Exam Professional Cloud Architect topic 1 question 199 discussion

C. Change the filter to metric.label.state = ‘used’. The current filter is set up with multiple AND conditions, which means it's looking for a metric that simultaneously has all these states: 'used', 'buffered', 'cached', and 'slab'. This is logically impossible, as a memory location can't be in multiple states at once. Therefore, the filter will never match any metrics, and the autoscaling policy won't trigger.

I am confused since this question comes in contrast with the answer in question 190. Anyone knows what is the real answer? I would expected used+buffered+cached+slab Which means the sum of all these.

Explanation: • Issue with the Current Filter: The filter you configured uses multiple conditions with the AND operator for states (‘used’, ‘buffered’, ‘cached’, ‘slab’). However, each time series reported by the Cloud Monitoring agent includes a single state label value. This means no single data point can satisfy all these conditions simultaneously. • Correcting the Filter: To monitor total memory usage accurately, you should only focus on the “used” memory state. Changing the filter to just metric.label.state = 'used' ensures that the autoscaler is correctly evaluating the actual used memory percentage. Once the used memory exceeds the target (80%), the autoscaler will trigger scaling. Thus, modifying the filter as in option C resolves the issue.

Autoscale based on memory usage To configure autoscaling based on the percent of used memory, specify the percent_used metric provided by the memory Ops Agent metrics. You should filter the metric by state to use only the used memory state. If you do not specify the filter, then the autoscaler takes the sum of memory usage by all memory states labeled as buffered, cached, free, slab, and used.

as it is clearly indicated in the public documentation https://cloud.google.com/compute/docs/autoscaler/scaling-cloud-monitoring-metrics#gcloud_5 you have change the filter to metric.label.state="used"