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Exam Professional Cloud Developer topic 1 question 221 discussion

Actual exam question from Google's Professional Cloud Developer
Question #: 221
Topic #: 1
[All Professional Cloud Developer Questions]

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

  • A. Download, install, and start the Snapshot Debugger agent in your VM. Take debug snapshots of the functions that take the longest time. Review the call stack frame, and identify the local variables at that level in the stack.
  • B. 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.
  • 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 where bottlenecks are occurring.
  • D. 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.
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Suggested Answer: B 🗳️

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__rajan__
7 months ago
Selected Answer: B
B is correct.
upvoted 1 times
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purushi
8 months, 3 weeks ago
Selected Answer: B
Focus is to find which function is more CPU and Memory intensive. Flame graphs highlights the memory intensive functions in a graphical way. B is the best answer.
upvoted 1 times
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Pime13
1 year, 2 months ago
Selected Answer: B
https://cloud.google.com/profiler/docs
upvoted 1 times
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omermahgoub
1 year, 3 months ago
Selected Answer: B
B. 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. Option B is the best solution because it involves importing the Cloud Profiler package into the application, initializing the Profiler agent, and reviewing the generated flame graph in the Google Cloud console. This will allow you to identify time-intensive functions and determine which source code is consuming the most CPU and memory resources. The flame graph is a visualization of the call stack and it can be used to identify bottlenecks in the application. Option A and C are also related to profiling but they don't exactly focus on identifying time-intensive functions. Option D is not the best option because it would be more complex and less efficient than using a profiler.
upvoted 1 times
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TNT87
1 year, 4 months ago
Selected Answer: B
https://cloud.google.com/profiler/docs/about-profiler#profiling_agent https://cloud.google.com/profiler/docs/about-profiler#environment_and_languages Answer B
upvoted 2 times
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sharath25
1 year, 4 months ago
Selected Answer: B
option B
upvoted 1 times
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zellck
1 year, 4 months ago
Selected Answer: B
B is the answer. https://cloud.google.com/profiler/docs/about-profiler Cloud Profiler is a statistical, low-overhead profiler that continuously gathers CPU usage and memory-allocation information from your production applications. It attributes that information to the source code that generated it, helping you identify the parts of your application that are consuming the most resources, and otherwise illuminating your applications performance characteristics.
upvoted 1 times
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A (35%)
C (25%)
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