#731: AWS News: Kiro, Amazon Bedrock AgentCore, and Lots More

Summary

AWS Podcast Episode #731: AWS News - Kiro, Amazon Bedrock AgentCore, and Lots More
Release Date: July 28, 2025
Hosts: Liz Shimothy and Simon Elisha

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Introduction

In Episode #731 of the AWS Podcast, hosts Liz Shimothy and Simon Elisha delve into a plethora of exciting updates and developments within the Amazon Web Services ecosystem. From groundbreaking AI advancements to enhanced storage solutions, this episode serves as a comprehensive guide for developers and IT professionals eager to stay abreast of the latest AWS offerings.

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AI and Development Tools

Kiro: An IDE-Enhanced Development Experience

Liz introduces Kiro (KIRO), a new Integrated Development Environment (IDE) that integrates generative AI to revolutionize software development. Unlike traditional autocomplete features, Kiro assists developers by creating comprehensive requirements based on prompts, iterating on them, and facilitating technical design.

“Kiro takes a different approach to software development being augmented by AI... if the spec is not great, you're going to get not great.”
— Liz Shimothy [00:25]

Simon praises Kiro for its holistic integration of generative AI into the development workflow, differentiating it from other IDEs that use AI merely as a coding assistant.

“The Kiro team has thought about how can we really integrate generative AI as part of the entire development experience.”
— Simon Elisha [02:04]

Amazon Bedrock AgentCore

Simon highlights the introduction of Amazon Bedrock AgentCore, a game-changer for building AI agent applications at scale. This tool streamlines the transition from proof of concept to production by handling observability, security, and reliability.

“This is going to really change how people think about building AI agentic applications overall at scale.”
— Simon Elisha [04:10]

Liz emphasizes the Agent Core Gateway, which simplifies tool integration and discovery, ensuring control and visibility over AI agents' activities.

“Agent Core Gateway... simplifies tool integration, that discovery approach and understanding what's going on.”
— Liz Shimothy [05:12]

AWS Marketplace AI Agents and Tools

Liz announces the availability of AI agents and tools from AWS partners in the AWS Marketplace, enhancing procurement and deployment processes.

“This is a new way to purchase and consume these capabilities... it becomes easier to pick and choose what makes sense for your business.”
— Liz Shimothy [06:06]

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Analytics and Data Management

AWS Glue Zero ETL Integrations

Simon introduces the latest updates to AWS Glue, which now supports zero ETL integrations from Amazon DynamoDB and eight other applications to S3 tables. This enhancement allows seamless data movement without the traditional Extract, Transform, Load (ETL) processes.

“Zero ETL means you're not actually doing the ETL... data that starts in point A can easily be viewed or read in point B.”
— Simon Elisha [05:12]

Amazon S3 Enhancements

Several updates to Amazon S3 are discussed, including:

• Metadata Support for Existing Objects: Now manages metadata for all existing S3 data, enabling SQL queries across extensive storage.

• Reduced Pricing: Discounts of up to 33% on metadata-related operations and significant reductions in compaction processing fees for Apache Iceberg tables.

• S3 Vectors (Preview): Introduces native support for storing and querying vectors, optimized for cost and performance, crucial for large-scale AI applications.

“Amazon S3 vectors is the first cloud object storage with native support for storing and querying vectors... cost-effective to create and use really large vector data sets.”
— Simon Elisha [25:37]

Amazon Redshift Updates

Amazon Redshift now supports automatic refresh of materialized views on Apache Iceberg tables and cascading refreshes of nested materialized views, enhancing data warehousing capabilities.

“Amazon Redshift now supports cascading refresh of nested materialized views with a single option to specify cascade or restrict.”
— Simon Elisha [06:57]

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Compute and Free Tier Enhancements

AWS Deadline Cloud for Unreal Engine

Simon announces expanded support for Unreal Engine in AWS Deadline Cloud, allowing developers to render projects without managing compute infrastructure.

“You can submit Unreal Engine projects to Deadline Cloud for rendering without needing to configure or manage compute infrastructure.”
— Simon Elisha [17:33]

AWS Free Tier Update

The AWS Free Tier now offers $200 in credits and a 6-month free plan, providing greater flexibility for users to explore AWS services, including Amazon Bedrock.

