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Answer: Use Istio to create a service mesh that includes the microservices on GKE and the on-premises services
The latency issues caused by fluctuating bandwidth can lead to request timeouts and application crashes. Option B (using Istio) is the correct approach because a service mesh can manage traffic more effectively by implementing retries, timeouts, and circuit breakers. These features make the application resilient to temporary network issues, reducing the likelihood of crashes. Other options are less viable: Option A risks violating regulatory requirements by caching PII in the cloud, Option C (more VPN tunnels) does not directly address latency caused by fluctuating bandwidth, and Option D (lowering MTU) is unrelated to bandwidth-related latency.
Author: LeetQuiz Editorial Team
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After migrating an on-premises monolithic application to microservices on Google Kubernetes Engine (GKE), the application depends on backend services (including a CRM system and a MySQL database with PII) that must remain on-premises for compliance. A Cloud VPN connects the on-premises data center to Google Cloud, but latency issues from fluctuating bandwidth are causing failed requests and application crashes. How can you resolve the latency problems?
A
Use Memorystore to cache frequently accessed PII data from the on-premises MySQL database
B
Use Istio to create a service mesh that includes the microservices on GKE and the on-premises services
C
Increase the number of Cloud VPN tunnels for the connection between Google Cloud and the on-premises services
D
Decrease the network layer packet size by decreasing the Maximum Transmission Unit (MTU) value from its default value on Cloud VPN
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