Professional-Cloud-DevOps-Engineer Exam Dumps : Google Cloud Certified - Professional Cloud DevOps Engineer Exam

Roll back the experimental canary release.

Start monitoring latency, traffic, errors, and saturation.

Record data for the postmortem document of the incident.

Trace the origin of 500 errors and the root cause of increased latency.

In Cloud Monitoring, create an alerting policy based on the SLO's error budget burn rate. Configure the alert to trigger when the current consumption rate is projected to exhaust the budget before the end of the 30-day compliance period.

Create a custom dashboard in Cloud Monitoring that visualizes the SLO compliance percentage and the remaining error budget. Configure the dashboard to send a scheduled daily report through email.

Configure a log-based metric in Cloud Monitoring that tracks the rate of application error logs. Create an alerting policy on this metric that triggers when the error rate shows a significant anomalous deviation from its historical baseline.

In Metrics Explorer, create an alerting policy based on the average request latency for the application's load balancer. Configure the alert to trigger if latency exceeds a predefined threshold.

Verity the maximum node pool size, enable a horizontal pod autoscaler, and then perform a load test to verity your expected resource needs.

Because you are deployed on GKE and are using a cluster autoscaler. your GKE cluster will scale automatically, regardless of growth rate.

Because you are at only 30% utilization, you have significant headroom and you won't need to add any additional capacity for this rate of growth.

Proactively add 60% more node capacity to account for six months of 10% growth rate, and then perform a load test to make sure you have enough capacity.