Exam Professional Cloud DevOps Engineer topic 1 question 61 discussion

Correct Answer is D: Scaling App Engine scales the number of instances automatically in response to processing volume. This scaling factors in the automatic_scaling settings that are provided on a per-version basis in the configuration file. A service with basic scaling is configured by setting the maximum number of instances in the max_instances parameter of the basic_scaling setting. The number of live instances scales with the processing volume. You configure the number of instances of each version in that service's configuration file. The number of instances usually corresponds to the size of a dataset being held in memory or the desired throughput for offline work. You can adjust the number of instances of a manually-scaled version very quickly, without stopping instances that are currently running, using the Modules API set_num_instances function. https://cloud.google.com/appengine/docs/standard/python/how-instances-are-managed

D is correct - https://cloud.google.com/appengine/docs/standard/python/config/appref max_idle_instances Optional. The maximum number of idle instances that App Engine should maintain for this version. Specify a value from 1 to 1000. If not specified, the default value is automatic, which means App Engine will manage the number of idle instances. Keep the following in mind: A high maximum reduces the number of idle instances more gradually when load levels return to normal after a spike. This helps your application maintain steady performance through fluctuations in request load, but also raises the number of idle instances (and consequent running costs) during such periods of heavy load.

https://cloud.google.com/appengine/docs/legacy/standard/python/config/appref#scaling_elements:~:text=traffic%20or%20not.-,max_idle_instances,-Optional.%20The%20maximum

Option D

D. Modify the App Engine configuration to have additional idle instances. This will ensure that there are enough resources available to handle the spike in traffic, reducing the likelihood of latency for users. Additionally, you may also consider enabling high availability on the CloudSQL instances and upgrading the GCS buckets to Multi-Regional for more resiliency.

D, no brainer. A B and C don't even make sense.

Vote for D

D is correct

D is the answer

D is the answer

D looks like the nearest correct solution though this will not address with high latency with CloudSQL & storage instances

D is correct to me. A: wrong – because increase in latency for all user requests, not for specific region. So B: wrong – problem affects both database and GCS C: wrong increase in CPU use, and the number of processes running the application => problem is that CPU is not enough to run application processes.

B could be useful but does not solve latency problem on Cloud Storage side

Ans B https://cloud.google.com/sql/docs/mysql/high-availability

A. Upgrade the GCS buckets to Multi-Regional. B. Enable high availability on the CloudSQL instances. C. Move the application from App Engine to Compute Engine. D. Modify the App Engine configuration to have additional idle instances. There is nothing in the question that talks about region. If I assume that bucket is created in the region where the app is deployed B - Gives redundancy. I don't see how this can improve the latency C - Does not make any sense D - Additional instance, would reduce the CPU Time & memory. I would go with D. But not too sure.