ExamTopics Logo
Mail Us[email protected]
Menu
Google Discussions
exam questions

Exam Professional Cloud Developer All Questions

View all questions & answers for the Professional Cloud Developer exam
Go to Exam

Exam Professional Cloud Developer topic 1 question 150 discussion

Actual exam question from Google's Professional Cloud Developer
Question #: 150
Topic #: 1
[All Professional Cloud Developer Questions]

The new version of your containerized application has been tested and is ready to deploy to production on Google Kubernetes Engine. You were not able to fully load-test the new version in pre-production environments, and you need to make sure that it does not have performance problems once deployed. Your deployment must be automated. What should you do?

  • A. Use Cloud Load Balancing to slowly ramp up traffic between versions. Use Cloud Monitoring to look for performance issues.
  • B. Deploy the application via a continuous delivery pipeline using canary deployments. Use Cloud Monitoring to look for performance issues. and ramp up traffic as the metrics support it.
  • C. Deploy the application via a continuous delivery pipeline using blue/green deployments. Use Cloud Monitoring to look for performance issues, and launch fully when the metrics support it.
  • D. Deploy the application using kubectl and set the spec.updateStrategv.type to RollingUpdate. Use Cloud Monitoring to look for performance issues, and run the kubectl rollback command if there are any issues.
Show Suggested Answer Hide Answer
Suggested Answer: B 🗳️
by zellck at Dec. 16, 2022, 3:01 p.m.

Comments

Chosen Answer:
This is a voting comment (?). It is better to Upvote an existing comment if you don't have anything to add.
Switch to a voting comment New
Submit Cancel
thewalker
9 months, 3 weeks ago
Selected Answer: B
Option C involves blue/green deployments, which can be more complex and risky compared to canary deployments. With blue/green, you're swapping between two environments, and if there’s an issue with the new version, you might need to do a full rollback, which can disrupt your service. Canary deployments, on the other hand, allow you to gradually shift traffic to the new version. This way, you can closely monitor the performance and catch any issues early on without affecting all your users. Blue/green deployments are useful in some scenarios, but for this case, where you couldn’t fully load-test beforehand, a more cautious, incremental approach like canary deployments would be more effective.
upvoted 1 times
...
__rajan__
1 year, 10 months ago
Selected Answer: B
B. Deploy the application via a continuous delivery pipeline using canary deployments. Use Cloud Monitoring to look for performance issues, and ramp up traffic as the metrics support it.
upvoted 1 times
...
purushi
2 years ago
Selected Answer: B
I go with B. The key is depolyment must be automated. With canary and CI/CD pipeline in place, we can adjust the traffic based on the input from Canary users.
upvoted 1 times
...
zanhsieh
2 years, 2 months ago
Selected Answer: B
B. Automated deployment can be done with Cloud Deploy. A: No. Not relevant and I can't find documents for Cloud Load Balancing supports canary deployment. C: No. Blue / green is not possible because "not able to fully load-test the new version in pre-production environments" - either no budget or other causes. D: No. Not automated and in-place upgrade will have performance hit.
upvoted 1 times
...
closer89
2 years, 3 months ago
Selected Answer: B
deployment should be automated https://cloud.google.com/deploy/docs/deployment-strategies/canary#types_of_canary
upvoted 3 times
...
Teraflow
2 years, 4 months ago
Selected Answer: B
B. Deploy the application via a continuous delivery pipeline using canary deployments. Use Cloud Monitoring to look for performance issues, and ramp up traffic as the metrics support it. Canary deployment strategy can be used to mitigate risk in the production deployment process. In this strategy, a small subset of traffic is routed to the new version of the application, while the rest of the traffic is sent to the current version. This allows for real-time monitoring of the new version's performance before fully rolling it out to all users. If there are any issues or performance problems, the traffic can be immediately routed back to the previous version. Cloud Monitoring can be used to monitor performance metrics and make informed decisions about when to ramp up traffic to the new version
upvoted 3 times
...
Pime13
2 years, 5 months ago
Selected Answer: D
i'd choose d.
upvoted 1 times
...
omermahgoub
2 years, 7 months ago
Selected Answer: A
Based on the link provided by the guys on the comments, after reviewing the links, I can see that Option A "Use Cloud Load Balancing to slowly ramp up traffic between versions. Use Cloud Monitoring to look for performance issues" is a good approach, using Cloud Load Balancing, traffic is gradually shifted between the versions, and by using Cloud monitoring, you can detect any performance issues early on.
upvoted 1 times
closer89
2 years, 3 months ago
deployment should be automated
upvoted 1 times
...
omermahgoub
2 years, 7 months ago
Option C "Deploy the application via a continuous delivery pipeline using blue/green deployments. Use Cloud Monitoring to look for performance issues, and launch fully when the metrics support it" is also a good approach, as it allows you to test the new version of the application on a production-like environment and compare it against the previous version using real traffic, and once the metrics are good, switch all traffic to the new version. Option D "Deploy the application using kubectl and set the spec.updateStrategy.type to RollingUpdate. Use Cloud Monitoring to look for performance issues, and run the kubectl rollback command if there are any issues" is also a good option, in this case as well you are incrementally rolling out the new version, and monitoring its performance, if any issues occur, you can roll back the update.
upvoted 1 times
omermahgoub
2 years, 7 months ago
Ultimately, the approach you choose will depend on the specifics of your application and infrastructure, but any of these options can work well if implemented correctly.
upvoted 1 times
...
...
...
TNT87
2 years, 7 months ago
Selected Answer: D
Answer D https://kubernetes.io/docs/tutorials/kubernetes-basics/update/update-intro/ https://cloud.google.com/kubernetes-engine/docs/how-to/updating-apps#overview Kindly master the requirements of the question, and be very aware of the question's key words
upvoted 2 times
Kadhem
1 year, 8 months ago
deployment shouldn't be automated ?
upvoted 1 times
...
...
TNT87
2 years, 7 months ago
https://kubernetes.io/docs/tutorials/kubernetes-basics/update/update-intro/ https://cloud.google.com/kubernetes-engine/docs/how-to/updating-apps#overview Answer D. The rest need testing before...
upvoted 2 times
...
zellck
2 years, 7 months ago
Selected Answer: C
C is the answer. https://cloud.google.com/architecture/implementing-deployment-and-testing-strategies-on-gke#perform_a_bluegreen_deployment
upvoted 1 times
...
Community vote distribution
A (35%)
C (25%)
B (20%)
Other
Most Voted
A voting comment increases the vote count for the chosen answer by one.

Upvoting a comment with a selected answer will also increase the vote count towards that answer by one. So if you see a comment that you already agree with, you can upvote it instead of posting a new comment.

SaveCancel