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Answer: Create a logs-based metric in Stackdriver Logging and a dashboard for that metric in Stackdriver Monitoring.
To visualize how often a cache miss happens over time, the most effective approach is to create a logs-based metric in Stackdriver Logging for the cache miss entries and then use Stackdriver Monitoring to create a dashboard for that metric. This allows for real-time monitoring and visualization of cache misses over time. Option A suggests using Google Data Studio, which is more for business intelligence and not as suited for real-time monitoring as Stackdriver Monitoring. Option B's suggestion to use Stackdriver Profiler is incorrect because Profiler is used for profiling application performance, not for monitoring log entries. Option D involves using BigQuery, which is more for data analysis and not as efficient for real-time visualization as Stackdriver Monitoring. Therefore, the correct answer is C.
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How can you visualize the frequency of cache misses over time for an application that logs each cache miss event in Stackdriver Logging?
A
Link Stackdriver Logging as a source in Google Data Studio. Filter the logs on the cache misses.
B
Configure Stackdriver Profiler to identify and visualize when the cache misses occur based on the logs.
C
Create a logs-based metric in Stackdriver Logging and a dashboard for that metric in Stackdriver Monitoring.
D
Configure BigQuery as a sink for Stackdriver Logging. Create a scheduled query to filter the cache miss logs and write them to a separate table.