This post explores building a highly available multi-cluster AI inference gateway on Google Cloud using GKE, TPUs, and managed DRANET for cross-regional deployment.
- •Uses GKE's managed DRANET to enable resource sharing and networking across TPU nodes in multiple regions
- •Multi-cluster Inference Gateway load-balances AI workloads across clusters with automatic failover when one region fails
- •Leverages Cloud Storage FUSE to provide centralized LLM model storage accessible from all clusters
- •Implements cross-region traffic routing that prioritizes the geographically nearest healthy cluster
- •Requires quota provisioning, static IP reservations, VPC setup, and Kubernetes Workload Identity configuration
This summary was automatically generated by AI based on the original article and may not be fully accurate.