data protection, model security, and compliance requirements. The course meets the growing demand for specialized security knowledge in the rapidly evolving field of generative AI.

Amazon Connect Contact Lens free trials – We’re introducing free trials for first-time users of Amazon Connect Contact Lens conversational analytics and performance evaluations. New customers can process up to 100,000 voice minutes monthly at no cost for 2 months, and first-time performance evaluation users receive a 30-day free trial starting with their first evaluation. With this initiative, customers can experience Contact Lens capabilities in their environment without additional costs. The free trials are available across all AWS Regions where Contact Lens is supported.

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

Whether you’re a developer, architect, business leader, or you’re starting your cloud journey – and regardless of what 2024 brought your way – 2025 presents new opportunities for everyone.

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

Betty

Announcing the new AWS Asia Pacific (Thailand) Region

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Today, we’re pleased to announce that the AWS Asia Pacific (Thailand) Region is now generally available with three Availability Zones and API name ap-southeast-7.

The AWS Asia Pacific (Thailand) Region is the first infrastructure Region in Thailand and the fourteenth Region in Asia Pacific, joining existing Regions in Hong Kong, Hyderabad, Jakarta, Malaysia, Melbourne, Mumbai, Osaka, Seoul, Singapore, Sydney, and Tokyo, as well as the Beijing and Ningxia China Regions.

Lumphini Park, one of the largest green spaces in central Bangkok spanning 142 acres.

The adoption of cloud computing has gained significant momentum in Thailand, driven by evolving business needs and government initiatives such as Thailand 4.0. These initiatives aim to transform Thailand into an innovation-driven economy by using emerging technologies to enhance productivity, competitiveness, and sustainable growth.

The new AWS Region will help startups, enterprises, government agencies, educational institutions, and nonprofit organizations run their applications and serve end users while maintaining data residency in Thailand. This aligns with Thailand’s digital transformation goals and the growing demand for cloud services. Over the next 15 years, Amazon Web Services (AWS) planned investments in Thailand are estimated to contribute $10B to Thailand’s Gross Domestic Product (GDP) and support an estimated average of 11,000 full-time equivalent (FTE) jobs in local Thai businesses annually.

Growing presence of AWS in Thailand
Our journey in Thailand began in 2013 with the first AWS office in Bangkok. Since then, AWS has continuously expanded its infrastructure and services in the country:

Amazon CloudFront – Since 2020, AWS has established six Amazon CloudFront edge locations throughout Thailand. These edge locations are part of the highly secure and programmable AWS content delivery network (CDN), designed to accelerate the delivery of data, videos, applications, and APIs to users worldwide with low latency and high transfer speeds.

AWS Outposts – In the same year, 2020, AWS introduced AWS Outposts to the Thai market. As a fully managed solution, AWS Outposts brings AWS infrastructure and services to virtually any on-premises or edge location, enabling a truly consistent hybrid experience. This service is particularly valuable for workloads that require low latency, local data processing, or local data storage.

AWS Local Zones – In 2022, AWS strengthened its commitment to Thailand by launching AWS Local Zones in Bangkok. This infrastructure deployment places compute, storage, database, and other select services closer to large population, industry, and IT centers. As a result, customers can deliver applications requiring single-digit millisecond latency to end users.

AWS Direct Connect – AWS established a AWS Direct Connect location in Bangkok in 2023 to enhance connectivity options and added a new AWS Direct Connect location with the launch of the AWS Asia Pacific (Thailand) Region. Customers can use AWS Direct Connect to establish secure and dedicated network connections to their AWS resources, providing improved network performance and reduced bandwidth costs.

AWS customer success stories in Thailand
Organizations in Thailand are using our services to drive innovation and transformation. Here are a few examples:

2C2P
2C2P, a leading Thailand-based FinTech startup, chose AWS for its robust security capabilities. As an omnichannel payment service provider in Southeast Asia, the company processes millions of customer payments globally using AWS CloudHSM for cryptographic key management, AWS Shield for distributed denial of service (DDoS) protection, and AWS Secrets Manager to safeguard sensitive credentials.

