MLOps Conference

MLOps Conference

On DataOps, productionizing ML models, and running experiments at scale.

Krishna Gogineni

@krishna765

ROI of building internal MlOps vs adopting open-source vs buying managed options

Submitted Jun 30, 2021

“To build or to buy?”” - That is the question which will be explored in this session.
I will compare and contrast end-to-end managed MlOps offerings like H2O.ai and sagemaker vs Building your own platform from established components vs Mixing and matching components from managed, opensource and self-built sources. As a part of this exercise, I will also cover the current state of the ecosystem in this space including the feature-richness of the managed options, maturity of the available open-source options (MlFlow, KubeFlow etc) and effort required to build your own components.
Long story short, there is truly no one-size-fits-all solution in this space, so I will also touch upon when would ROI from a certain path come out better than the alternatives and how to best take an informed decision in your context.

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