Cloud Digital Leader Practice Question: Google Cloud products, services, and solutions

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✗

  Cloud Monitoring, which detects the traffic spike and sends an alert to the operations team to manually scale up

  Why it's wrong here

  Cloud Monitoring collects metrics and logs, and its alerting policies can notify an operations team when thresholds such as request count or latency are breached, but the alert itself is purely a signal—it performs no scaling action. Waiting for a human to receive the alert, diagnose the cause, and manually resize a managed instance group introduces a delay of several minutes, which is unacceptable for a 50x spike that materializes in seconds. While one could theoretically wire an alert to a Cloud Function for automated response, the scenario described—manual scale-up—is precisely what autoscaling is designed to eliminate.

• ✓

  Managed Instance Groups with autoscaling (for VMs) or Cloud Run (for containers), which automatically provision additional instances based on traffic load without manual intervention

  Why this is correct

  This is correct. MIG autoscaling monitors CPU/request metrics and automatically adds instances when load increases, then removes them when load drops. Cloud Run scales automatically to any number of container instances in seconds. Both handle the 50x spike scenario automatically.

• ✗

  Cloud Load Balancing, which distributes traffic evenly across existing instances to handle the spike

  Why it's wrong here

  Cloud Load Balancing operates at the network layer, distributing incoming traffic across the current set of backend VMs or containers according to configured rules. It does not, however, have any mechanism to add or remove instances; a 50x traffic spike would simply exhaust the fixed pool of backends, causing connection failures and degraded latency even if traffic is evenly spread. The load balancer works in conjunction with an autoscaler, which is responsible for growing the backend pool, but the balancer alone cannot supply the extra capacity needed for a spike of this magnitude.

• ✗

  Cloud Billing, which automatically increases the spending limit when traffic spikes occur

  Why it's wrong here

  Cloud Billing is a financial governance service that tracks spend, manages budgets, and sets cost alerts, but it has no mechanism to provision compute infrastructure. Even if a spending limit were increased during a traffic spike, that action would not launch additional VMs or container instances; billing configuration is entirely decoupled from capacity management. At best, exceeding a budget triggers a notification or service shutdown, which would worsen the situation, not alleviate it. Only an autoscaler can convert a demand spike into more instances.

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