“Through AWS, we’ve unlocked the power to securely, dynamically, and compliantly scale to meet the surge in payment transaction volumes. AWS CloudHSM plays a pivotal role in fulfilling compliance requirements and propelling us toward accelerated business expansion,” says Myo Zaw, Chief Technology Officer at 2C2P.

aCommerce
aCommerce, the largest ecommerce enabler in Southeast Asia, has revolutionized market intelligence by launching AskIQ, a generative AI–powered feature on AWS. This software as a service (SaaS) platform provides the world’s leading brands with comprehensive competitor and category performance tracking capabilities across Southeast Asia’s largest ecommerce sites.

Leena Chanvirach, VP of Data Products at aCommerce Group, emphasizes the strategic value of their AWS collaboration: “Our collaboration with AWS allows clients to double down on their core competencies and business priorities. This best-of-both-worlds approach gives brands a competitive edge without the burden of building and maintaining sophisticated data infrastructure in-house.”

Ascend Money
Ascend Money, a leading Southeast Asian FinTech company, achieved a 70 percent reduction in compute costs while simultaneously improving application performance by up to 40 percent in certain workloads. Ascend Money implemented a sophisticated compute strategy using Amazon EC2 instances, resulting in significant operational improvements.

“AWS has significantly improved our performance, enabling us to deliver more innovative services to our customers,” says Peerawit Phuangkaeo, Head of Technical Operations at Ascend Money.

Building cloud skills together
AWS has built comprehensive programs for cloud education and skills development in Thailand, training more than 50,000 individuals in cloud skills since 2017. Here are some of the programs:

AWS Skill Builder
AWS Skill Builder is an online learning center where you can learn from AWS experts and build cloud skills online. AWS has made cloud education more accessible to Thai learners by offering more than 600 courses, with 106 courses specifically available in Thai language. The recent launch of the Amazon AI Ready initiative has further expanded the learning opportunities, particularly in the growing field of AI.

AWS Educate
Since its introduction in 2016, AWS Educate has played a transformative role in Thai education. The program has successfully integrated cloud computing into educational curricula across Thailand, providing students with direct access to AWS resources and hands-on experience. The impact has been substantial, with over 20,000 Thai students enrolled in the program. Beyond student education, AWS Educate has invested in training Thai educators, preparing them to deliver engaging and practical cloud computing courses that prepare students for the demands of the digital economy.

AWS Academy
AWS Academy has been instrumental in connecting academic learning with industry needs since its launch in Thailand in 2017. Through strategic partnerships with more than 30 leading universities and colleges across the country, AWS Academy has created a robust pipeline of cloud-skilled professionals. The program provides educational institutions with comprehensive cloud computing curricula that align with industry needs, making sure that students graduate with practical, job-ready skills.

Through these various initiatives and programs, AWS is not just providing educational resources, it’s building a foundation for Thailand’s digital future by helping equip the workforce with the necessary skills to use cloud technologies effectively.

Supporting sustainable innovation in Thailand
The AWS commitment to sustainability extends to supporting innovative companies in Thailand that are driving environmental initiatives.

BODA Technology & Consultancy
BODA, an AWS powered sustainability startup, uses AWS IoT Core to develop AI-powered solutions for energy efficiency optimization. The company has successfully improved operations in over 100,000 buildings and factories across Thailand, enabling these facilities to maximize efficiency while reducing costs and environmental impact.

GSPC Group
GSPC Group, a leading sustainable power company in Thailand, demonstrates how AWS supports the energy sector’s digital transformation. Following the merger between Global Power Synergy Public Company and Glow Energy, the group chose AWS Cloud for migrating its photovoltaic solar plant operations. Working with AWS and AWS Partner Dailitech, GSPC Group has achieved a 20–25 percent reduction in hardware, software, and licensing costs since moving to the cloud.

Things to know
AWS Community in Thailand — Thailand is home to two AWS Heroes, seven AWS Community Builders, and more than 17,000 members of the AWS User Group. If you’re interested in joining AWS User Group Thailand, visit their Facebook page.

