A financial services organization is designing a high-availability architecture for its stateless payment gateway microservices on Google Cloud. The architecture must achieve a 99.99% availability SLA, support automatic multi-region failover during a regional outage, and handle unpredictable traffic bursts seamlessly. To minimize operational costs and infrastructure management overhead, which compute deployment strategy should you recommend?
- Deploy the stateless microservices to Cloud Run across multiple regions behind a global External HTTP(S) Load Balancer.Cevap
- BDeploy multi-zonal Google Kubernetes Engine (GKE) clusters in two regions with node auto-provisioning behind a global External HTTP(S) Load Balancer.
- CDeploy the microservices on Compute Engine Virtual Machines within a single regional Managed Instance Group (MIG) configured with CPU-based autoscaling.
- DDeploy Compute Engine Virtual Machines across two separate VPC networks and rely on VPC Network Peering to handle transitive cross-region application failover.
Cevap
Deploy the stateless microservices to Cloud Run across multiple regions behind a global External HTTP(S) Load Balancer.
Deploying stateless microservices to Cloud Run in multiple regions behind a global External HTTP(S) Load Balancer meets the 99.99% availability requirement with automatic cross-region failover while removing compute management overhead.
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Designing High Availability for Stateless Microservices using Cloud Run and Global Load Balancing
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