3.2 Managing Service Lifecycle PROFESSIONAL-CLOUD-DEVOPS-ENGINEER Practice Questions (Page 4)

Questions 16–20

1. 16foundation · easy

   Which component is used to trigger autoscaling decisions?

   • AMetrics such as CPU utilization or request count
   • BDeployment strategy
   • CReservation settings
   • DQuota limits
   Reveal Solution Discussion Select an answer first
2. 17application · medium

   You run a stateful application on a GKE cluster. The application stores data on persistent volumes. You configure the Horizontal Pod Autoscaler (HPA) to scale based on CPU utilization at 70%. You also enable the cluster autoscaler. During a load test, you notice that new pods are created, but they remain in 'Pending' state for several minutes. You verify that the cluster has enough total CPU and memory resources. What is the most likely cause of the pending pods?

   • AThe cluster autoscaler has a maximum node count that is too low
   • BThe persistent volumes are in a zone that does not have enough node capacity
   • CThe cluster autoscaler is disabled for the node pool where the pods are scheduled
   • DThe HPA is scaling based on the wrong metric, so it creates pods that cannot be scheduled
   Reveal Solution Discussion Select an answer first
4. 18foundation · easy

   What is the fundamental principle of autoscaling?

   • AAutomatically adjusting the number of resources based on demand
   • BScheduling workloads during off-peak hours
   • CManually scaling resources during peak hours
   • DReserving a fixed amount of capacity
   Reveal Solution Discussion Select an answer first
5. 19application · medium

   Your team manages a customer-facing checkout service running on a managed instance group (MIG) behind a global external HTTP(S) load balancer. You need to deploy a new version that changes the database schema and is not backward-compatible with the old version. The compliance team requires that if the deployment fails, you must be able to roll back to the previous version within minutes. You also need to verify the new version works correctly with a small percentage of live traffic before full rollout. What deployment strategy should you use?

   • ARolling update with a 50% max surge and 50% max unavailable
   • BCanary deployment using a single MIG with a rolling update and a 10% max surge
   • CBlue/green deployment with a new MIG and a weight-based traffic split, starting at 5%
   • DRolling update with a 100% max surge and 0% max unavailable
   Reveal Solution Discussion Select an answer first
6. 20foundation · easy

   Which deployment strategy involves gradually shifting traffic from the old version to the new version over a period of time, allowing for monitoring before full rollout?

   • ARolling deployment
   • BRecreate deployment
   • CBlue/green deployment
   • DCanary deployment
   Reveal Solution Discussion Select an answer first