Sanity check of my decision for "Iterative AI" (DVC, MLEM, CML) pipeline over Azure ML

This page summarizes the projects mentioned and recommended in the original post on /r/mlops
Build Tool Build Tools Build system Monorepo Python

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InfluxDB - Power Real-Time Data Analytics at Scale
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  • pants

    The Pants Build System

    • We don't have the CD yet, but I think what I put in place counts as simple CI (even if incomplete)? Every push & PR trigger an azure pipeline, which runs pants. This install the dependencies from the lockfile, run some linters, uses DVC to pull the data necessary for tests, and run unit tests (mypy check is deactivated until I solve a weird error). Basically the same script runs on laptops cross-platform (one of us uses Max, one Ubuntu with GPU, one Ubuntu with CPU, the scripts runs on every platform). The only difference with CI is the installation of Pants and the gestion of Cache (needs to be downloaded in CI so it takes ~3min in CI versus 20 seconds on my laptop).

  • Scout Monitoring

    Free Django app performance insights with Scout Monitoring. Get Scout setup in minutes, and let us sweat the small stuff. A couple lines in settings.py is all you need to start monitoring your apps. Sign up for our free tier today.

    Scout Monitoring logo
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