43Your inference server OOMs when requests arrive with long prompts. How do you handle variable-length memory?▼hardNVIDIAOpenAITogether1 replies◆ premiumA serving box steady on short prompts falls over the instant a 30k-token request arrives, because KV-cache memory scales with sequence length times batch. Here is how to bound it without crashing.Open full answer →
54Traffic arrives in sharp bursts and your LLM p99 spikes each time. How do you absorb the bursts?▼hardOpenAIAWSNVIDIA2 replies◆ premiumAutoscaling reacts in minutes, but a burst lands in seconds, and the gap is where your tail latency dies. Absorbing bursts is about buffers and shedding, not just adding replicas. Here is the playbook.Open full answer →
