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The AWS Serverless Model Context Protocol (MCP) Server now supports specialized tools for https://aws.amazon.com/lambda/ event source mappings (ESM), helping developers configure and manage ESMs more efficiently. These new tools combine the power of AI assistance with Lambda ESM expertise to streamline how developers set up, optimize, and troubleshoot event-driven serverless applications built on Lambda. We previously launched the open-source https://aws.amazon.com/blogs/compute/introducing-aws-serverless-mcp-server-ai-powered-development-for-modern-applications/ to enhance how developers build modern applications with AI-powered contextual guidance for architecture decisions, infrastructure provisioning, deployment automation, and troubleshooting of serverless applications. Starting today, we’re expanding the MCP server’s capabilities with new ESM tools that empower AI assistants, like Amazon Q Developer and Kiro, with proven knowledge of ESM patterns and best practices. The new ESM tools translate high-level throughput, latency, and reliability requirements into specific ESM configurations, generate complete AWS Serverless Application Model (AWS SAM) templates with optimized settings, validate network topology for Amazon Virtual Private Cloud (VPC)-based event sources, and diagnose common ESM issues. Thus, these tools enhance the event-driven application development experience, guiding developers through the entire ESM lifecycle, from initial setup to optimization and troubleshooting. The key new ESM tools being added to the Serverless MCP Server are: the ESM guidance tool for contextual guidance across all supported event sources, the ESM optimization tool for analyzing configuration tradeoffs, and the ESM Kafka troubleshooting tool for specialized diagnostics with Amazon Managed Streaming for Apache Kafka (Amazon MSK) and self-managed Apache Kafka clusters. To learn more about the Serverless MCP Server and how it can transform your AI-assisted application development, visit the https://aws.amazon.com/blogs/compute/introducing-aws-lambda-event-source-mapping-tools-in-the-aws-serverless-mcp-server/ and https://awslabs.github.io/mcp/servers/aws-serverless-mcp-server/. To download and try out the open-source MCP server with your AI-enabled IDE of choice, visit the https://github.com/awslabs/mcp/tree/main/src/aws-serverless-mcp-server.

The AWS Serverless Model Context Protocol (MCP) Server now supports specialized tools for AWS Lambda event source mappings (ESM), helping developers configure and manage ESMs more efficiently. These new tools combine the power of AI assistance with Lambda ESM expertise to streamline how developers set up, optimize, and troubleshoot event-driven serverless applications built on Lambda. We previously launched the open-source Serverless MCP Server to enhance how developers build modern applications with AI-powered contextual guidance for architecture decisions, infrastructure provisioning, deployment automation, and troubleshooting of serverless applications. Starting today, we’re expanding the MCP server’s capabilities with new ESM tools that empower AI assistants, like Amazon Q Developer and Kiro, with proven knowledge of ESM patterns and best practices. The new ESM tools translate high-level throughput, latency, and reliability requirements into specific ESM configurations, generate complete AWS Serverless Application Model (AWS SAM) templates with optimized settings, validate network topology for Amazon Virtual Private Cloud (VPC)-based event sources, and diagnose common ESM issues. Thus, these tools enhance the event-driven application development experience, guiding developers through the entire ESM lifecycle, from initial setup to optimization and troubleshooting. The key new ESM tools being added to the Serverless MCP Server are: the ESM guidance tool for contextual guidance across all supported event sources, the ESM optimization tool for analyzing configuration tradeoffs, and the ESM Kafka troubleshooting tool for specialized diagnostics with Amazon Managed Streaming for Apache Kafka (Amazon MSK) and self-managed Apache Kafka clusters. To learn more about the Serverless MCP Server and how it can transform your AI-assisted application development, visit the launch blog post and documentation. To download and try out the open-source MCP server with your AI-enabled IDE of choice, visit the GitHub repository.

AWS Lambda increases asynchronous invocations maximum payload size from 256 KB to 1 MB, allowing customers to ingest richer, complex payloads for their event-driven workloads without the need to split, compress, or externalize data. Customers invoke their Lambda functions asynchronously using either Lambda API directly, or by receiving push-based events from various AWS services like Amazon S3, Amazon CloudWatch, Amazon SNS, Amazon EventBridge, AWS Step Functions. Modern cloud applications increasingly rely on AWS Lambda’s asynchronous invocations and its integration with various AWS serverless services to build scalable, event-driven architectures. These applications often need to process rich contextual data, including large-language model prompts, telemetry signals, and complex JSON structures for machine learning outputs. With increase in maximum payload size to 1MB for asynchronous invocations, developers can streamline their architectures by including comprehensive data, from detailed user profiles to complete transaction histories, in a single event, eliminating the need for complex data chunking or external storage solutions. This feature is generally available in all https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/. Customers can start sending asynchronous invocation payloads up to 1 MB using Lambda’s invoke API. Customers are charged for 1 request per each asynchronous invocation for first 256 KB. Individual payload size beyond 256 KB is charged 1 additional request for each 64 KB of chunk up to 1 MB. To learn more, read Lambda asynchronous invocation https://docs.aws.amazon.com/lambda/latest/dg/invocation-async.html and AWS Lambda https://aws.amazon.com/lambda/pricing/. 

