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For a moment, my eyes switched two letters and the title I read was "Reflecting on Your Fears of Databricks". I've never used their services and my company nee

by dsign 5y ago

For a moment, my eyes switched two letters and the title I read was "Reflecting on Your Fears of Databricks". I've never used their services and my company needs some MLOps, but the contents of this thread made me fear it. So, mission accomplished, dear eyes.

polynomial 5y ago
Not to put too fine a point on it, but MLflow alone isn't MLOps; moreover -and somewhat surprisingly- Databricks doesn't really do MLOps well, despite having creating one of its most useful components.
Jugurtha 5y ago
>I've never used their services and my company needs some MLOps, but the contents of this thread made me fear it. So, mission accomplished, dear eyes. I'd say I wouldn't discourage you from looking at several solutions. There's an MLOps community and they have a Slack: https://mlops.community/ https://mlops.community/ Also, a plug: I recently submitted a "Show HN: Use your own clusters to train, track, deploy, and monitor ML models (iko.ai)" https://news.ycombinator.com/item?id=28777589 https://news.ycombinator.com/item?id=28777589 https://iko.ai https://iko.ai Nothing fancy, way too small. We built it initially because we do a lot of consulting projects for enterprise clients and it took a toll on us. We either needed to hire people who knew it all (data, models, deployment, infra), or had people tapping on others' shoulders for support. Incidentally, we use MLflow for automatic experiment tracking: this means you don't need to pollute notebooks with tracking code or to learn MLflow API. We detect params, metrics, and the models itself automatically and save to S3. It's all done for multi-user, behind authentication. Anyway, my contact information is in my profile. I'd be interested in what your problems are. As I said, not a competitor of something huge like Databricks. My competitor is my colleague's laptop or a "powerful workstation with GPU" in some office.

by dsign 5y ago

polynomial 5y ago

Not to put too fine a point on it, but MLflow alone isn't MLOps; moreover -and somewhat surprisingly- Databricks doesn't really do MLOps well, despite having creating one of its most useful components.

Jugurtha 5y ago

>I've never used their services and my company needs some MLOps, but the contents of this thread made me fear it. So, mission accomplished, dear eyes. I'd say I wouldn't discourage you from looking at several solutions. There's an MLOps community and they have a Slack: https://mlops.community/ https://mlops.community/ Also, a plug: I recently submitted a "Show HN: Use your own clusters to train, track, deploy, and monitor ML models (iko.ai)" https://news.ycombinator.com/item?id=28777589 https://news.ycombinator.com/item?id=28777589 https://iko.ai https://iko.ai Nothing fancy, way too small. We built it initially because we do a lot of consulting projects for enterprise clients and it took a toll on us. We either needed to hire people who knew it all (data, models, deployment, infra), or had people tapping on others' shoulders for support. Incidentally, we use MLflow for automatic experiment tracking: this means you don't need to pollute notebooks with tracking code or to learn MLflow API. We detect params, metrics, and the models itself automatically and save to S3. It's all done for multi-user, behind authentication. Anyway, my contact information is in my profile. I'd be interested in what your problems are. As I said, not a competitor of something huge like Databricks. My competitor is my colleague's laptop or a "powerful workstation with GPU" in some office.