AWS Global footprint — AWS now spans 111 Availability Zones within 35 geographic regions worldwide. We have announced plans for 15 more Availability Zones and five more AWS Regions in Germany, Taiwan, Mexico, the Kingdom of Saudi Arabia, and New Zealand. 

The new Asia Pacific (Thailand) Region is ready to support your business. To learn more, visit the AWS Global Infrastructure page and start building on ap-southeast-7!

Happy building!
Donnie

And that’s a wrap!

This post was originally published on this site

After 20 years, and 3283 posts adding up to 1,577,106 words I am wrapping up my time as the lead blogger on the AWS News Blog.

It has been a privilege to be able to “live in the future” and to get to learn and write about so many of our innovations over the last two decades: message queuing, storage, on-demand computing, serverless, and quantum computing to name just a few and to leave many others out. It has also been a privilege to be able to meet and to hear from so many of you that have faithfully read and (hopefully) learned from my content over the years. I treasure those interactions and your kind words, and I keep both in mind when I write.

Next for Jeff
I began my career as a builder. Over the years I have written tens of thousands of lines of assembly code (6502, Z80, and 68000), Visual Basic, and PHP, along with hundreds of thousands of lines of C. However, over the years I’ve progressively spent less time building and more time talking about building. As each new service and feature whizzed past my eyes I would reminiscence about days and decades past, when I could actually use these goodies to create something cool. I went from being a developer who could market, to a marketer who used to be able to develop. There’s absolutely nothing wrong with that, but I like to build. The medium could be code, 3D printing, LEGO bricks, electronics components, or even cardboard –creating and innovating is what motivates and sustains me.

With that as my driving force, my goal for the next step of my career is to invest more time focused on learning and using fewer things, building cool stuff, and creating fresh, developer-focused content as I do so. I’m still working to figure out the form that this will take, so stay tuned. I am also going to continue to make my weekly appearances at AWS OnAir (our Friday Twitch show), and I will continue to speak at AWS community events around the globe.

Next for the Blog
As for the AWS News Blog, it has long been backed by an awesome team, both visible and invisible. Here we are at the recent AWS re:Invent celebration of the blog’s 20th anniversary (photo courtesy of Liz Fuentes with edits by Channy Yun to add those who were otherwise occupied):

During the celebration I told the team that I look forward to celebrating the 30 year anniversary with them at re:Invent 2034.

Going forward, the team will continue to grow and the goal remains the same: to provide our customers with carefully chosen, high-quality information about the latest and most meaningful AWS launches. The blog is in great hands and this team will continue to keep you informed even as the AWS pace of innovation continues to accelerate.

Thanks Again
Once again I need to thank all of you for the very kind words and gestures over the years. Once in your life, if you work hard and get really lucky, you get a unique opportunity to do something that really and truly matters to people. And I have been lucky.

Jeff;

Now Available – Second-Generation FPGA-Powered Amazon EC2 instances (F2)

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Equipped with up to eight AMD Field-Programmable Gate Arrays (FPGAs), AMD EPYC (Milan) processors with up to 192 cores, High Bandwidth Memory (HBM), up to 8 TiB of SSD-based instance storage, and up to 2 TiB of memory, the new F2 instances are available in two sizes, and are ready to accelerate your genomics, multimedia processing, big data, satellite communication, networking, silicon simulation, and live video workloads.

A Quick FPGA Recap
Here’s how I explained the FPGA model when we previewed the first generation of FPGA-powered Amazon Elastic Compute Cloud (Amazon EC2) instances

One of the more interesting routes to a custom, hardware-based solution is known as a Field Programmable Gate Array, or FPGA. In contrast to a purpose-built chip which is designed with a single function in mind and then hard-wired to implement it, an FPGA is more flexible. It can be programmed in the field, after it has been plugged in to a socket on a PC board. Each FPGA includes a fixed, finite number of simple logic gates. Programming an FPGA is “simply” a matter of connecting them up to create the desired logical functions (AND, OR, XOR, and so forth) or storage elements (flip-flops and shift registers). Unlike a CPU which is essentially serial (with a few parallel elements) and has fixed-size instructions and data paths (typically 32 or 64 bit), the FPGA can be programmed to perform many operations in parallel, and the operations themselves can be of almost any width, large or small.