“You get $100 in credits straight up when you sign up and then an additional $100 if you use services like Amazon EC2.”
— Liz Shimothy [18:28]

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Database Innovations

Amazon DocumentDB Enhancements

Amazon DocumentDB with MongoDB compatibility now supports up to 10 secondary region clusters, doubling the previous limit and enhancing global scalability and disaster recovery.

“This gives you disaster recovery from region-wide outages and fast local reads for globally distributed applications.”
— Liz Shimothy [19:37]

Amazon RDS for SQL Server

Updates include support for change data capture and cumulative updates for SQL Server 2022, improving data tracking and system reliability.

“Amazon RDS for SQL Server now supports the cumulative update 19 for SQL Server 2022.”
— Liz Shimothy [20:47]

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Internet of Things (IoT) and Networking

AWS IoT Greengrass Version 2.15

Liz mentions the release of AWS IoT Greengrass version 2.15, which brings significant updates to core components, enhancing support for resource-constrained devices.

“These are all about resource-constrained devices... like five meg RAM type devices.”
— Liz Shimothy [20:56]

Amazon VPC CNI Plugin

Amazon VPC Container Network Interface (CNI) plugin now supports higher bandwidth and improved network performance per pod, catering to high-performance computing and AI workloads.

“If you need to scale the network performance for your Kubernetes-based workflows, this is definitely something that you should check out.”
— Simon Elisha [25:37]

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Management, Governance, and Observability

AWS Cost Anomaly Detection

Enhancements to AWS Cost Anomaly Detection improve model accuracy by handling historical cost variations, providing more reliable cost monitoring.

“It understands the patterns that your organization typically goes through.”
— Liz Shimothy [21:30]

AWS Knowledge Model Context Protocol (MCP) Server

The preview of the AWS Knowledge Model Context Protocol MCP Server offers authoritative AWS knowledge in an LLM-compatible format, ensuring up-to-date information access for AI applications.

“You don't have to worry about keeping it up to date because you know it's always up to date.”
— Liz Shimothy [22:47]

Amazon CloudWatch Generative AI Observability (Preview)

Amazon CloudWatch now includes generative AI observability, enabling end-to-end prompt tracing and enhanced telemetry for complex systems.

“This gives you end-to-end prompt tracing components... you get to understand telemetry across these increasingly complicated systems.”
— Liz Shimothy [23:49]

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Migration and Transfer

AWS DataSync IPv6 Support

Simon announces that AWS DataSync now supports IPv6, enhancing connectivity and future-proofing data transfer mechanisms.

“AWS DataSync now supports IPv6.`
— Simon Elisha [23:57]

AWS Transform for Mainframe

Enhanced AWS Transform for Mainframe offers improved code refactoring and business logic extraction, aiding in the modernization of legacy mainframe applications.

“This is going to result in more readable and maintainable code for developers.”
— Simon Elisha [24:01]

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Storage Solutions

Amazon EBS Volume Initialization Status

Liz shares a significant update to Amazon EBS, which now provides visibility into volume initialization status, crucial for latency-sensitive applications.

“Having visibility is really cool... EBS volumes that are created from a snapshot, it's like lazy loading in the background.”
— Liz Shimothy [25:37]

Amazon S3 Tables and Compaction Enhancements

Amazon S3 tables now support MCP Server integration and offer more cost-effective compaction operations for Apache Iceberg tables, reducing processing fees by up to 90%.

“With these compaction price reductions, the per object price is now 50% lower, while the per byte processing prices are 90% lower for bin pack compaction.”
— Simon Elisha [25:37]

Amazon S3 Vectors (Preview)

Introducing Amazon S3 Vectors, the first cloud object storage with native support for storing and querying vectors, optimized for cost and performance.

“You can reduce the cost of uploading, storing, and querying your vectors by up to 90%.”
— Simon Elisha [25:37]

S3 Console External Access Summary

The Amazon S3 console now displays an external access summary for all buckets, enhancing security by allowing users to identify publicly accessible or cross-account accessible buckets effortlessly.

