AWS Compute

Customers use AWS Lambda to build Serverless applications for a wide variety of use cases, from simple API backends to complex data processing pipelines. Lambda’s flexibility makes it an excellent choice for many workloads, and with support for up to 10,240 MB of memory, you can now tackle compute-intensive tasks that were previously challenging in a Serverless environment. When you configure a Lambda function’s memory size, you allocate RAM and Lambda automatically provides proportional CPU power. When you configure 10,240 MB, your Lambda function has access to up to 6 vCPUs.

This post is co-written with Neel Patel, Abdullahi Olaoye, Kristopher Kersten, Aniket Deshpande from NVIDIA. Today, we’re excited to announce that the NVIDIA Evo-2 NVIDIA NIM microservice are now listed in Amazon SageMaker JumpStart. You can use this launch to deploy accelerated and specialized NIM microservices to build, experiment, and responsibly scale your drug discovery

Business applications often coordinate multiple steps that need to run reliably or wait for extended periods, such as customer onboarding, payment processing, or orchestrating large language model inference. These critical processes require completion despite temporary disruptions or system failures. Developers currently spend significant time implementing mechanisms to track progress, handle failures, and manage resources when

Stay current with the latest serverless innovations that can transform your applications. In this 31st quarterly recap, discover the most impactful AWS serverless launches, features, and resources from Q4 2025 that you might have missed.

To support cloud applications that increasingly depend on rich contextual data, AWS is raising the maximum payload size from 256 KB to 1 MB for asynchronous AWS Lambda function invocations, Amazon Amazon SQS, and Amazon EventBridge. Developers can use this enhancement to build and maintain context-rich event-driven systems and reduce the need for complex workarounds such as data chunking or external large object storage.

AWS now supports multiple local gateway (LGW) routing domains on AWS Outposts racks to simplify network segmentation. Network segmentation is the practice of splitting a computer network into isolated subnetworks, or network segments. This reduces the attack surface so that if a host on one network segment is compromised, the hosts on the other network segments are not affected. Many customers in regulated industries such as manufacturing, health care and life sciences, banking, and others implement network segmentation as part of their on-premises network security standards to reduce the impact of a breach and help address compliance requirements.

Amazon Elastic Kubernetes Service (Amazon EKS) on AWS Outposts brings the power of managed Kubernetes to your on-premises infrastructure. Use Amazon EKS on Outposts rack to create hybrid cloud deployments that maintain consistent AWS experiences across environments. As organizations increasingly adopt edge computing and hybrid architectures, storage optimization and performance tuning become critical for successful workload deployment.

Amazon Web Services (AWS) Lambda now supports .NET 10 as both a managed runtime and base container image. .NET is a popular language for building serverless applications. Developers can now use the new features and enhancements in .NET when creating serverless applications on Lambda. This includes support for file-based apps to streamline your projects by implementing functions using just a single file.

In healthcare, generative AI is transforming how medical professionals analyze data, summarize clinical notes, and generate insights to improve patient outcomes. From automating medical documentation to assisting in diagnostic reasoning, large language models (LLMs) have the potential to augment clinical workflows and accelerate research. However, these innovations also introduce significant privacy, security, and intellectual property challenges.

Organizations often have large volumes of documents containing valuable information that remains locked away and unsearchable. This solution addresses the need for a scalable, automated text extraction and knowledge base pipeline that transforms static document collections into intelligent, searchable repositories for generative AI applications.

You can now develop AWS Lambda functions using Node.js 24, either as a managed runtime or using the container base image. Node.js 24 is in active LTS status and ready for production use. It is expected to be supported with security patches and bugfixes until April 2028. The Lambda runtime for Node.js 24 includes a new implementation of the

Recently we announced the availability of Amazon Elastic Compute Cloud (Amazon EC2) R8a instances, the latest addition to the AMD memory-optimized instance family. These instances are powered by the 5th Generation AMD EPYC (codename Turin) processors with a maximum frequency of 4.5 GHz. In this post I take these instances for a spin and benchmark MySQL later on, but first I discuss the top things you should know about these instances.

AWS re:Invent 2025 returns to Las Vegas, Nevada, from December 1–5, 2025. This year, we’re offering a comprehensive lineup of sessions and booth activities to help you build resilient, performant, and scalable applications wherever you need them—in the cloud, on premises, or at the edge.

Organizations running critical workloads on Amazon Elastic Compute Cloud (Amazon EC2) reserve compute capacity using On-Demand Capacity Reservations (ODCR) to have availability when needed. However, reserved capacity can intermittently sit idle during off-peak periods, between deployments, or when workloads scale down. This unused capacity represents a missed opportunity for cost optimization and resource efficiency across the organization.

Amazon Web Services (AWS) provides many mechanisms to optimize the price performance of workloads running on Amazon Elastic Compute Cloud (Amazon EC2), and the selection of the optimal infrastructure to run on can be one of the most impactful levers. When we started building the AWS Graviton processor, our goal was to optimize AWS Graviton

In this post, you will learn how the new Amazon API Gateway’s enhanced TLS security policies help you meet standards such as PCI DSS, Open Banking, and FIPS, while strengthening how your APIs handle TLS negotiation. This new capability increases your security posture without adding operational complexity, and provides you with a single, consistent way to standardize TLS configuration across your API Gateway infrastructure.

Event-driven applications often need to process data in real-time. When you use AWS Lambda to process records from Apache Kafka topics, you frequently encounter two typical requirements: you need to process very high volumes of records in close to real-time, and you want your consumers to have the ability to scale rapidly to handle traffic spikes. Achieving both necessitates understanding how Lambda consumes Kafka streams, where the potential bottlenecks are, and how to optimize configurations for high throughput and best performance.

Today, we announced Amazon API Gateway REST API’s support for private integration with Application Load Balancers (ALBs). You can use this new capability to securely expose your VPC-based applications through your REST APIs without exposing your ALBs to the public internet.

Modern generative AI applications often need to stream large language model (LLM) outputs to users in real-time. Instead of waiting for a complete response, streaming delivers partial results as they become available, which significantly improves the user experience for chat interfaces and long-running AI tasks. This post compares three serverless approaches to handle Amazon Bedrock LLM streaming on Amazon Web Services (AWS), which helps you choose the best fit for your application.

Today, AWS is announcing tenant isolation for AWS Lambda, enabling you to process function invocations in separate execution environments for each end-user or tenant invoking your Lambda function. This capability simplifies building secure multi-tenant SaaS applications by managing tenant-level compute environment isolation and request routing, allowing you to focus on core business logic rather than implementing tenant-aware compute environment isolation.