Cloud Digital Leader Scaling with Google Cloud operations Practice Question
A company's cloud costs have increased by 40% over the past quarter. The operations team wants to identify and address the root causes. Which cost optimization strategies should they investigate first?
⚠ Common exam trap
The trap here is that candidates often jump to aggressive cost-cutting measures like migrating to Spot VMs or switching providers, without first addressing the low-hanging fruit of resource waste, which is the most impactful and least risky initial step in cost optimization.
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
✓
Identify idle and underutilized resources (oversized VMs, unused disks, unattached IPs), apply lifecycle policies to storage, and commit to CUDs for stable workloads.
The first step in cloud cost optimization is to identify and eliminate waste from idle or oversized resources, which is the most common source of cost inefficiency. Applying lifecycle policies to storage and committing to Committed Use Discounts (CUDs) for stable workloads are proven strategies to reduce costs without compromising performance. This approach aligns with Google Cloud's recommended FinOps practices, focusing on immediate, high-impact savings before considering architectural changes.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Immediately upgrade all infrastructure to the latest generation hardware for better efficiency.
Why it's wrong here
Upgrading to the latest hardware generation does not inherently reduce costs; newer machine families often carry the same or higher list prices, and any efficiency gains may be offset by increased per-hour rates. This approach overlooks the actual source of wasted spend — idle and oversized resources — so you would be paying more for resources that are still not fully utilized. Cost optimization should begin with rightsizing and eliminating waste, not with refreshing infrastructure that may not even be the bottleneck, which is why this is not an effective first move.
- ✓
Identify idle and underutilized resources (oversized VMs, unused disks, unattached IPs), apply lifecycle policies to storage, and commit to CUDs for stable workloads.
Why this is correct
This is the correct first step because it directly targets the largest, most actionable cost leaks in any GCP environment. Active Assist tools like Recommender identify idle VMs and oversized instances for right-sizing, while unused disks and unattached IP addresses can be immediately deleted to stop recurring charges. Storage lifecycle policies (e.g., moving from Standard to Nearline or Coldline) automatically downgrade data access tiers for rarely used data, and Committed Use Discounts (CUDs) lock in lower prices for stable, predictable baseline compute — all without sacrificing performance or availability.
- ✗
Migrate all workloads to Spot VMs immediately to reduce costs by 90%.
Why it's wrong here
Migrating all workloads to Spot VMs would be disastrous because Spot VMs are preemptible capacity with no availability SLA — Google can reclaim them at any moment with only a 30-second warning. Running production workloads on them would cause constant, unpredictable interruptions and data-loss risks, far outweighing the claimed 90% savings, which are also unrealistic for most workloads. Spot VMs are best suited for batch jobs and fault-tolerant stateless workloads, not as a wholesale cost-reduction strategy.
- ✗
Switch cloud providers to whoever has the lowest advertised list price.
Why it's wrong here
Switching providers based purely on advertised list price ignores the massive hidden costs of migration: re-architecting for different APIs, retraining engineers, data transfer fees, and potential downtime during cutover. The lowest list price rarely translates to the lowest total cost of ownership once your specific workload profiles, networking costs, and operational overhead are factored in. Committed use contracts and sustained use discounts on GCP alone often deliver 20–40% savings without the expense and risk of a provider switch, and optimizing the current environment should always come first.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This GCDL practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the GCDL exam.