How should HipLocal redesign their architecture to ensure the application scales to support a significant increase in users while meeting business and technical requirements?

Key considerations:

Replace the single-instance MySQL database with a globally scalable solution (e.g., Cloud Spanner or sharded Cloud SQL).

Migrate APIs from Compute Engine to a managed service like Google Kubernetes Engine (GKE) or Cloud Run for autoscaling.

Implement distributed logging (Cloud Logging) and monitoring (Cloud Monitoring) with actionable alerts.

Adopt CI/CD pipelines (e.g., Cloud Build) to automate deployments and reduce manual intervention.

Use global load balancing (Cloud Load Balancing) and CDN (Cloud CDN) to ensure low-latency access across regions.

Enforce SLIs/SLOs and regional compliance (e.g., data residency via Firestore or Spanner configurations).

Integrate authentication/authorization (Identity-Aware Proxy, Firebase Auth) and secure communication (VPC peering/TLS).

Leverage Pub/Sub or Eventarc for asynchronous processing to handle spikes in demand.

Exam-Like

Use Google Kubernetes Engine (GKE) to run the application as a microservice. Run the MySQL database on a dedicated GKE node.

16.7%

Use multiple Compute Engine instances to run MySQL to store state information. Use a Google Cloud-managed load balancer to distribute the load between instances. Use managed instance groups for scaling.

11.9%

Use Memorystore to store session information and CloudSQL to store state information. Use a Google Cloud-managed load balancer to distribute the load between instances. Use managed instance groups for scaling.

66.7%

Use a Cloud Storage bucket to serve the application as a static website, and use another Cloud Storage bucket to store user state information.

4.8%

Google Professional Cloud Developer

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