Following my enriching experience at the AWS Summit in Bangkok, Thailand, where the Developer Lounge buzzed with activity, I’m excited to share the latest updates from Amazon Web Services. The summit provided a fantastic opportunity for developers to connect, exchange ideas, and explore the newest AWS offerings. If you’re in the ASEAN region, don’t miss the upcoming AWS Summit in Singapore.
Recent AWS Launches
Here’s a rundown of some noteworthy AWS launches from the past week:
Amazon Nova Premier Now Generally Available
Amazon Nova Premier, meticulously designed for intricate tasks and model distillation, has achieved General Availability within Amazon Bedrock. This model distinguishes itself through its profound ability to address complex challenges that demand an in-depth understanding of contextual nuances and multistep planning. It efficiently processes a diverse range of data types, including text, images, and videos, leveraging a substantial 1M token context length to ensure comprehensive analysis and decision-making. The availability of Nova Premier marks a significant advancement in the capabilities of Amazon Bedrock, providing users with a powerful tool for handling sophisticated and computationally intensive workloads.
The true potential of Nova Premier is fully realized when used in conjunction with Amazon Bedrock Model Distillation. This synergistic combination allows users to create tailored versions of Nova Pro, Lite, and Micro, each meticulously optimized to meet specific performance requirements and cost constraints. These customized models are not only highly effective in their respective domains but also offer exceptional cost efficiency and low latency, making them ideally suited to a wide array of unique requirements. The ability to fine-tune and adapt Nova Premier to specific use cases ensures that users can leverage the model’s power without incurring unnecessary costs or compromising on performance.
The process of model distillation involves training smaller, more efficient models to mimic the behavior of the larger, more complex Nova Premier model. This technique enables users to deploy models that are significantly faster and less resource-intensive, while still retaining a high degree of accuracy and performance. By carefully selecting the training data and hyperparameters, users can create distilled models that are perfectly tailored to their specific needs, ensuring optimal performance and cost-effectiveness.
Amazon Q Developer Elevates IDE Experience
Amazon Q Developer is revolutionizing the Integrated Development Environment (IDE) experience with an innovative agentic coding approach. This groundbreaking feature empowers Q Developer to intelligently execute actions on behalf of the developer directly within Visual Studio Code. By automating routine tasks and providing intelligent assistance, Q Developer significantly enhances developer productivity and reduces the cognitive load associated with complex coding projects.
The agentic coding approach employed by Q Developer fosters real-time collaboration for various development activities, including coding, documentation, and testing. The platform provides transparent reasoning for its actions, allowing developers to understand the rationale behind the suggestions and decisions made by the AI agent. Furthermore, Q Developer supports automated or step-by-step modifications across multiple programming languages, providing developers with the flexibility to work in their preferred environment and leverage the platform’s capabilities regardless of the specific language being used.
The ability to automate code generation, documentation, and testing streamlines the development process and allows developers to focus on more strategic and creative tasks. The transparent reasoning provided by Q Developer ensures that developers maintain control over the development process and can understand the logic behind the AI agent’s suggestions. The multi-language support further enhances the platform’s versatility and makes it a valuable tool for developers working on a wide range of projects.
New Foundation Models in Amazon Bedrock
Amazon Bedrock’s model offerings have been significantly expanded with the addition of two new foundation models, further solidifying its position as a leading platform for generative AI. These new models bring enhanced capabilities and expanded functionality to the Bedrock ecosystem, empowering users to tackle a wider range of AI-powered applications and use cases.
Writer’s Palmyra X5 and X4: These models are specifically designed for complex reasoning within enterprise applications, featuring large context windows (1M and 128K tokens, respectively) to enable comprehensive analysis of extensive datasets. The models support sophisticated tool-calling, allowing them to seamlessly interact with external APIs and services to augment their reasoning capabilities. They also incorporate adaptive thinking mechanisms, enabling them to dynamically adjust their strategies based on the evolving context of the task at hand. The Palmyra X5 and X4 models adhere to high reliability standards, ensuring consistent and dependable performance in critical enterprise applications.
