Your company runs services by using multiple globally distributed Google Kubernetes Engine (GKE) clusters. Your operations team has set up workload monitoring that uses Prometheus-based tooling for metrics, alerts, and generating dashboards. This setup does not provide a method to view metrics globally across all clusters. You need to implement a scalable solution to support global Prometheus querying and minimize management overhead. What should you do?

QuestionsCategory: Google Professional Cloud DevOps EngineerYour company runs services by using multiple globally distributed Google Kubernetes Engine (GKE) clusters. Your operations team has set up workload monitoring that uses Prometheus-based tooling for metrics, alerts, and generating dashboards. This setup does not provide a method to view metrics globally across all clusters. You need to implement a scalable solution to support global Prometheus querying and minimize management overhead. What should you do?
Admin Staff asked 4 months ago
Your company runs services by using multiple globally distributed Google Kubernetes Engine (GKE) clusters. Your operations team has set up workload monitoring that uses Prometheus-based tooling for metrics, alerts, and generating dashboards. This setup does not provide a method to view metrics globally across all clusters. You need to implement a scalable solution to support global Prometheus querying and minimize management overhead. What should you do?

A. Configure Prometheus cross-service federation for centralized data access.

B. Configure workload metrics within Cloud Operations for GKE.

C. Configure Prometheus hierarchical federation for centralized data access.

D. Configure Google Cloud Managed Service for Prometheus.








 

Correct Answer: A

This question is in Google Professional Cloud DevOps Engineer Exam
For getting Google Professional Cloud DevOps Certificate

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