“Your S3 buckets should not be public... access should be via a CloudFront distribution or specific permissions.”
— Liz Shimothy [25:37]

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Closing Remarks

Liz and Simon wrap up the episode by highlighting the extensive range of updates covered, emphasizing the transformative impact of these enhancements on AWS users' productivity and capabilities.

“This might have been like the biggest update show that we've had so far in 2025.”
— Simon Elisha [30:41]

“Keep on building.”
— Liz Shimothy [31:34]

For additional feedback or to connect with the hosts, listeners are encouraged to visit awspodcastmo.com or reach out to Jillian Ford on LinkedIn.

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This episode underscores AWS's commitment to innovation, particularly in the realms of AI, data management, and scalable infrastructure solutions. Whether you're developing cutting-edge AI applications or managing extensive cloud resources, AWS continues to provide robust tools and services to support your endeavors.

Transcript

[Simon]

This is episode 731 of the AWS podcast released on July 28, 2025.

[Liz Shimothy]

Hello everyone and welcome back to the Adabus Podcast. I'm Liz Shimothy. Great to have you back. And I'm joined by my co host Gillian Ford. G' day Gillian. How you doing?

[Simon]

Always awesome to be here. Simon. I love that you've got like the old school T shirt with like new school topics which we're going to be talking about today.

[Liz Shimothy]

For those who are listening, of course it is an audio show. I'm wearing a the Goodies podcast which is a 90s UK based comedy show that was very popular in Australia and the UK but not much else. So it's always fun to wear the Goodies T shirt. Not joined by Shruti today. She is unavailable but because we have three availability zones and two are functioning, we can carry the load just fine. And my goodness, there's a lot to talk about. Oh yeah, lots of good stuff both on the AI side and the non AI side as well. Sort of comes in two categories these days when you're talking about it, but Gillian, so one of the first things off the rank is a new development experience called Kiro K I R O. When I first read it I called it Kairo, but I'm told it's called Kiro and it's a IDE based development experience and I've been using it for a little while actually myself and I'm really enjoying it because it takes a different approach to software development being augmented by AI. It's less of a autocomplete ask for answers type thing and far more of a create me a set of requirements based upon a set of prompts, iterate on those and then do the technical design based on those requirements and then go and build. And I think as we've been talking about generative AI and its use in software development, the creation of the spec is actually far more important than it's ever been before because the machine will go do what the machine is told and if the specific is not great, you're going to get not great. If you get a really robust clear spec, you'll be able to build really well. So this is kind of interesting. I don't know Jillian, what you've seen and what you've been experiencing with it.

[Simon]

Yeah, I think it's a really cool that because in the past like generative AI has been incorporated into ides based on how we've been programming pre generative AI. And I like that the Kiro team has thought about, well, how can we really integrate generative AI as part of the entire development experience? And what does that look like? And I think that is something you'll see as a difference between using Curo versus if you were to use whatever your favorite IDE is and then maybe just use like your, like maybe an LLM or whatever to help doing your coding assistant. So I think that's really cool. Like MCP servers of course is something that you'll see the agentic chat, which is definitely something that you're probably already used to if this is something that's already integrated in your workflow. I think the hooks is also really interesting. So these are agent hooks that are going to help with automation as part of your like integrative development experience. But now it's agent tech type of hooks versus maybe just automation that you're probably used to already in your development life.

[Liz Shimothy]

It's all really, really similar stuff. But the nice thing is I was a VS code user and a VS code user. The migration into into Curos, literally one click, complete compatibility with all your plugins and everything else, it's all easy, which is great. So it's a very familiar experience. You just get like some extra capabilities like, oh, this lets me build quicker, which is what I'm always looking for, and better.

[Simon]

I like it.

[Liz Shimothy]

Now there was also more and I think quite a substantially important iteration in the world of generative AI agents just recently. And this is in the form of Amazon Bedrock Agent Call and you took a bit of a deep dive on this. Gillian, tell us about what you see in this new capability, kind of what it is and where it fits.

