PCDOE Implementing service monitoring strategies Practice Question
A DevOps team is defining an SLO for a web application that runs on Compute Engine behind an HTTP Load Balancer. They need to measure the proportion of requests that complete within 300ms. Which Cloud Monitoring metric is most appropriate as the SLI?
⚠ Common exam trap
Google Cloud often tests the distinction between latency metrics (histogram-based) and simple counters or byte metrics, expecting candidates to recognize that only a distribution metric like `total_latencies` can compute percentile-based SLIs.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
loadbalancing.googleapis.com/https/total_latencies
The SLI must measure the proportion of requests completing within 300ms, which is a latency distribution metric. The `total_latencies` metric from the HTTP Load Balancer provides a histogram of request latencies, allowing you to compute the percentage of requests below a threshold (e.g., 300ms). This directly supports the SLO definition.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
loadbalancing.googleapis.com/https/backend_request_bytes
Why it's wrong here
This metric tracks bytes transferred, not latency.
- ✗
loadbalancing.googleapis.com/https/frontend_tcp_rtt
Why it's wrong here
This metric measures TCP round-trip time, not HTTP request latency.
- ✗
loadbalancing.googleapis.com/https/request_count
Why it's wrong here
This metric counts requests, not latency, so it cannot be used for a latency-based SLI.
- ✓
loadbalancing.googleapis.com/https/total_latencies
Why this is correct
This metric gives latency distribution, including percentiles, making it ideal for a latency SLI.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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