Help on understanding mlops tools.

This page summarizes the projects mentioned and recommended in the original post on /r/mlops

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  • metaflow

    :rocket: Build and manage real-life ML, AI, and data science projects with ease!

  • Reading up on TFX (https://www.tensorflow.org/tfx/guide): it is written in python and thus (IMO) cannot cover infrastructure aspects. I feel that it somewhat compares to Metaflow (https://metaflow.org/). As I have read more about Metaflow than TFX I'll keep going with Metaflow. It's a python sdk to streamline your ml pipeline wrapping your python annotated code in nodes of a DAG that can be scheduled on your infrastructure (see: https://admin-docs.metaflow.org/metaflow-on-aws/deployment-guide/manual-deployment).

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    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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