[Simon]

Yeah, this is super cool and I think it's going to really change how people think about building AI agentic applications overall at scale. So let's talk about what it is. So this is going to help really streamline the process of taking your AI agent applications that you're currently building in your proof of concept stage and then getting it into production. Whether that's, how do you set up observability, how do you make sure that it's secure, how do you make sure that reliability is also included as part of the overall application? And you can use a bunch of different open source frameworks that maybe customers have already started to use. You can now use that within Agent Core and it's going to be hosted within the Amazon Bedrock ecosystem. So it just makes it much simpler to go from proof of concept to production.

[Liz Shimothy]

It does. And one of the things that really appealed to Me too. I guess from an enterprise user perspective is the fact that there's this thing called the Agent Core Gateway which really simplifies that tool integration, that discovery approach and understanding what's going on. This, this seems to be the pattern, I guess, that's emerging in terms of, well, how do we let all these agents go do their stuff, but also maintain some degree of control and understanding of what's going on.

[Simon]

Yeah, absolutely. And some other things also, in addition to the security aspects that really come to mind. I like that you've got short term and long term memory as an option and long term lives literally eight hours. And so if you can think about like, wait eight hours, a lot of things you can do in an application, a workflow, if you're having eight hours as a memory context, and then hundreds of tools like. So the ideas of what you could possibly build are almost endless.

[Liz Shimothy]

Yeah, think it's exciting. Speaking of exciting, let's get into some of the other updates we've had. Firstly for the AWS Marketplace. Speaking of agents, we are now introducing AI agents and tools in the AWS marketplace. So this lets agents and tools from AWS partners be purchased from the marketplace. So it's a streamlined procurement and deployment experience, means you can find what you need more quickly and get up and running fast. So again, this is a new way to, I guess, purchase and consume these capabilities. And again, it ties into, I think, where things are moving in the future. And you can also, as a partner, you can categorize your offerings and highlight MCP support, A2A protocol support, et cetera. So as people are growing out in what they're doing, and this all integrates into Amazon bedrock, Agent Core as well, it becomes easier to pick and choose what makes sense for your business.

[Simon]

Now we've got some updates. In the world of analytics, AWS glue now supports zero ETL integrations from Amazon DynamoDB and eight applications to S3 tables. And so for those who are new to the Xero etl, just do a, I'll do a quick primer. So zero ETL ETL is what it sounds like. That means you're not actually doing the etl. AWS has created these integrations with services, so data that starts in point A can easily be like viewed red in point B. So let's say like RDS for an example, maybe you have a redshift data warehouse. And fun fact, there's even a landing page if you want to look up. And zero etl. It's amazing the number of different zero etl integrations that are out there within aws. So I definitely suggest taking a look at that as you're thinking about ways of being able to move and share data, since there might be zero ETL integrations that are built and you don't have to actually do that yourself. So now how does this translate into what we're talking about today? So with Dynamodb and AWS Glue and especially Amazon S3 tables, you can now automate the extraction loading of data into S3 tables from DynamoDB and other applications like Salesforce, SAP ServiceNow and Zendesk. So now with the Zero with, you can enable S3 tables to also work with lake formation to support other services as well. Athena, emr, Redshift and Glue. So yeah, this is definitely a time saver.

[Liz Shimothy]

Lots of integrations.

[Simon]

Lots of, lots of integrations for sure. And more MCP we're also announcing Amazon MSK has MCP based surfer that allows customers to interact with their Amazon MSK clusters using a standardized natural language interface and agentic applications. Amazon Redshift now supports automatic refresh of materialized views that are defined on external Apache Iceberg tables in the Amazon S3 data lake. So with this update Amazon Redshift is going to automatically refresh a materialized view when defined on Apache Iceberg tables that reside in the Amazon S3 bucket of the data lake. Amazon Redshift now supports cascading refresh of nested materialized views that are defined on local Amazon Redshift tables and external streaming sources such as Amazon Kinesis Data Streams, Amazon Managed streaming for Apache, Kafka or Confluent Cloud. With this update, customers can now run cascading refresh of nested materialized views with a single option to specify cascade or restrict. And now we've got application integration. We also have the MCP server for the AWS API. I can only imagine the amount of things that you could probably go wild with with this type of yeah, it's.

