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Google announces the preview of multi-cluster GKE Inference Gateway for scalable AI/ML inference workloads across multiple GKE clusters and regions.
•Single-cluster deployments face limitations including regional outage risks, GPU/TPU hardware caps, resource silos, and high latency for distant users
•Multi-cluster Inference Gateway enables intelligent, model-aware load balancing with automatic traffic rerouting on cluster or region failures
•GCPBackendPolicy allows load balancing based on real-time custom metrics such as KV cache utilization or in-flight request counts
•Two core resources, InferencePool and InferenceObjective, manage backend pod groups and model routing priorities respectively
•A dedicated config cluster holds Gateway and HTTPRoute resources, while target clusters run model servers exposed as GCPInferencePoolImport resources
This summary was automatically generated by AI based on the original article and may not be fully accurate.
Google Cloud