Hey everyone! I'm looking for some insights on managing multiple versions for various deployments, especially when different customers may be on different versions of everything. My company has about five or more Helm charts that we release independently, and each of these charts has its own versioning. On top of that, we have distinct 'appVersions' that are also separately released, along with several infrastructure components that are versioned and scheduled independently. It's getting hard to keep track of everything!
I'm even considering building a web app to help visualize and manage all these versions and release schedules because standard project management tools just don't cut it for me. Ideally, I want to see a timeline for each component that shows its current version alongside what each customer is using. I'd love to hear if you have any tips or know of existing tools that excel in tracking this kind of information!
3 Answers
Why go through the hassle of building your own solution? Tools like ArgoCD already exist to manage deployment versions efficiently. Also, Helm can be handy because it automatically handles releases, reflecting both the chart version and the parameters linked to your Docker image versions.
I've encountered similar issues. For our CI/CD process, we have a script that sends data to an API endpoint to save essential info like build times, IDs, and release details for each customer and environment. This data feeds into a dashboard that displays every service version across all customers, and it’s filterable so we can track easily. We also have a special app for developers to choose the versions and commits they want for their release plans. Once selected, those versions get tested and released through another custom application.
I had my fair share of headaches with devs labeling everything as 'new,' which led to confusion. Instead, we decided to implement a time-based tagging system combined with our GitLab pipeline numbers. Since we manage around 100 apps, tracking by app, time, and pipeline helps us diagnose deployment issues much more easily.
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