AWS Compute Blog

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AWS Lambda introduces tiered pricing for Amazon CloudWatch logs and additional logging destinations

Effective logging is an important part of an observability strategy when building serverless applications using AWS Lambda. Lambda automatically captures and sends logs to Amazon CloudWatch Logs. This allows you to focus on building application logic rather than setting up logging infrastructure and allows operators to troubleshoot failures and performance issues more easily. On May […]

Optimizing cold start performance of AWS Lambda using advanced priming strategies with SnapStart

Introduced at re:Invent 2022, SnapStart is a performance optimization that makes it easier to build highly responsive and scalable applications using AWS Lambda. The largest contributor to startup latency (often referred to as cold-start time) is the time spent initializing a function. This post discusses ‘Priming’, a technique to further optimize startup times for AWS Lambda functions built using Java and Spring Boot.

AWS Lambda standardizes billing for INIT Phase

Effective August 1, 2025, AWS will standardize billing for the initialization (INIT) phase across all AWS Lambda function configurations. This change specifically affects on-demand invocations of Lambda functions packaged as ZIP files that use managed runtimes, for which the INIT phase duration was previously unbilled. This update standardizes billing of the INIT phase across all runtime types, deployment packages, and invocation modes. In this post, we discuss the Lambda Function Lifecycle and upcoming changes to INIT phase billing. You will learn what happens in the INIT phase and when it occurs, how to monitor your INIT phase duration, and strategies to optimize this phase and minimize costs.

Streamlining trace sampling behavior for AWS Lambda functions with AWS X-Ray

This post explores the importance of distributed tracing for operating serverless applications and announces an important update to tracing behavior for AWS Lambda, which streamlines how trace context is handled in PassThrough mode. This blog post will demonstrate how this change gives you better control over how your Lambda functions handle tracing with AWS X-Ray through practical examples. Whether you’re building new applications or operating existing ones, this update helps you achieve more predictable and efficient tracing across your serverless applications built using Lambda.

Changing a function to Node.js 22

Node.js 22 runtime now available in AWS Lambda

This post is written by Julian Wood, Principal Developer Advocate, and Andrea Amorosi, Senior SA Engineer. You can now develop AWS Lambda functions using the Node.js 22 runtime, which is in active LTS status and ready for production use. Node.js 22 includes a number of additions to the language, including require()ing ES modules, as well as changes to the runtime […]

Changing a function to Python 3.13

Python 3.13 runtime now available in AWS Lambda

This post is written by Julian Wood, Principal Developer Advocate, and Leandro Cavalcante Damascena, Senior Solutions Architect Engineer. AWS Lambda now supports Python 3.13 as both a managed runtime and container base image. Python is a popular language for building serverless applications. The Python 3.13 release includes a number of changes to the language, the implementation, and the […]

Viewing function code in the Lambda Code Editor

Introducing an enhanced in-console editing experience for AWS Lambda

AWS Lambda is introducing a new code editing experience in the AWS console based on the popular Code-OSS, Visual Studio Code Open Source code editor. This brings the familiar Visual Studio Code interface and many of the features directly into the Lambda console, allowing developers to use their preferred coding environment and tools in the cloud. […]