Optimize Global Latency Caching Load Balancing

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An e-commerce platform hosts its core web application and transactional database in a single Google Cloud region (us-central1). Geographically distributed users in Europe and Asia experience high latency (Time to First Byte > 300 ms) when browsing catalog pages and loading static media assets. Additionally, repetitive database read queries during peak traffic spikes are causing high database CPU utilization and application degradation.

You need to optimize the architecture to minimize user latency at the edge and offload repetitive read queries from the central database while avoiding multi-region database replication complexity. What should you do?

Deploy a global external Application Load Balancer on Premium Tier with Cloud CDN enabled for static and cacheable web assets, and deploy Memorystore for Redis in us-central1 to cache frequent database read queries.

Deploy an external passthrough Network Load Balancer in us-central1 with Cloud CDN enabled, and implement local in-instance memory caching on each Compute Engine VM.

Deploy an external Application Load Balancer using Standard Tier networking, and configure Cloud Storage static website failover as the primary caching layer for catalog items.

Distribute frontend Compute Engine Managed Instance Groups across europe-west1 and asia-east1, configured to query the us-central1 database directly over cross-region VPC peering without a caching layer.

Professional Cloud DevOps Engineer

Optimize Global Latency Caching Load Balancing

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