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Is there any love for the Argo [1] project suite (Workflows, Events, CD) for this type of use case? I haven’t tried it out myself yet however it does look inter
by jon_adler 4y ago
Is there any love for the Argo [1] project suite (Workflows, Events, CD) for this type of use case? I haven’t tried it out myself yet however it does look interesting.
[1] https://argoproj.github.io https://argoproj.github.io
- ForHackernews 4y agoI've never used their workflows thing, but having been forced to live with ArgoCD it sounds horrifying. Argo is another over-engineered "CNCF" thing trying to ride the Kubernetes hype train. It's all "eventually consistent", which makes it extraordinarily difficult to see when any particular thing actually happened. Is my code deployed? Who knows, Argo is "syncing". Check out these great docs: https://argoproj.github.io/argo-workflows/rest-api/ https://argoproj.github.io/argo-workflows/rest-api/ > API reference docs : > Latest docs (maybe incorrect) > Interactively in the Argo Server UI.<https://localhost:2746/apidocs https://localhost:2746/apidocs> (>= v2.10) Yes, that is a localhost URL on their website.
- robertlagrant 4y agoHow do you know if anything is deployed if it hasn't come back and confirmed it's deployed? Manual only?
- ForHackernews 4y agorsync returns status code 0. ;)
- robertlagrant 4y agoWell, no-one's going to accuse that of being overengineered :D
- ricklamers 4y agoArgo is pretty amazing if you want to take advantage of the work Kubernetes has done to scale resource efficiently across a cluster of compute nodes. If you’re looking for something that’s a bit more high level and friendly to expose directly to your data team (data scientists/data engineers/data analysts) you can check out https://github.com/orchest/orchest https://github.com/orchest/orchest You can think of it as a browser UI/workbench for Argo scheduled pipelines. Disclaimer: author of the project