Since that launch, AWS customers have used F1 instances to host many different types of applications and services. With a newer FPGA, more processing power, and more memory bandwidth, the new F2 instances are an even better host for highly parallelizable, compute-intensive workloads.

Each of the AMD Virtex UltraScale+ HBM VU47P FPGAs has 2.85 million system logic cells and 9,024 DSP slices (up to 28 TOPS of DSP compute performance when processing INT8 values). The FPGA Accelerator Card associated with each F2 instance provides 16 GiB of High Bandwidth Memory and 64 GiB of DDR4 memory per FPGA.

Inside the F2
F2 instances are powered by 3rd generation AMD EPYC (Milan) processors. In comparison to F1 instances, they offer up to 3x as many processor cores, up to twice as much system memory and NVMe storage, and up to 4x the network bandwidth. Each FPGA comes with 16 GiB High Bandwidth Memory (HBM) with up to 460 GiB/s bandwidth. Here are the instance sizes and specs:

Instance Name vCPUs
FPGAs
FPGA Memory
HBM / DDR4
Instance Memory
NVMe Storage
EBS Bandwidth
Network Bandwidth
f2.12xlarge 48 2 32 GiB /
128 GiB
512 GiB 1900 GiB
(2x 950 GiB)
15 Gbps 25 Gbps
f2.48xlarge 192 8 128 GiB /
512 GiB
2,048 GiB 7600 GiB
(8x 950 GiB)
60 Gbps 100 Gbps

The high-end f2.48xlarge instance supports the AWS Cloud Digital Interface (CDI) to reliably transport uncompressed live video between applications, with instance-to-instance latency as low as 8 milliseconds.

Building FPGA Applications
The AWS EC2 FPGA Development Kit contains the tools that you will use to develop, simulate, debug, compile, and run your hardware-accelerated FPGA applications. You can launch the kit’s FPGA Developer AMI on a memory-optimized or compute-optimized instance for development and simulation, then use an F2 instance for final debugging and testing.

The tools included in the developer kit support a variety of development paradigms, tools, accelerator languages, and debugging options. Regardless of your choice, you will ultimately create an Amazon FPGA Image (AFI) which contains your custom acceleration logic and the AWS Shell which implements access to the FPGA memory, PCIe bus, interrupts, and external peripherals. You can deploy AFIs to as many F2 instances as desired, share with other AWS accounts or publish on AWS Marketplace.

If you have already created an application that runs on F1 instances, you will need to update your development environment to use the latest AMD tools, then rebuild and validate before upgrading to F2 instances.

FPGA Instances in Action
Here are some cool examples of how F1 and F2 instances can support unique and highly demanding workloads:

Genomics – Multinational pharmaceutical and biotechnology company AstraZeneca used thousands of F1 instances to build the world’s fastest genomics pipeline, able to process over 400K whole genome samples in under two months. They will adopt Illumina DRAGEN for F2 to realize better performance at a lower cost, while accelerating disease discovery, diagnosis, and treatment.

Satellite Communication – Satellite operators are moving from inflexible and expensive physical infrastructure (modulators, demodulators, combiners, splitters, and so forth) toward agile, software-defined, FPGA-powered solutions. Using the digital signal processor (DSP) elements on the FPGA, these solutions can be reconfigured in the field to support new waveforms and to meet changing requirements. Key F2 features such as support for up to 8 FPGAs per instance, generous amounts of network bandwidth, and support for the Data Plan Development Kit (DPDK) using Virtual Ethernet can be used to support processing of multiple, complex waveforms in parallel.

AnalyticsNeuroBlade‘s SQL Processing Unit (SPU) integrates with Presto, Apache Spark, and other open source query engines, delivering faster query processing and market-leading query throughput efficiency when run on F2 instances.

Things to Know
Here are a couple of final things that you should know about the F2 instances:

Regions – F2 instances are available today in the US East (N. Virginia) and Europe (London) AWS Regions, with plans to extend availability to additional regions over time.

Operating Systems – F2 instances are Linux-only.