[Liz Shimothy]

A big deal control.

[Simon]

So literally the AWS API MCP server allows MCP clients to Discover supported AWS APIs and make calls to them through the host of foundation models enabling actions such as inspecting, creating and modifying AWS resources like wow, that is like.

[Liz Shimothy]

Yeah, let, let's, let's be careful on that last one folks.

[Simon]

Or else you're going to hear from from Simon the phrase.

[Liz Shimothy]

The phrase dry run is always an important one.

[Simon]

But don't worry because the server provides secure access through IAM credentials and is pre configured with API permissions. So that does ensure that foundation models can only access or perform authorized actions on permitted AWS APIs, but definitely still agree with Simon. You definitely want to be scoped out. Yes, with that one. Amazon EventBridge now supports logging to Amazon CloudWatch logs, Amazon S3 and Amazon Kinesis data firehose, improving observability and simplifying debugging for your event driven applications. Amazon Corretto has announced quarterly security and critical updates for long term supported and feature released versions of OpenJDK.

[Liz Shimothy]

Let's talk about artificial intelligence and we're happy to introduce the new AWS AI League. This is a program that helps organizations upskill their workforce by combining a fun competition with hands on learning using AI services like Amazon SageMaker AI and Amazon Bedrock. The program offers unique opportunities for both enterprises and developers to get valuable and practical skills in fine tuning, model customization and prompt engineering. Now you can apply to receive AWS credits to host internal AWS AI League competitions which helps foster a culture of innovation. Individual developers can also participate in the league at select AWS Summits and at Re Invent, which means you can compete with lots of others. There is up to 2 million Doll of Adams credits and a championship prize pool of $25,000 to reward top performers at Atomis Re Invent. So get a look at it. I know that when folks used to do the deepracer League, they got a lot out of it. This is kind of the next version of that in the brand new world. Image to Video Generation support for Luma's AI Ray 2 is now available in Amazon Bedrock. This new feature expands upon the text to video generation capabilities that came out in January, which gives you even more powerful tools for creating dynamic video content. You can now static jpeg and PNG images of up to 25 meg into videos. Wow. I gotta try it. Okay, this is cool. This is like, you know, because I always have trouble starting the picture, but if I have the picture I can then make the video from the picture. That's nice. I like it.

[Simon]

Well, we can create like image to videos of like us, the podcast hosts.

[Liz Shimothy]

