We built a serverless GPU inference platform with predictable latency5 ポイント·投稿者 QubridAI·5 か月前·1 コメントWe’ve been working on a GPU-first inference platform focused on predictable latency and cost control for production AI workloads.Some of the engineering problems we ran into:- GPU cold starts and queue scheduling - Multi-tenant isolation without wasting VRAM - Model loading vs container loading tradeoffs - Batch vs real-time inference routing - Handling burst workloads without long-term GPU reservation - Cost predictability vs autoscaling behaviorWe wrote up the architecture decisions, what failed, and what worked.Happy to answer technical questions - especially around GPU scheduling, inference optimization, and workload isolation.1 コメントコメントを投稿[–]tgrowazay·5 か月前返信Well, do you have a blog post or we need to ask about each item to get it?
Some of the engineering problems we ran into:
- GPU cold starts and queue scheduling - Multi-tenant isolation without wasting VRAM - Model loading vs container loading tradeoffs - Batch vs real-time inference routing - Handling burst workloads without long-term GPU reservation - Cost predictability vs autoscaling behavior
We wrote up the architecture decisions, what failed, and what worked.
Happy to answer technical questions - especially around GPU scheduling, inference optimization, and workload isolation.