Automate Lambda runtime upgrades at scale with AWS Transform custom | Amazon Web Services

Опубликовано 11 марта 2026, 14:13

If your team is spending 20–30% of its development resources on Lambda runtime upgrades, there's a better way. In this video, we walk through how AWS Transform custom uses an agentic AI approach to automate runtime modernization — from a single function all the way to hundreds across your organization.

We start with the real cost of ignoring deprecated runtimes: security exposure from unpatched vulnerabilities, missed performance gains like faster cold starts and lower costs, and the compounding technical debt that makes every upgrade harder than the last. Then we show how AWS Transform Custom addresses all of it.

The agent handles code changes, dependency updates, and validation automatically. It generates a step-by-step plan before execution, validates results against exit criteria, and learns from every run — getting more accurate over time. You can drive the entire process interactively through the CLI, run it in non-interactive batch mode using a CSV or JSON input file, or deploy a containerized execution environment with API Gateway, AWS Batch, Fargate, S3, and CloudWatch for full-scale orchestration.

The results speak for themselves. Air Canada upgraded their entire Node.js 16 to Node.js 20 Lambda fleet in just a few days, achieving a 90% efficacy rate and an 80% reduction in expected time and cost. Teams that once dedicated a significant portion of their sprint capacity to upgrade work are seeing up to 80% faster execution.

Whether you're upgrading Python, Node.js, or Java runtimes, AWS Transform custom lets you define a transformation once and apply it everywhere — with a continual learning loop that improves with every execution.

Get started with AWS Transform: go.aws/4sG8InT
Documentation: go.aws/4b423Or

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