Yeah, let's not do that. That's a poor use of the technology. I would suggest some new foundation models available In Amazon Bedrock 12 Labs, Marengo 2.7 and Pegasus 1.2 multimodal foundation models are available. Marengo 2.7 is a video embedding model proficient at performing tasks like searching classification, while Pegasus 1.2 is a video language model that can generate text based on your video data. Amazon novasonic has added language support for French, Italian and German. Now this is a speech to speech foundation model that delivers real time human voice conversations with low latency. I know folks who've used this are like it's pretty cool. So now it supports more languages. We're announcing on demand deployment for custom Amazon Nova models in Amazon Bedrock. So this enables Bedrock customers to reduce their costs by processing requests in real time without requiring pre provisioned compute resources. You can now customize Amazon nova in Amazon SageMaker AI so available as ready to use recipes. This allows you customers to adapt Nova Micro Anova Lite Anova Pro across the model training lifecycle including pre training, supervised fine tuning and alignment. Amazon SageMaker has announced integration with Amazon Quicksight so you can now launch your Amazon Quicksight directly from the unified studio. Amazon SageMaker Catalog has added support for Amazon S3 general purpose buckets so this makes it easy for you to discover and access data sets. And Amazon SageMaker HyperPod has accelerated Open Weight's model deployment so this lets you seamlessly train, fine tune and deploy models on the same hyperpod compute resources which means you maximize your resource utilization across the whole model lifecycle. Building models is hard and it's a big deal and there's a lot of computing. I know hyperpod helps a lot of folks working that space and related to that few updates for Hyperpod in fact we're announcing a new observability capability so now you can understand what's going on and take away their manual work of collecting hundreds of metrics from across the stack. And hyperpod has also introduced CLI and SDK for AI workflows so you can now build things out in a far more intuitive and automated way. Amazon SageMaker Studio now also supports remote connections from Visual Studio code so if that's what you like to use. Also things like Jupyter Lab and Code Editor based on code OSS you can get access to that. And Amazon SageMaker not finished yet. They've introduced a visual workflows builder so it's a drag and drop interface for building workflows which makes authoring and scheduling much easier. Amazon SageMaker also now supports data processing jobs so you can author, manage, monitor and troubleshoot your data processing workloads as well. And it is also now simplified data management with automated lakehouse onboarding and metadata ingestion so you can automatically ingest your metadata for your data sets. Things like glue data catalog tables into your SageMaker catalog so there's no manual IAM permissions. Undifferentiated heavy lifting goes away. SageMaker has also streamlined the S3 tables workflow experience so it makes it easy for you to query, create and join Amazon S3 tables with data in S3 general purpose buckets and fully managed ML Flow 3 is also now available on Amazon SageMaker AI. So this allows you to do more experimentation and it transforms your managed ML flow from an experiment tracking to providing end to end observability which reduces your time to market and makes it easy to figure out what's going on in the experiments that you're running. So lots of updates there. A quick update for business applications Custom integrations is now available for topics in ML. Amazon Q in Quicksight Custom instructions enable author professionals to curate Amazon Q's responses to questions by adding domain specific knowledge that can't be captured through a topic's metadata settings like synonyms or semantic types.

[Simon]

Next up is Compute AWS Deadline Cloud has expanded its support for Unreal Engine in its service managed fleets. With this new feature you can submit Unreal Engine 5.4, 5.5 or 5.6 projects to deadline Cloud for rendering without needing to configure or manage compute infrastructure. AWS Deadline Cloud now supports usage based licensing for Chaos v Ray so you can seamlessly leverage the cloud to render and access flexible V Ray licensing. And we've got a new update on the free tier. AWS Free Tier now offers $200 in credits and 6 month free plan to explore AWS at no cost. I think we need a sound for this one.

[Liz Shimothy]

I had no warning that a sound was required. Let me see if I can. I can do this. There you go. That's the best I can do in short notice.

[Simon]

All right.

[Liz Shimothy]

But this is a big deal because this is a big change to the way the free tier works and I think it gives you a lot more flexibility because you get your credits and you can do what you want rather than having to kind of track what each particular service has. A free tiering.

[Simon]

That's a great call out. And I also want to call out that Amazon Bedrock is included as one of the services that you can use these $200 in credits for. And that goes a long way when you're just building a proof of concept for an AI application. Not to bring up AI again, but.

[Liz Shimothy]

Yeah, and the way it works is you get $100 in credits straight up when you sign up and then you get an additional $100 in credits if you use services like Amazon EC2 or Amazon. So you get sort of the way to go there. Also, there are still 30 always free services. So these are Services that are always free will not list them for you. It's in the free plan details. But it means you can get up and running and do meaningful work very, very quickly, which is kind of nice.

[Simon]

And yes, it's available in all AWS regions.

[Liz Shimothy]

Exactly, except US Gov cloud regions and the China regions.

[Simon]

Good call, good call. And Amazon EKS announces support for up to 100,000 worker nodes in a cluster, enabling you to run ultra scale AI ML training and inference workloads in a single cluster. That's a lot.

[Liz Shimothy]

That is a lot. Let's talk about databases. Amazon DocumentDB with MongoDB compatibility now introduces support for up to 10 secondary region clusters. So that's awesome if you're building anything that needs scalability, availability and is globally distributed. So this gives you disaster recovery from region wide outages and it gives you fast local reads for globally distributed applications. So previously we had a limit of five, now it's up to 10. So twice as good as it was before. Amazon RDS custom for SQL Server now supports change data capture. Amazon RDS for SQL Server also now supports the cumulative update 19 for SQL Server 2022, which allows in to remind you too. Let's see if I can get this right. Haven't done it for a little while. Pack your stuff.

