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PROFESSIONAL-CLOUD-DEVOPS-ENGINEER · Question #23

You support a web application that runs on App Engine and uses CloudSQL and Cloud Storage for data storage. After a short spike in website traffic, you notice a big increase in latency for all user…

The correct answer is D. Modify the App Engine configuration to have additional idle instances. The symptom pattern - latency persists after load normalizes, affects both CloudSQL and Cloud Storage equally, no errors, no code changes - points to App Engine instance warm-up latency, not a database or storage issue. When the traffic spike hit, App Engine scaled up by…

Submitted by lukas.cz· Apr 18, 2026Applying site reliability engineering principles to a service

Question

You support a web application that runs on App Engine and uses CloudSQL and Cloud Storage for data storage. After a short spike in website traffic, you notice a big increase in latency for all user requests, increase in CPU use, and the number of processes running the application. Initial troubleshooting reveals: - After the initial spike in traffic, load levels returned to normal but users still experience high latency. - Requests for content from the CloudSQL database and images from Cloud Storage show the same high latency. - No changes were made to the website around the time the latency increased. - There is no increase in the number of errors to the users. You expect another spike in website traffic in the coming days and want to make sure users don't experience latency. What should you do?

Options

  • AUpgrade the GCS buckets to Multi-Regional.
  • BEnable high availability on the CloudSQL instances.
  • CMove the application from App Engine to Compute Engine.
  • DModify the App Engine configuration to have additional idle instances.

How the community answered

(18 responses)
  • A
    17% (3)
  • B
    6% (1)
  • C
    6% (1)
  • D
    72% (13)

Explanation

The symptom pattern - latency persists after load normalizes, affects both CloudSQL and Cloud Storage equally, no errors, no code changes - points to App Engine instance warm-up latency, not a database or storage issue. When the traffic spike hit, App Engine scaled up by spawning new instances, but those new instances had cold-start overhead. To prevent this before the next spike, configuring 'min_idle_instances' keeps pre-warmed instances alive and ready, eliminating the latency from cold starts. Options A and B target storage/database HA, which are unrelated to the observed cross-service latency. Option C (moving to Compute Engine) increases management overhead without solving the root cause.

Topics

#App Engine Scaling#Performance Optimization#Latency Reduction#Traffic Management

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