metaflow-on-kubernetes-docs
kedro-great
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| metaflow-on-kubernetes-docs | kedro-great | |
|---|---|---|
| 1 | 1 | |
| 7 | 52 | |
| - | - | |
| 1.8 | 0.0 | |
| about 2 years ago | over 1 year ago | |
| Shell | Python | |
| - | MIT License |
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metaflow-on-kubernetes-docs
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[D] What’s the simplest, most lightweight but complete and 100% open source MLOps toolkit? -> MY OWN CONCLUSIONS
There are community Forks supporting Kubernetes and KFP. But they are not yet a part of the main framework and support is fluctuating. I think support should be available in the future.
kedro-great
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[D] What’s the simplest, most lightweight but complete and 100% open source MLOps toolkit? -> MY OWN CONCLUSIONS
I expected Great Expectations library to be recommended, but nobody told anything. Instead, unit testing and/or smoke tests using pytest. And checking them with Jenkins. Anyway, if Kedro ends up being our project template, I'll keep an eye on the plugin with Great Expectations.
What are some alternatives?
clearml - ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
great_expectations - Always know what to expect from your data.
metaflow - Build and manage real-life data science projects with ease.
Poetry - Python packaging and dependency management made easy
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
streamlit - Streamlit — A faster way to build and share data apps.
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
feast - Feature Store for Machine Learning
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production