PROFESSIONAL-CLOUD-DEVELOPER · Question #195
You recently migrated an on-premises monolithic application to a microservices application on Google Kubernetes Engine (GKE). The application has dependencies on backend services on- premises, includi
The correct answer is C. Increase the number of Cloud VPN tunnels for the connection between Google Cloud and the on-. The correct answer is C: Increase the number of Cloud VPN tunnels. Cloud VPN supports up to 3 Gbps per tunnel. When bandwidth fluctuates due to traffic spikes, adding more VPN tunnels using ECMP (Equal-Cost Multi-Path routing) increases aggregate bandwidth and distributes load ac
Question
You recently migrated an on-premises monolithic application to a microservices application on Google Kubernetes Engine (GKE). The application has dependencies on backend services on- premises, including a CRM system and a MySQL database that contains personally identifiable information (PII). The backend services must remain on-premises to meet regulatory requirements. You established a Cloud VPN connection between your on-premises data center and Google Cloud. You notice that some requests from your microservices application on GKE to the backend services are failing due to latency issues caused by fluctuating bandwidth, which is causing the application to crash. How should you address the latency issues?
Options
- AUse Memorystore to cache frequently accessed PII data from the on-premises MySQL database
- BUse Istio to create a service mesh that includes the microservices on GKE and the on-premises
- CIncrease the number of Cloud VPN tunnels for the connection between Google Cloud and the on-
- DDecrease the network layer packet size by decreasing the Maximum Transmission Unit (MTU)
How the community answered
(16 responses)- A13% (2)
- C81% (13)
- D6% (1)
Explanation
The correct answer is C: Increase the number of Cloud VPN tunnels. Cloud VPN supports up to 3 Gbps per tunnel. When bandwidth fluctuates due to traffic spikes, adding more VPN tunnels using ECMP (Equal-Cost Multi-Path routing) increases aggregate bandwidth and distributes load across multiple paths, directly addressing the root cause of the latency and availability issues. Using Memorystore to cache PII data (A) would violate regulatory requirements since PII must remain on-premises; caching it in a managed cloud service moves it off-premises. Using Istio for a service mesh (B) improves observability and retry logic, but does not increase the underlying network bandwidth between on-premises and GCP. Decreasing the MTU (D) reduces packet size, which increases the number of packets and associated overhead, and would actually worsen throughput performance rather than improve it.
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