Ask HN: How can I monetize a load balancer for ML applications?
- You have a GPU attached to each instance.
- Each request takes anywhere from 10ms to 2min.
- There's a hard limit on the number of in-flight requests/queries (I assume because of the GPUs).
Normally, I see people fronting the instances with software load balancers, but this doesn't work very well for reasons. Assuming I have a solution in the form of a fancy load balancer, how would I go about monetizing it? Let's assume the solution is non-trivial to create, but very straightforward to use (essentially a drop-in replacement).
I ask because I don't think I can just "sell a fancy load balancer" like it's the late 90s or something. Modern companies appear to always have more complicated products and I just want to sell a straightforward piece of infrastructure that solves a fairly hard problem.
Thanks in advance.
11 comments
[ 3.7 ms ] story [ 30.8 ms ] threadWhich reasons? In my experience/exposure, people are perfectly happy with Proxmox on a big GPU-laden boxen.
Either way, I feel like these details are orthogonal to my original question. Do you think it matters?
What were the "reasons" for "doesn't work very well? aka trying to do goolgle search type work on 2mb intel 486 oover a 2mb network and expecting to be able to compete with google is never going to work out.
What type of load balancing? Load balancing typically has to be tuned/adjusted based on end usage requirements/production environment (not just per factory setting)
Your tone is coming off as condescending and I'm not sure if it's intentional. I guess I should mention that I'm _very_ familiar with how load balancing works. This is a real problem and you can't "tune" your way into a consistent global view of the backend states.
Pre-modern computing, load balancing was a telecommunications field thing. Cloud computing is the modern 'load balancing' take.
When you generalize this by saying "cloud computing", it glosses over the fact that there's still a fleet of load balancers somewhere. When you use an NLB or ALB in AWS, there are many machines behind the scene and a very complex control plane providing those machines with the information they need to balance load.
The problem I'm talking about still exists here. I _know_ they have this problem because I'm familiar with how those systems are built and I know what shortcomings they have.
Modern cloud processing has 'fees/payment' tied to scale/balancing per use requirements (not necessarily tied specifically to gpu's).