[Simon]

Sounded a little different this time. There. There wasn't. There was a bigger echo before when you.

[Liz Shimothy]

I know it was. That was the megaphone. Whereas I could have done this one.

[Simon]

Oh, that's a new one. I like that. I think that one will definitely freak people out to get them moving. Now let's talk about the Internet of Things. AWS announces the Release of AWS IoT Greengrass version 2.15 introducing significant updates to both Nucleus and Nucleus Light core components. I don't know what that means, but I'm sure if you're probably, if you're an IOT person, you probably are in the know and know what that actually means.

[Liz Shimothy]

And that's the thing. And these are all about resource constrained devices. So we're talking five meg RAM type devices. So that's funny. On the one hand, as IT professionals we get to work with like these machines that have got extraordinary amounts of storage on them now. And on the other hand there's a whole bunch of folks who are like, yeah, I got five meg to work with here, throw me a bone. Let's talk about management and governance. AWS cost anomaly detection improves accuracy with model enhancements. Now if you're not using AWS cost anomaly detection and I do it gives you a heads up if things are happening that are out of traditional behaviors. Now this update provides you with a more consistent and reliable cost model monitoring by handling historical cost variation so it understands the patterns that your organization typically goes through. We're happy to announce the preview of the AWS Knowledge Model Context Protocol MCP Server. This is a new tool that surfaces authoritative AWS knowledge in an LLM compatible format. So you're getting documentation, blog posts, what's new announcements and well architected best practices. And you don't have to worry about keeping it up to date because you know it's always up to date. So this is going to be a go to for me in terms of my little MCP collections that I'm going to run. The AWS Price List API now supports four new query filters so you can search product data more easily. These new filters help simplify product discovery, which means you can get up and running quickly. So you can now search products by exactly managing attributes, using substring matches and creating include exclude lists for more targeted results. And if we weren't doing enough in the world of price lists, we now have an MCP server for the Adidas Price list. Can you get a trend going on here folks? The world is mcp' ing itself, so now you can leverage your AI assistants to access pricing and product information across regions and make data driven decisions all through natural language conversations. I'm excited to use this one too. And Amazon CloudWatch adds generative AI observability in preview as well. So this gives you end to end prompt tracing components like knowledge bases, tools and models. This is compatible with things like strands, agents, LangChain, langgraph, et cetera. So you can use the flexibility of choice, but it means you get to understand telemetry across these increasingly complicated systems as well.

[Simon]

Next up is migration and transfer. AWS datasync now supports IPv6 the year.

[Liz Shimothy]

Of IPv6 continues Julian it really is.

[Simon]

AWS Transform for Mainframe introduces enhanced code, refactoring and business logic capabilities. The Reforge capability in AWS Transform for Mainframe. This is going to enhance Java code by restructuring complex methods and it's going to add descriptive comments, optimize variable usage and improve the overall code flow. So this is going to result in more readable and maintainable code for developers. And AWS Transform for Mainframe's Business Logic Extraction capability now provides application level insights from high level summaries to detailed business function analysis which is going to complement the existing file level business logic extraction to help users better understand their legacy applications like that. Nothing worse than not knowing what's going on in your application.

[Liz Shimothy]

What is this thing doing?

[Simon]

Yep, next topic is networking and content delivery. Amazon VPC CNI or Container Network Interface plugin now supports higher bandwidth and network performance per pod. So this is really useful for AI high performance computing use cases and this interface is going to handle all of the incoming and outgoing traffic per pod. So if you need to scale the network performance for your kubernetes based workflows, workloads, this is definitely something that you should check out.

