Category: Serverless

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.

In this post, we explore how to optimize processing array data embedded within complex JSON structures using AWS Step Functions Distributed Map. You’ll learn how to use ItemsPointer to reduce the complexity of your state machine definitions, create more flexible workflow designs, and streamline your data processing pipelines—all without writing additional transformation code or AWS Lambda functions.

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 […]

In this post, you’ll learn how to process Amazon S3 objects at scale with the new AWS Step Functions Distributed Map S3 prefix and transformation capabilities.

You can use AWS Step Functions to orchestrate complex business problems. However, as workflows grow and evolve, you can find yourself grappling with monolithic state machines that become increasingly difficult to maintain and update. In this post, we show you strategies for decomposing large Step Functions workflows into modular, maintainable components.

In this post, you learn how to implement blue/green deployments by using Amazon API Gateway for your APIs. For this post, we use AWS Lambda functions on the backend. However, you can follow the same strategy for other backend implementations of the APIs. All the required infrastructure is deployed by using AWS Serverless Application Model (AWS SAM).

Welcome to the 30th edition of the AWS Serverless ICYMI (in case you missed it) quarterly recap. At the end of a quarter, we share the most recent product launches, feature enhancements, blog posts, videos, live streams, and other interesting things that you might have missed! In case you missed our last ICYMI, check out […]

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.

In this post, we show how to use Step Functions Distributed Map to process Amazon S3 objects and export results to Amazon S3 Tables, creating a scalable and maintainable data processing pipeline.