Recently wrote a step-by-step guide using the open-source ZenML (Disclaimer: I'm the co-creator). Thought it covered some nice concepts and is OSS, so the HN community would appreciate. Peace!
I mean, I don't think that's a good argument - it costs you cents per user. Either way, I think you should charge however much value users can take from the product, completely unrelated to the cost.
At the moment though, being notified whenever my github repo is trending is a nice to have that gives me nearly 0 value as there's no actions I can take from that (other than share with my team :)). So I would try to find some other way to monetize it or to bring value to the users. Sorry for the harsh feedback.
Not at all harsh! Very valuable. Tbh it was really about just trying it out for now, its very arbitrary! :-) Do you have any suggestions on what exactly you'd like to do after you find out its Trending?
Wouldn't it make sense to decouple the orchestration later from the authoring layer for the dags? That way you could solve the authoring problems separately from the lower level orchestration problems. We're trying this over at ZenML (https://zenml.io) but have yet to get feedback
ZenML is hiring for a Design Engineer | Remote-friendly | Freelancer or Employee | Full-time or Part-time
ZenML is an extensible, open-source MLOps framework to create production-ready machine learning pipelines. Built for data scientists, it has a simple, flexible syntax, is cloud- and tool-agnostic, and has interfaces/abstractions that are catered towards ML workflows.
We’re looking for a Design Engineer with a multi-disciplinary skill-set who can take over the look and feel of the ZenML experience. ZenML is a tool designed for developers and we want to delight them from the moment they land on our web page, to after they start using it on their machines. We would like a consistent design experience across our many touchpoints (including the [landing page](https://zenml.io), the [docs](https://docs.zenml.io), the [blog](https://blog.zenml.io), the [podcast](https://podcast.zenml.io), our social media, the product itself which is a [python package](https://github.com/zenml-io/zenml) etc).
A lot of this job is about communicating complex ideas in a beautiful way. You could be a developer or a non-coding designer, full time or part-time, employee or freelance. We are not so picky about the exact nature of this role. If you feel like you are a visually creative designer, and are willing to get stuck in the details of technical topics like MLOps, we can’t wait to work with you!
They are just two different solutions that have pros and cons just like any two solutions :) A few that jump out:
- Setup time: Setting up GCP, setting up a certificate, adding a static IP, etc. is not seamless/adds friction
- Autoscaling and rolling updates (no downtime)
- Team management and collaborative environment with usage tracking, permissions, etc.
- Optional integration with a pipelining service for training, tuning, deploying models in a single tool
And a point of clarification: Practically speaking, neither tool is free. Both require a cloud instance so they will cost roughly the same for the end user (Gradient also supports preemptible instances).
Hey @sabalaba, that sounds pretty interesting. Would you be willing to integrate with ZenML? https://github.com/maiot-io/zenml . We're looking for solutions like that that have synergies
Yes this is aimed at being a simpler API rather than complicated one. Also MLFlow does not orchestrate self-starting preemptible instances, so you'd have to pay the full amounts.