[Liz Shimothy]

Now let's talk about storage. Amazon EBS now provides visibility into EBS Volume initialization status oh this is a cool one. I'm very happy with this. You can use this status to determine when your volume becomes fully initialized when restoring from a snapshot and is fully ready to support latency sensitive applications. So EBS volumes that are created from EBS snapshots undergo volume initialization in which the storage blocks from the snapshot must be downloaded from Amazon S3 and written to the volume before you can access them. Now the volume initialization rate fluctuates throughout the initialization process which can make completion times unpredictable. So sometimes you get increased I O latency and reduce performance. Now you can see where you're at using this status. This is a big deal for me as an old timer Amazonian cloud user because we'd always tell folks if you're using an EBS volume that's created from a snapshot, it's kind of lazy loading in the background so things can be unpredictable. Having visibility is really cool. Amazon S3 metadata now supports existing objects and reduces prices by up to 33%. So now you can discard discover data that's in your S3 data and previously S3 metadata supported new and updated objects. Now it will also create and manage metadata for your existing S3 data so you can write a SQL query across metadata for any amount of S3 storage. As I've always said folks, SQL learn it, you just get to use it for everything. The other thing is that we're reducing the journal table price by 33% to make real time change tracking and backfilling more cost effective for large data sets. So the cost reduction continue and then more of those to come in a second. Amazon S3 tables though now supports Guess what model context protocol MCP server. So this integration lets AI assisted data management happen because now your AI code assistants have a contextual understanding of S3 table capabilities and operations so you can accelerate what you're doing. I mentioned there'd be more cost effective stuff. Well guess what? Amazon S three tables now offers more cost effective compaction operations for Apache Iceberg tables with processing fees reduced by up to 90%. S3 tables provide storage that's optimized for analytic workloads, which automates maintenance operations like compaction to continuously improve query performance and reduce storage costs. With these compaction price reductions, the per object price is now 50% lower, while the per byte processing prices are 90% lower for bin pack compaction and 80% lower for sort and Z Order Compaction. So this is pretty nice. Amazon S3 also now supports compaction of Apache Avro and Orc formats for Apache Iceberg tables. And another big deal is Amazon S3 vectors is now available in preview. This is the first cloud object storage with native support for storing and querying vectors. Now this is important because it reduces the cost of uploading, storing and querying your vectors by up to 90%. So this allows it to be cost effective to create and use really large vector data sets. It's designed to provide the same elasticity, scale and durability as Amazon S3, but this lets you store and search data with sub second query performance. S3 vectors gives you a simple and flexible API for operations like finding similar scenes in petabyte scale video archives, identifying collections of related business documents, or detecting rare patterns in diagnostic collections of millions of medical images. So this is really, really cool. It's native natively integrated with Amazon Bedrock knowledge bases so you can reduce the cost of using large vector data sets for rag type work. You can also use it with the Amazon OpenSearch service to lower your storage cost for infrequently queried vectors and then quickly move them to OpenSearch as demands increase or to enhance your search capabilities. Lots and lots of choice here. I was speaking to someone the other day and they said to me, Simon, this is where the vector should have been in the first place. It's hard to disagree. And finally, the Amazon S3 console now displays an external access summary for all your buckets. So you can now identify S3 buckets in any region that allow public access or access from other AWS accounts without needing to inspect policies in each AWS region individually. So this is powered by the AWS IAM Access Analyzer and is available at no cost in the console in all AWS regions. This is my reminder to you that that none of your Amazon S3 buckets should be public. If you need to access data from an S3 bucket it should be via for example a cloud front distribution or through a specified permission through an endpoint that is delivered to your customers. It shouldn't just be open to world so just not a thing you should do. Wow Gillian, lots of updates there.

[Simon]

There is a lot. I mean this might have been like the biggest update show that we've had so far in 2025. Not just like obviously yes the AI updates but even just other overall AWS productivity types of updates.

[Liz Shimothy]

The EBS volume stuff. I'm super excited about that. That's really, really cool. So pretty.

[Simon]

I appreciate that you are like the true Amazonian to get super excited about.

[Liz Shimothy]

I remember when we didn't have EBS. I remember when when the only two statuses of an EC of a EC2 instance were running or terminated. It was a different world.

[Simon]

It really is compared to where it is that we're at now.

[Liz Shimothy]

Jillian, how do folks reach out to you?

[Simon]

I am Jillian Ford on LinkedIn and.

[Liz Shimothy]

If you want to give us feedback the old fashioned way, awspodcastmo. Com is the place to do it. And until next time, keep on building.