Meta’s Llama 4 Scout 17B and Maverick 17B: These models offer native multimodal capabilities, seamlessly integrating text and image processing to enable a richer understanding of complex information. They utilize a mixture-of-experts architecture, which combines the strengths of multiple specialized models to enhance reasoning and image understanding. The models support multiple languages and extended context processing, making them well-suited for global applications and scenarios requiring the analysis of lengthy documents. Streamlined integration is facilitated through the Bedrock Converse API, providing a seamless and intuitive interface for interacting with the models.
The addition of these new foundation models significantly expands the capabilities of Amazon Bedrock, providing users with a wider range of options for building and deploying AI-powered applications. The Palmyra X5 and X4 models are ideal for enterprise applications requiring complex reasoning and tool-calling, while the Llama 4 Scout 17B and Maverick 17B models are well-suited for multimodal applications requiring the integration of text and image processing.
Second-Generation AWS Outposts Racks Released
AWS has announced the general availability of its second-generation Outposts racks, marking a significant advancement in the capabilities and performance of on-premises cloud infrastructure. These next-generation racks incorporate a range of enhancements, including the latest x86 EC2 instances, simplified networking configurations, and accelerated networking options, delivering substantial improvements in performance, scalability, and ease of management.
The second-generation Outposts racks offer doubled vCPU, memory, and network bandwidth compared to their predecessors, resulting in a remarkable 40% performance boost. This enhanced performance makes them ideal for demanding on-premises deployments that require significant computational resources and high-bandwidth connectivity. The racks also provide support for ultra-low latency workloads, ensuring that applications requiring real-time responsiveness can operate with optimal efficiency.
The simplified networking configurations streamline the deployment and management of Outposts racks, reducing the complexity associated with integrating on-premises infrastructure with the AWS cloud. The accelerated networking options provide further performance enhancements, enabling applications to communicate with minimal latency and maximum throughput. These improvements make the second-generation Outposts racks a compelling solution for organizations seeking to extend the power and flexibility of AWS to their on-premises environments.
Amazon CloudFront SaaS Manager Launches
Amazon CloudFront SaaS Manager is a purpose-built service designed to empower SaaS providers and web hosting platforms with the ability to effectively manage content delivery across multiple customer domains. This innovative service minimizes operational complexity while simultaneously delivering high-performance content and enterprise-grade security for each individual customer domain.
By centralizing the management of content delivery through a single platform, Amazon CloudFront SaaS Manager significantly reduces the administrative overhead associated with managing multiple customer domains. The service provides a comprehensive set of tools and features for configuring and optimizing content delivery, ensuring that each customer receives the best possible performance and security. The service also integrates seamlessly with Amazon CloudFront, leveraging its global network of edge locations to deliver content with exceptional speed and reliability.
The enterprise-grade security features of Amazon CloudFront SaaS Manager protect customer data and applications from a wide range of threats, including DDoS attacks, bot traffic, and malicious code injection. The service provides granular control over access policies, allowing SaaS providers to restrict access to sensitive data and resources. The service also offers comprehensive logging and monitoring capabilities, providing real-time visibility into the performance and security of content delivery operations.
Extend the Amazon Q Developer CLI with Model Context Protocol (MCP)
The Amazon Q Developer CLI now supports the Model Context Protocol (MCP), a powerful extension that enables seamless integration with external data sources, providing context-aware responses that significantly enhance the accuracy and relevance of code suggestions and query results. This integration empowers developers to connect pre-built integrations or MCP Servers that support stdio, enriching code accuracy, data understanding, and query execution.
