Category: AWS Lambda

Today, AWS Lambda is promoting Rust support from Experimental to Generally Available. This means you can now use Rust to build business-critical serverless applications, backed by AWS Support and the Lambda availability SLA.

You can now develop AWS Lambda functions using Java 25 either as a managed runtime or using the container base image. This blog post highlights notable Java language features, Java Lambda runtime updates, and how you can use the new Java 25 runtime in your serverless applications.

This post examines the benefits of transitioning Lambda functions to IPv6, provides practical guidance for implementing dual-stack support in your Lambda environment, and considerations for maintaining compatibility with existing systems during migration.

Modern serverless applications increasingly rely on event-driven architectures, where AWS Lambda functions process events from various sources like Amazon Kinesis, Amazon DynamoDB Streams, Amazon Simple Queue Service (Amazon SQS), Amazon Managed Streaming for Apache Kafka (Amazon MSK), and self-managed Apache Kafka. Although event source mappings (ESM) offer a powerful mechanism for integrating AWS Lambda with […]

Users usually package their function code as container images when using machine learning (ML) models that are larger than 250 MB, which is the Lambda deployment package size limit for zip files. In this post, we demonstrate an approach that downloads ML models directly from Amazon S3 into your function’s memory so that you can continue packaging your function code using zip files.

Today, we’re excited to announce new capabilities that further simplify the local testing experience for Lambda functions and serverless applications through integration with LocalStack, an AWS Partner, in the AWS Toolkit for Visual Studio Code. In this post, we will show you how you can enhance your local testing experience for serverless applications with LocalStack using AWS Toolkit.

Delightful developer experience is an important part of building serverless applications efficiently, whether you’re creating an automation script or developing a complex enterprise application. While AWS Lambda has transformed modern application development in the cloud with its serverless computing model, developers spend significant time working in their local environments. They rely on familiar IDEs, debugging […]

AWS Lambda cold start latency can impact performance for latency-sensitive applications, with function initialization being the primary contributor to startup delays. Lambda SnapStart addresses this challenge by reducing cold start times from several seconds to sub-second performance for Java, Python, and .NET runtimes with minimal code changes. This post explains SnapStart’s underlying mechanisms and provides performance optimization recommendations for applications using this feature.

Imagine an AI assistant that doesn’t just respond to prompts – it reasons through goals, acts, and integrates with real-time systems. This is the promise of agentic AI. According to Gartner, by 2028 over 33% of enterprise applications will embed agentic capabilities – up from less than 1% today. While early generative AI efforts focused […]

Cold starts are an important consideration when building applications on serverless platforms. In AWS Lambda, they refer to the initialization steps that occur when a function is invoked after a period of inactivity or during rapid scale-up. While typically brief and infrequent, cold starts can introduce additional latency, making it essential to understand them, especially […]