Google Exam Professional Cloud Developer Topic 14 Question 91 Discussion

Actual exam question for Google's Professional Cloud Developer exam

Question #: 91
Topic #: 14

[All Professional Cloud Developer Questions]

You are developing an online gaming platform as a microservices application on Google Kubernetes Engine (GKE). Users on social media are complaining about long loading times for certain URL requests to the application. You need to investigate performance bottlenecks in the application and identify which HTTP requests have a significantly high latency span in user requests. What should you do9

AUpdate your microservices lo log HTTP request methods and URL paths to STDOUT Use the logs router to send container logs to Cloud Logging. Create fillers in Cloud Logging to evaluate the latency of user requests across different methods and URL paths.

BInstall tcpdiimp on your GKE nodes. Run tcpdunm-- to capture network traffic over an extended period of time to collect data. Analyze the
data files using Wireshark to determine the cause of high latency

CInstrument your microservices by installing the Open Telemetry tracing package. Update your application code to send traces to Trace for inspection and analysis. Create an analysis report on Trace to analyze user requests

DConfigure GKE workload metrics using kubect1. Select all Pods to send their metrics to Cloud Monitoring. Create a custom dashboard of application metrics in Cloud Monitoring to determine performance bottlenecks of your GKE cluster.

Show Suggested Answer

Suggested Answer: D

by Rolande at Sep 07, 2024, 05:17 PM

Limited Time Offer

25%

Off

Get Premium Professional Cloud Developer Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

Submit Cancel

Jeanice

2 months ago

Hold up, where's the 'Hire a psychic' option? I bet they could just sense the performance bottlenecks and solve the problem instantly.

upvoted 0 times

...

Filiberto

2 months ago

Option B with tcpdump? That's so old-school, I thought we were beyond that in the Kubernetes era. Might as well use a telegraph to debug your application.

upvoted 0 times

Selene

26 days ago

D) Configure GKE workload metrics using kubect1. Select all Pods to send their metrics to Cloud Monitoring. Create a custom dashboard of application metrics in Cloud Monitoring to determine performance bottlenecks of your GKE cluster.

upvoted 0 times

...

Marnie

28 days ago

C) Instrument your microservices by installing the Open Telemetry tracing package. Update your application code to send traces to Trace for inspection and analysis. Create an analysis report on Trace to analyze user requests

upvoted 0 times

...

Katina

1 months ago

A) Update your microservices lo log HTTP request methods and URL paths to STDOUT Use the logs router to send container logs to Cloud Logging. Create fillers in Cloud Logging to evaluate the latency of user requests across different methods and URL paths.

upvoted 0 times

...

Ngoc

2 months ago

Configuring GKE workload metrics in Cloud Monitoring could also help us identify performance bottlenecks.

upvoted 0 times

...

Valentin

2 months ago

I think we should also consider installing the Open Telemetry tracing package to analyze user requests.

upvoted 0 times

...

Rupert

2 months ago

Hmm, option D seems the most comprehensive. Monitoring the GKE cluster metrics in Cloud Monitoring could give you a wide range of insights into the performance issues.

upvoted 0 times

...

Azalee

2 months ago

I'd go with option A. Logging is a good start, and analyzing the logs in Cloud Logging should give you a good idea of which requests are taking too long.

upvoted 0 times

Stevie

1 months ago

upvoted 0 times

...

Malcolm

1 months ago

B) Install tcpdiimp on your GKE nodes. Run tcpdunm-- to capture network traffic over an extended period of time to collect data. Analyze the data files using Wireshark to determine the cause of high latency

upvoted 0 times

...

Loreen

1 months ago

Loreen: I'd go with option A. Logging is a good start, and analyzing the logs in Cloud Logging should give you a good idea of which requests are taking too long.

upvoted 0 times

...

Giovanna

2 months ago

upvoted 0 times

...

Hyman

2 months ago

Option C sounds like the way to go. Tracing is crucial for identifying performance bottlenecks in a microservices architecture. I'm glad they mentioned Open Telemetry, it's a great tool for this.

upvoted 0 times

Ezekiel

1 months ago

Absolutely, using Open Telemetry for tracing can help pinpoint where the bottlenecks are occurring and improve the overall user experience on the gaming platform.

upvoted 0 times

...

Elden

1 months ago

I agree, tracing with Open Telemetry can provide detailed insights into the latency of user requests. It's essential for optimizing performance in a microservices environment.

upvoted 0 times

...

Kyoko

1 months ago

Option C sounds like the way to go. Tracing is crucial for identifying performance bottlenecks in a microservices architecture. I'm glad they mentioned Open Telemetry, it's a great tool for this.

upvoted 0 times

...

Golda

3 months ago

I agree with Trinidad. Using logs to evaluate latency across different methods and URL paths is a good idea.

upvoted 0 times

...

Trinidad

3 months ago

I think we should update our microservices to log HTTP requests and analyze the latency.

upvoted 0 times

...