Purchasing Options – F2 instances are available in On-Demand, SpotSavings Plan, Dedicated Instance, and Dedicated Host form.

Jeff;

Introducing Buy with AWS: an accelerated procurement experience on AWS Partner sites, powered by AWS Marketplace

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Today, we are announcing Buy with AWS, a new way to discover and purchase solutions available in AWS Marketplace from AWS Partner sites. You can use Buy with AWS to accelerate and streamline your product procurement process on websites outside of Amazon Web Services (AWS). This feature provides you the ability to find, try, and buy solutions from Partner websites using your AWS account

AWS Marketplace is a curated digital store for you to find, buy, deploy, and manage cloud solutions from Partners. Buy with AWS is another step towards AWS Marketplace making it easy for you to find and procure the right Partner solutions, when and where you need them. You can conveniently find and procure solutions in AWS Marketplace, through integrated AWS service consoles, and now on Partner websites.

Accelerate cloud solution discovery and evaluation

You can now discover solutions from Partners available for purchase through AWS Marketplace as you explore solutions on the web beyond AWS.

Look for products that are “Available in AWS Marketplace” when browsing on Partner sites, then accelerate your evaluation process with fast access to free trials, demo requests, and inquiries for custom pricing.

For example, I want to evaluate Wiz to see how it can help with my cloud security requirements. While browsing the Wiz website, I come across a page where I see “Connect Wiz with Amazon Web Services (AWS)”.

Wiz webpage featuring Buy With AWS

I choose Try with AWS. It asks me to sign in to my AWS account if I’m not signed in already. I’m then presented with a Wiz and AWS co-branded page for me to sign up for the free trial.

Wiz and AWS co-branded page to sign up for free trial using Buy with AWS through AWS Marketplace

The discovery experience that you see will vary depending on type of the Partner website you’re shopping from. Wiz is an example of how Buy with AWS can be implemented by an independent software vendor (ISV). Now, let’s look at an example of an AWS Marketplace Channel Partner, or reseller, who operates a storefront of their own.

I browse to the Bytes storefront with product listings from AWS Marketplace. I have the option to filter and search from the curated product listings, which are available in AWS Marketplace, on the Bytes site.

Bytes storefront with product listings from AWS Marketplace

I choose View Details for Fortinet and see an option to Request Private Offer from AWS.

Bytes storefront with option to Request Private Offer for Fortinet from AWS Marketplace

As you can tell, on a Channel Partner site, you can browse curated product listings available in AWS Marketplace, filter products, and request custom pricing directly from their website.

Streamline product procurement on AWS Partner sites
I had a seamless experience using Buy with AWS to access a free trial for Wiz and browse through the Bytes storefront to request a private offer.

Now I want to try Databricks for one of the applications I’m building. I sign up for a Databricks trial through their website.

Database homepage after login with option to Upgrade

I chose Upgrade and see Databricks is available in AWS Marketplace, which gives me the option to Buy with AWS.

Option to upgrade to Databricks premium using Buy with AWS feature of AWS marketplace

I choose Buy with AWS, and after I sign in to my AWS account, I land on a Databricks and AWS Marketplace co-branded procurement page.

Databricks and AWS co-branded page to subscribe using Buy with AWS

I complete the purchase on the co-branded procurement page and continue to set up my Databricks account.

Databricks and AWS co-branded page after subscribing using Buy with AWS

As you can tell, I didn’t have to navigate the challenge of managing procurement processes for multiple vendors. I also didn’t have to speak with a sales representative or onboard a new vendor in my billing system, which would have required multiple approvals and delayed the overall process.

Access centralized billing and benefits through AWS Marketplace
Because Buy with AWS purchases are transacted through and managed in AWS Marketplace, you also benefit from the post-purchase experience of AWS Marketplace, including consolidated AWS billing, centralized subscription management, and access to cost optimization tools.

For example, through the AWS Billing and Cost Management console, I can centrally manage all my AWS purchases, including Buy with AWS purchases, from one dashboard. I can easily access and process invoices for all of my organization’s AWS purchases. I also need to have valid AWS Identity and Access Management (IAM) permissions to manage subscriptions and make a purchase through AWS Marketplace.

