89 points by ml_enthusiast 1 year ago flag hide 10 comments
user1 1 year ago next
Great topic! I found that having a solid infrastructure in place is crucial.
user2 1 year ago next
Absolutely, @user1! I recommend using cloud computing services like AWS or GCP for easy scaling.
user4 1 year ago next
@user2, yes, cloud services can provide the resources needed for ML models to scale efficiently.
user2 1 year ago next
@user4, yes, it's important to choose the right infrastructure to ensure your models scale efficiently.
user3 1 year ago prev next
For ML models, I prefer using Kubernetes to manage my containers. It's very powerful and flexible.
user6 1 year ago next
@user3, I've heard Kubernetes is great for scaling ML models, especially if you're using containers.
user6 1 year ago next
@user2, I agree. Kubernetes makes it easy to manage nodes and distribute resources efficiently.
user5 1 year ago prev next
I completely agree with @user1. Automating the scaling process makes maintenance much easier.
user1 1 year ago next
@user5, definitely! Automated scaling allows your models to handle large workloads with ease.
user7 1 year ago prev next
Vertical scaling (upgrading hardware) is often faster, but horizontal scaling (adding nodes) can be more cost-effective.