Netflix’s Secret to Safe Automation at Scale • Aubrey Chipman & Roberto Perez Alcolea • GOTO 2025

This presentation was recorded at GOTO Copenhagen 2025. #GOTOcon #GOTOcph
https://gotocph.com

Aubrey Chipman - Senior Engineer at Netflix
Roberto Pérez Alcolea - Software Engineer at Netflix @robertoperezalcolea3731 

ORIGINAL TALK TITLE
From Lag to Lightning: Confident, Automated Changes at Scale

RESOURCES
Aubrey
https://twitter.com/AubreyChipman
https://www.linkedin.com/in/aubreychipman

Roberto
https://bsky.app/profile/rpalcolea.bsky.social
https://hachyderm.io/@rpalcolea
https://twitter.com/rpalcolea
https://github.com/rpalcolea
https://www.linkedin.com/in/robertoperezalcolea
http://rpalcolea.github.io

Links
https://www.sonatype.com/state-of-the-software-supply-chain/introduction
https://inside.java/2023/03/21/the-arrival-of-java-20
https://docs.openrewrite.org
https://medium.com/@rohanguptatx/sourcegraph-the-future-of-big-code-1de9adbeca36
https://git-scm.com/book/en/v2
https://github.com/nebula-plugins/gradle-resolution-rules-plugin
https://medium.com/contino-engineering/knowthe-testing-pyramid-42a4b3573988

ABSTRACT
How do you confidently deploy automated changes—such as dependency updates—across thousands of repositories, in hours instead of weeks?
At Netflix, we've reimagined the way code changes and dependency updates are delivered—swiftly, safely, and at scale. In this talk, we’ll share how we reimagined our approach to automated changes at scale, blending technical innovation with a focus on developer trust and safety.

We’ll dive into the systems and strategies that enabled us to move from manual, slow updates to a fully automated, zero-touch process. Key to this transformation were advanced dependency management resolution rules, automated SCM changes, and comprehensive artifact observability, allowing us to track and validate every change across a vast codebase.

But automating at scale only works if engineers are confident in the process. Drawing from Netflix’s experience, we’ll explore how sharing validation results, feedback loops, and impact analysis data builds trust in automation—empowering teams to embrace rapid, platform-driven changes.
We’ll discuss how shifting verification left, providing developer self-service insights, and analyzing failure impacts enable both high velocity and robust quality, even as the number of automated changes grows.

Finally, we’ll highlight future directions—such as language-agnostic tooling and proactive security measures—offering practical takeaways for any organization looking to accelerate and scale their automated change management with confidence. [...]

TIMECODES
00:00 Intro
05:00 Example: Delivering code is hard
06:51 How to improve delivering changes at scale?
07:39 Build options – Paved path
10:57 What about transitive dependencies?
17:07 Artifact observability
21:17 Distributed refactoring
24:30 Code changes are crafted with many tools
25:17 Continuous delivery
28:43 Testing & validation
35:46 Shift left testing
42:18 Better artifact observability
42:53 Recap
43:42 Takeaways
44:24 Outro

Download slides and read the full abstract here:
https://gotocph.com/2025/sessions/3733

RECOMMENDED BOOKS
Nora Jones & Casey Rosenthal • Chaos Engineering • https://www.verica.io/book
Nora Jones & Casey Rosenthal • Chaos Engineering • https://amzn.to/3hUmuAH
Aaron Rinehart • Security Chaos Engineering • https://www.verica.io/sce-book
Mikolaj Pawlikowski • Chaos Engineering • https://amzn.to/2SQ5Olf
Russ Miles • Learning Chaos Engineering • https://amzn.to/3hCiUe8
Murphy, Beyer, Jones & Petoff • Site Reliability Engineering • https://amzn.to/2Vg6Mbr

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