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# announcements
s
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b
Yes. BentoML.ai is a company that started the BentoML project. The relationship is similar to Databricks to Apache Spark, and Datastax to Cassandra
p
So you (are planning to) built more advanced/user-friendly/enterprisy stuff on top of BentoML?
Anyway, I thought the project and especially the documentation is looking very good!
b
Yes, we plan offer commercial product in the future. There was a great thread that Chaoyu talked about the company and future plans. https://bentoml.slack.com/archives/CK8PQU2JY/p1598648820019600. Open-source is our core. The company's success is depended on to have a successful open source project that truly provides value to our community.
c
@Pieter Marsman yes we are building advanced enterprise features on top of the open source BentoML, is that something your team may be interested in? happy to chat more
p
Thanks! Those explanations are really helpful!
We just decided to use BentoML to wrap our models for deployment, and also be able to do offline testing with the exact same code, including pre- and post-processing.
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c
That’s awesome, let me know how it goes! Would love to hear more of your feedback and thoughts
c
Hi all! Colleague of Pieter here. Pieter started this project at out company, but is currently on holiday and I am taking over for a bit. It looks really awesome! 😄 Our manager however just asked some critical questions on how BentoML compares to the Google Cloud AI Platform. My knowledge about both the AI platform and about BentoML is not extensive enough yet to make this comparison and argue for one or another. My intuition from what I've learned so far would be that BentoML supports more ML frameworks and more diverse deployment options. Do you have any input? 🙂
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c
Hi @Cas Wognum - I actually just had a call with @Shihgian Lee about their experience migrating from Google Cloud AI platform to BentoML. In Shihgian’s words: Google Cloud API Platform has a strong opinion on how you architect your applications which introduces fragmented architecture and frictions to DevOps and Engineers who are operating those ML workloads in production. Whereas BentoML is highly modular and gives DevOps & engineers the flexibility to deploy in their own infrastructure, and integrate with existing infra tooling for monitoring, log collection, tracing, etc.
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And yes you are right, in terms of features, BentoML supports more ML frameworks and more diverse deployment options!
s
To add to Chaoyu’s comment, Google AI Platform’s first class ML library is TensorFlow. The sklearn version is very far behind. So, we could not use the predict probability function on a later version of sklearn for one of our ML algorithms. We had to copy the source from sklearn site and include it in Google AI platform. Google AI platform will improve sklearn deployment later but it is not their primary focus. We were very frustrated with Google AI Platform.
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c
Thank you guys! I really appreciate the quick response. This aligns with what I've read so far about the different platforms. I'm with Pieter! BentoML seems like the way to go! Thanks again! 👍
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