AWS Lambda increases asynchronous invocations maximum payload size from 256 KB to 1 MB, allowing customers to ingest richer, complex payloads for their event-driven workloads without the need to split, compress, or externalize data. Customers invoke their Lambda functions asynchronously using either Lambda API directly, or by receiving push-based events from various AWS services like Amazon S3, Amazon CloudWatch, Amazon SNS, Amazon EventBridge, AWS Step Functions. Modern cloud applications increasingly rely on AWS Lambda’s asynchronous invocations and its integration with various AWS serverless services to build scalable, event-driven architectures. These applications often need to process rich contextual data, including large-language model prompts, telemetry signals, and complex JSON structures for machine learning outputs. With increase in maximum payload size to 1MB for asynchronous invocations, developers can streamline their architectures by including comprehensive data, from detailed user profiles to complete transaction histories, in a single event, eliminating the need for complex data chunking or external storage solutions. This feature is generally available in all AWS Commercial and AWS GovCloud (US) Regions. Customers can start sending asynchronous invocation payloads up to 1 MB using Lambda’s invoke API. Customers are charged for 1 request per each asynchronous invocation for first 256 KB. Individual payload size beyond 256 KB is charged 1 additional request for each 64 KB of chunk up to 1 MB. To learn more, read Lambda asynchronous invocation documentation and AWS Lambda pricing.

AWS was named as a Leader in the 2025 Gartner Magic Quadrant for Cloud-Native Application Platforms in two consecutive years positioned highest on "Ability to Execute", and for Container Management in three years positioned furthest for "Completeness of Vision".

Last week, Strands Agents, AWS open source for agentic AI SDK just hit 1 million downloads and earned 3,000+ GitHub Stars less than 4 months since launching as a preview in May 2025. With Strands Agents, you can build production-ready, multi-agent AI systems in a few lines of code. We’ve continuously improved features including support […]

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“ I have checked the documents of AWS to explore code security feature as gitlab and github source...

AWS is announcing integrated LocalStack support in the AWS Toolkit for Visual Studio Code that makes it easier than ever for developers to test and debug serverless applications locally. This enhancement builds upon our recent improvements to the Lambda development experience, including the console to IDE integration and remote debugging capabilities we launched in July 2025, continuing our commitment to simplify serverless development on AWS.

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Uncover how AWS Lambda benefits healthcare by boosting patient care, streamlining interactions, protecting data, integrating systems, and cutting costs by 92%.

AWS Lambda now offers Code Signing in GovCloud Regions (AWS GovCloud (US-West) and AWS GovCloud (US-East)), which allows administrators to ensure that only trusted and verified code is deployed to Lambda functions. This feature uses AWS Signer, a managed code signing service. When code is deployed, Lambda checks the signatures to confirm the code hasn't been altered and is signed by trusted developers. Administrators can create Signing Profiles in AWS Signer and use AWS Identity and Access Management (IAM) to manage user access. Within Lambda, they can specify allowed signing profiles for each function and configure whether to warn or reject deployments if signature checks fail. There is no extra charge for using this feature. For more details, you can refer to https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/, https://aws.amazon.com/blogs/aws/new-code-signing-a-trust-and-integrity-control-for-aws-lambda/, https://aws.amazon.com/blogs/aws/new-code-signing-a-trust-and-integrity-control-for-aws-lambda/, or https://docs.aws.amazon.com/signer/latest/developerguide/lambda-workflow.html.

AWS Lambda now offers Code Signing in GovCloud Regions (AWS GovCloud (US-West) and AWS GovCloud (US-East)), which allows administrators to ensure that only trusted and verified code is deployed to Lambda functions. This feature uses AWS Signer, a managed code signing service. When code is deployed, Lambda checks the signatures to confirm the code hasn't been altered and is signed by trusted developers. Administrators can create Signing Profiles in AWS Signer and use AWS Identity and Access Management (IAM) to manage user access. Within Lambda, they can specify allowed signing profiles for each function and configure whether to warn or reject deployments if signature checks fail. There is no extra charge for using this feature. For more details, you can refer to the AWS Region table, the AWS blog, the Lambda developer guide, or the Signer developer guide.

A Serverless API Template Generator for Server-Side Swift - swift-serverless/Breeze