With the recent end of life for version 1.32 and the support for 1.33 ending soon, upgrading feels like a constant challenge. I'm curious about how others are managing to keep up with upgrades to avoid those costly "Extended Support" fees. A lot of folks I know use tools to identify deprecated APIs and version gaps—seems like Pluto, kubent, and korpro.io are the go-to options. But when it comes to tracking those changes, are most people still relying on spreadsheets, or are there better ways to automate this process as we head into 2026?
5 Answers
I totally get where you're coming from; keeping up with these upgrades is like having a part-time job! We have set up a bi-annual upgrade strategy. We start by pushing changes to our development environment, let it sit for a couple of weeks, then move to staging for another week, and finally push to production. We always read the breaking changes from AWS and check their docs for any compatibility issues too. Giving it some time in development helps us avoid issues with our ops packages like velero and datadog.
Yeah, it’s definitely a challenge! We stick to straightforward methods. Just a couple upgrades a year, and using spreadsheets for tracking hasn't let us down. Curious if there are better tools out there, though!
All my clusters follow the same basic setup. I run depreciation checks and research any compatibility issues before deploying to lower environments. We usually jump 2-3 versions during our bi-annual upgrade sessions—it takes anywhere from a few hours to a couple of days. Most non-CNI related issues are pretty manageable!
Honestly, upgrades? Pfft! Unless there's a major vulnerability or a pressing need, we let things be. Why fix what's not broken, right?
I try to stay clear of third-party controllers and CRDs unless absolutely necessary. I pick a stable release channel and let GKE handle auto-upgrades for the clusters. It takes a lot of the stress out of the process!

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