Introducing Amazon SageMaker HyperPod Inference Gateway | Amazon Web Services
Eliminate GPU waste. Reduce first-token latency by up to 82%. Install one Kubernetes-native addon with zero application changes.
The problem: Naive routing wastes your most expensive resource
Running large language models (LLMs) at scale on GPU clusters is expensive. The default Kubernetes load balancers are making it worse. Round-robin and least-connections algorithms have no visibility into what’s happening inside your GPUs: which pods have saturated KV caches, which are mid-way through long-context generations, or which already have the LoRA adapter your request needs loaded in memory.
The result? Round-robin routing causes requests to pile up behind busy pods while idle capacity remains unused. First-token latency spikes to 4+ seconds during traffic bursts. GPU utilization becomes uneven and unpredictable. You over-provision to compensate. This burns money on GPUs that aren’t doing useful work.
The solution: SageMaker HyperPod Inference Gateway
Today, we’re excited to announce Amazon SageMaker HyperPod Inference Gateway. It is...
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