The transitory nature of MLOps: Advocating for DevOps/MLOps coalescence

This page summarizes the projects mentioned and recommended in the original post on dev.to

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  • kitops

    Tools for easing the handoff between AI/ML and App/SRE teams.

  • And checkout the source code here: https://github.com/jozu-ai/kitops

  • distribution-spec

    OCI Distribution Specification

  • Back in 2013, a little company called Docker made it really easy to start using containers to package up applications. A big key to their success was the OCI (you can learn about that here), an industry wide initiative to have standards around how we package up our applications. Because of OCI standards, we have hundreds (maybe thousands?) of tools that can be combined to manage and deploy applications. So why aren’t we using this for packaging up Notebooks and AI models as well? It would make deploying, sharing, and managing our models easier for everyone involved.

  • InfluxDB

    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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