AWS Marketplace not only simplifies my billing but also helps in maintaining governance over spending by helping me manage purchasing authority and subscription access for my organization with centralized visibility and controls. I can manage my budget with pricing flexibility, cost transparency, and AWS cost management tools.

Buy with AWS for Partners
Buy with AWS enables Partners who sell or resell products in AWS Marketplace to create new solution discovery and buying experiences for customers on their own websites. By adding call to action (CTA) buttons to their websites such as “Buy with AWS”, “Try free with AWS”, “Request private offer”, and “Request demo”, Partners can help accelerate product evaluation and the path-to-purchase for customers.

By integrating with AWS Marketplace APIs, Partners can display products from the AWS Marketplace catalog, allow customers to sort and filter products, and streamline private offers. Partners implementing Buy with AWS can access AWS Marketplace creative and messaging resources for guidance on building their own web experiences. Partners who implement Buy with AWS can access metrics for insights into engagement and conversion performance.

The Buy with AWS onboarding guide in the AWS Marketplace Management Portal details how Partners can get started.

Learn more
Visit the Buy with AWS page to learn more and explore Partner sites that offer Buy with AWS.

To learn more about selling or reselling products using Buy with AWS on your website, visit:

Prasad

Accelerate foundation model training and fine-tuning with new Amazon SageMaker HyperPod recipes

This post was originally published on this site

Today, we’re announcing the general availability of Amazon SageMaker HyperPod recipes to help data scientists and developers of all skill sets to get started training and fine-tuning foundation models (FMs) in minutes with state-of-the-art performance. They can now access optimized recipes for training and fine-tuning popular publicly available FMs such as Llama 3.1 405B, Llama 3.2 90B, or Mixtral 8x22B.

At AWS re:Invent 2023, we introduced SageMaker HyperPod to reduce time to train FMs by up to 40 percent and scale across more than a thousand compute resources in parallel with preconfigured distributed training libraries. With SageMaker HyperPod, you can find the required accelerated compute resources for training, create the most optimal training plans, and run training workloads across different blocks of capacity based on the availability of compute resources.

SageMaker HyperPod recipes include a training stack tested by AWS, removing tedious work experimenting with different model configurations, eliminating weeks of iterative evaluation and testing. The recipes automate several critical steps, such as loading training datasets, applying distributed training techniques, automating checkpoints for faster recovery from faults, and managing the end-to-end training loop.

With a simple recipe change, you can seamlessly switch between GPU- or Trainium-based instances to further optimize training performance and reduce costs. You can easily run workloads in production on SageMaker HyperPod or SageMaker training jobs.

SageMaker HyperPod recipes in action
To get started, visit the SageMaker HyperPod recipes GitHub repository to browse training recipes for popular publicly available FMs.

You only need to edit straightforward recipe parameters to specify an instance type and the location of your dataset in cluster configuration, then run the recipe with a single line command to achieve state-of-art performance.

You need to edit the recipe config.yaml file to specify the model and cluster type after cloning the repository.

$ git clone --recursive https://github.com/aws/sagemaker-hyperpod-recipes.git
$ cd sagemaker-hyperpod-recipes
$ pip3 install -r requirements.txt.
$ cd ./recipes_collections
$ vim config.yaml

The recipes support SageMaker HyperPod with Slurm, SageMaker HyperPod with Amazon Elastic Kubernetes Service (Amazon EKS), and SageMaker training jobs. For example, you can set up a cluster type (Slurm orchestrator), a model name (Meta Llama 3.1 405B language model), an instance type (ml.p5.48xlarge), and your data locations, such as storing the training data, results, logs, and so on.

defaults:
- cluster: slurm # support: slurm / k8s / sm_jobs
- recipes: fine-tuning/llama/hf_llama3_405b_seq8k_gpu_qlora # name of model to be trained
debug: False # set to True to debug the launcher configuration
instance_type: ml.p5.48xlarge # or other supported cluster instances
base_results_dir: # Location(s) to store the results, checkpoints, logs etc.

