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Question 258 - Professional Cloud Developer discussion

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You are monitoring a web application that is written in Go and deployed in Google Kubemetes Engine. You notice an increase in CPU and memory utilization. You need to determine which function is consuming the most CPU and memory resources. What should you do?

A.
Import the Cloud Profiler package into your application, and initialize the Profiler agent. Review the generated flame graph in the Google Cloud console to identify time-intensive functions.
Answers
A.
Import the Cloud Profiler package into your application, and initialize the Profiler agent. Review the generated flame graph in the Google Cloud console to identify time-intensive functions.
B.
Create a Cloud Logging query that gathers the web application's logs. Write a Python script that calculates the difference between the timestamps from the beginning and the end of the application's longest functions to identity time-intensive functions.
Answers
B.
Create a Cloud Logging query that gathers the web application's logs. Write a Python script that calculates the difference between the timestamps from the beginning and the end of the application's longest functions to identity time-intensive functions.
C.
Import OpenTelemetry and Trace export packages into your application, and create the trace provider. Review the latency data for your application on the Trace overview page, and identify which functions cause the most latercy.
Answers
C.
Import OpenTelemetry and Trace export packages into your application, and create the trace provider. Review the latency data for your application on the Trace overview page, and identify which functions cause the most latercy.
D.
Add print commands to the application source code to log when each function is called, and redeploy the application.
Answers
D.
Add print commands to the application source code to log when each function is called, and redeploy the application.
Suggested answer: A

Explanation:

Google Cloud Profiler efficiently analyzes cloud-based applications, like those on GKE, using minimal code changes and flame graphs for in-depth insights into CPU and memory usage, thus identifying performance bottlenecks with ease. For more information, visit: https://dev.to/billcchung/profiling-go-grpc-service-with-google-cloud-profiler-1k8l and https://www.cncf.io/blog/2020/03/27/continuous-profiling-go-application-running-in-kubernetes/

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asked 18/09/2024
John Shelby
36 questions
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