By leveraging the Model Context Protocol, the Amazon Q Developer CLI can access a vast array of external data sources, including databases, APIs, and other repositories of information. This contextual awareness allows the CLI to provide more accurate and relevant code suggestions, answer complex queries with greater precision, and generate code that is better aligned with the specific requirements of the project. The feature streamlines development tasks and will soon be available in Amazon Q Developer IDE plugins, further enhancing the developer experience.
The Model Context Protocol provides a standardized interface for connecting external data sources to the Amazon Q Developer CLI, simplifying the integration process and allowing developers to easily access the information they need. The stdio support ensures that the CLI can communicate with a wide range of MCP Servers, regardless of the underlying technology or platform. This flexibility makes the Model Context Protocol a valuable tool for developers working on a wide range of projects and using a variety of different data sources.
Amazon Aurora Now Supports PostgreSQL 17
Amazon Aurora, the fully managed, MySQL- and PostgreSQL-compatible relational database service, now supports PostgreSQL 17.4. This latest release incorporates a wealth of community improvements and Aurora-specific enhancements, including optimized memory management and faster failovers, further enhancing the performance, reliability, and scalability of Aurora databases.
The PostgreSQL 17.4 release includes numerous bug fixes, security patches, and performance optimizations contributed by the PostgreSQL community, ensuring that Aurora users benefit from the latest advancements in database technology. The Aurora-specific enhancements, such as optimized memory management and faster failovers, are designed to further improve the performance and resilience of Aurora databases, making them an ideal choice for mission-critical applications.
This release also includes new features for Babelfish, enabling users to run SQL Server applications directly on Aurora PostgreSQL, simplifying migration and reducing costs. The release also includes updated extensions, providing access to a wider range of functionality and capabilities. PostgreSQL 17.4 is available in all AWS Regions, making it accessible to users around the globe.
CloudWatch Introduces Tiered Pricing for Lambda Logs
Amazon CloudWatch, the monitoring and observability service for AWS cloud resources and applications, has introduced tiered pricing for AWS Lambda logs and new delivery destinations, offering greater flexibility and cost savings for users managing large volumes of log data.
In the US East region, pricing starts at $0.50/GB for CloudWatch and $0.25/GB for S3 and Firehose, both scaling down to $0.05/GB as log volume increases. This tiered pricing structure allows users to pay only for the log data they consume, with lower prices for higher volumes of data. The new delivery destinations provide users with more options for storing and processing their log data, allowing them to choose the solution that best meets their needs.
This update offers greater flexibility in log management across all supported Regions, empowering users to optimize their log management strategies and reduce costs. The tiered pricing structure makes CloudWatch a more cost-effective solution for managing Lambda logs, while the new delivery destinations provide users with more options for storing and processing their data.
RDS for MySQL Updates Minor Versions
Amazon RDS for MySQL now supports minor versions 8.0.42 and 8.4.5, incorporating critical security fixes, bug fixes, and performance improvements that enhance the stability, reliability, and security of RDS for MySQL databases.
These minor version updates include a range of bug fixes that address known issues and improve the overall stability of the database engine. The updates also include security patches that address potential vulnerabilities and protect against malicious attacks. The performance improvements enhance the speed and efficiency of database operations, improving the responsiveness of applications and reducing resource consumption.
Users can upgrade automatically during maintenance windows or use Blue/Green deployments for safer updates, minimizing downtime and ensuring a seamless transition to the latest version. The Blue/Green deployment strategy allows users to create a parallel environment with the updated version of the database and then switch over to the new environment with minimal interruption to service.
Amazon Bedrock Model Distillation Generally Available
Amazon Bedrock Model Distillation has achieved General Availability, supporting new models such as Amazon Nova and Claude 3.5. This powerful technique enables the creation of smaller, more efficient models that accurately predict function calling for Agents, delivering responses up to 500% faster and reducing costs by 75% with minimal accuracy loss for RAG use cases.
