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Answer: Construct a dashboard featuring a custom metric for latency per instance, and employ the Aggregations tab to filter data by region, zone, and instance type.
Creating a dashboard with a custom metric to monitor latency per instance and using the Aggregations tab for filtering by region, zone, and instance type is the most effective approach. This method directly addresses the latency issue by allowing targeted analysis. Other options either focus on unrelated metrics or employ less efficient methods for the task at hand.
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As a DevOps Engineer, you're using Google Cloud's Metrics Explorer to analyze your company's application performance and notice a sudden spike in latency. What's the most effective method to pinpoint the cause of this issue?
A
Utilize Metrics Explorer to find a pre-existing metric such as 'compute.googleapis.com/instance/cpu/utilization' and apply filters by region, zone, and instance type.
B
Develop a custom metric to track latency per instance, then leverage Stackdriver Logging to sift through logs, filtering by region, zone, and instance type.
C
Construct a dashboard featuring a custom metric for latency per instance, and employ the Aggregations tab to filter data by region, zone, and instance type.
D
Search for a pre-existing metric like 'instance/network/received_packets_count' in Metrics Explorer and filter by region, zone, and instance type.