You can optionally adjust model-specific training parameters in this YAML file, which outlines the optimal configuration, including the number of accelerator devices, instance type, training precision, parallelization and sharding techniques, the optimizer, and logging to monitor experiments through TensorBoard.

run:
  name: llama-405b
  results_dir: ${base_results_dir}/${.name}
  time_limit: "6-00:00:00"
restore_from_path: null
trainer:
  devices: 8
  num_nodes: 2
  accelerator: gpu
  precision: bf16
  max_steps: 50
  log_every_n_steps: 10
  ...
exp_manager:
  exp_dir: # location for TensorBoard logging
  name: helloworld 
  create_tensorboard_logger: True
  create_checkpoint_callback: True
  checkpoint_callback_params:
    ...
  auto_checkpoint: True # for automated checkpointing
use_smp: True 
distributed_backend: smddp # optimized collectives
# Start training from pretrained model
model:
  model_type: llama_v3
  train_batch_size: 4
  tensor_model_parallel_degree: 1
  expert_model_parallel_degree: 1
  # other model-specific params

To run this recipe in SageMaker HyperPod with Slurm, you must prepare the SageMaker HyperPod cluster following the cluster setup instruction.

Then, connect to the SageMaker HyperPod head node, access the Slurm controller, and copy the edited recipe. Next, you run a helper file to generate a Slurm submission script for the job that you can use for a dry run to inspect the content before starting the training job.

$ python3 main.py --config-path recipes_collection --config-name=config

After training completion, the trained model is automatically saved to your assigned data location.

To run this recipe on SageMaker HyperPod with Amazon EKS, clone the recipe from the GitHub repository, install the requirements, and edit the recipe (cluster: k8s) on your laptop. Then, create a link between your laptop and running the EKS cluster and subsequently use the HyperPod Command Line Interface (CLI) to run the recipe.

$ hyperpod start-job –recipe fine-tuning/llama/hf_llama3_405b_seq8k_gpu_qlora 
--persistent-volume-claims fsx-claim:data 
--override-parameters 
'{
  "recipes.run.name": "hf-llama3-405b-seq8k-gpu-qlora",
  "recipes.exp_manager.exp_dir": "/data/<your_exp_dir>",
  "cluster": "k8s",
  "cluster_type": "k8s",
  "container": "658645717510.dkr.ecr.<region>.amazonaws.com/smdistributed-modelparallel:2.4.1-gpu-py311-cu121",
  "recipes.model.data.train_dir": "<your_train_data_dir>",
  "recipes.model.data.val_dir": "<your_val_data_dir>",
}'

You can also run recipe on SageMaker training jobs using SageMaker Python SDK. The following example is running PyTorch training scripts on SageMaker training jobs with overriding training recipes.

...
recipe_overrides = {
    "run": {
        "results_dir": "/opt/ml/model",
    },
    "exp_manager": {
        "exp_dir": "",
        "explicit_log_dir": "/opt/ml/output/tensorboard",
        "checkpoint_dir": "/opt/ml/checkpoints",
    },   
    "model": {
        "data": {
            "train_dir": "/opt/ml/input/data/train",
            "val_dir": "/opt/ml/input/data/val",
        },
    },
}
pytorch_estimator = PyTorch(
           output_path=<output_path>,
           base_job_name=f"llama-recipe",
           role=<role>,
           instance_type="p5.48xlarge",
           training_recipe="fine-tuning/llama/hf_llama3_405b_seq8k_gpu_qlora",
           recipe_overrides=recipe_overrides,
           sagemaker_session=sagemaker_session,
           tensorboard_output_config=tensorboard_output_config,
)
...

As training progresses, the model checkpoints are stored on Amazon Simple Storage Service (Amazon S3) with the fully automated checkpointing capability, enabling faster recovery from training faults and instance restarts.

Now available
Amazon SageMaker HyperPod recipes are now available in the SageMaker HyperPod recipes GitHub repository. To learn more, visit the SageMaker HyperPod product page and the Amazon SageMaker AI Developer Guide.

Give SageMaker HyperPod recipes a try and send feedback to AWS re:Post for SageMaker or through your usual AWS Support contacts.

Channy