Model Distillation involves training a smaller, more efficient model to mimic the behavior of a larger, more complex model. This technique allows users to deploy models that are significantly faster and less resource-intensive, while still retaining a high degree of accuracy and performance. The process is particularly effective for RAG (Retrieval-Augmented Generation) use cases, where the distilled model can quickly retrieve relevant information and generate accurate responses.
The service includes automated workflows for data synthesis and student model training, simplifying the process of creating and deploying distilled models. The automated workflows guide users through the steps involved in data preparation, model training, and evaluation, ensuring that the resulting distilled models are optimized for performance and accuracy.
AI Search Flow Builder for Amazon OpenSearch Service
Amazon OpenSearch Service now provides an AI search flow builder for OpenSearch 2.19+ domains, empowering users to create sophisticated AI-enhanced search flows with a low-code designer. This visual tool allows users to seamlessly integrate AWS and third-party services to build custom search experiences that leverage the power of artificial intelligence.
The low-code designer simplifies the process of creating complex search flows, allowing users to visually connect different components and configure their behavior. The tool supports various use cases, including RAG, query rewriting, and semantic encoding, enabling users to tailor their search experiences to meet their specific needs.
The AI search flow builder streamlines the development of AI-powered search applications, making it easier for users to leverage the power of artificial intelligence to improve the accuracy, relevance, and user experience of their search solutions. The tool supports a wide range of AWS and third-party services, providing users with the flexibility to build custom search flows that meet their unique requirements.
Community Contributions
Here are some of the most interesting posts from community.aws:
How to Generate AWS Architecture Diagrams Using Amazon Q CLI and MCP: Omshree Butani demonstrates how to rapidly generate AWS Architecture Diagrams using Amazon Q CLI and Model Context Protocol (MCP), streamlining the architecture design process. This is especially helpful for visualizing and communicating complex system designs.
Implementing Nova Act MCP Server on ECS Fargate: Vivek V details the implementation of an Amazon Nova Act Model Context Protocol (MCP) server on ECS Fargate for browser automation. The solution includes architecture designs, deployment strategies, server/client implementation, Streamlit UI, AWS CDK infrastructure, and VS Code integration. This post provides a detailed guide for those looking to automate browser-based tasks using AWS services.
Leveraging Crossplane to build single-tenant SaaS control planes on top of Kubernetes: Yehuda Cohen explores the use of Crossplane to build single-tenant SaaS control planes on Kubernetes. The article highlights how Crossplane extends Kubernetes’ declarative model to manage non-Kubernetes resources, enabling automated tenant provisioning and scalable cloud resource management. This is a valuable resource for SaaS providers aiming to streamline their infrastructure management.
How to Securely Display Objects from an S3 Bucket in a Browser: Osabutey-Anikon Theeophilus Lloyd shares techniques for securely displaying objects from Amazon S3 buckets in web browsers, focusing on proper security measures for browser-based access. This is essential for ensuring data security when providing browser-based access to S3 objects.
Upcoming AWS Events
Mark your calendars for these upcoming AWS events:
AWS Summit: Join free online and in-person events to connect, collaborate, and learn about AWS. Register for events in:
- Poland (May 6)
- Bengaluru (May 7 – 8)
- Hong Kong (May 8)
- Seoul (May 14-15)
- Singapore (May 29)
- Sydney (June 4–5)
AWS re:Inforce: Taking place from June 16–18 in Philadelphia, PA, AWS re:Inforce is a learning conference focused on AWS security solutions, cloud security, compliance, and identity. Subscribe for event updates.
AWS Partners Events: A range of AWS Partner events areavailable to inspire and educate, whether you are starting your cloud journey or solving new business challenges.
AWS Community Days: Community-led conferences feature technical discussions, workshops, and hands-on labs led by expert AWS users and industry leaders. Events include:
- Yerevan, Armenia (May 24)
- Zurich, Switzerland (May 25)
- Bengaluru, India (May 25)
Browse all upcoming in-person and virtual events.
That’s all for this week’s roundup. Stay tuned for another update next Monday!