Understanding GCP Committed Use Discounts: Should Your Company Buy CUDs?

Committed Use Discounts (CUDs) can save you up to 55% on Google Cloud compute costs. But commit to the wrong amount, and you're locked into paying for resources you don't use.

This guide helps you decide: Should your company buy CUDs? How much should you commit? And how do you avoid the common mistakes?

What Are Committed Use Discounts?

CUDs are Google Cloud's way of offering lower prices in exchange for a 1-year or 3-year commitment to use (or pay for) a certain amount of resources.

Key points:

• No upfront payment required—billed monthly
• Cannot be canceled mid-term
• Unused commitment is wasted money
• Savings range from 28% to 55% depending on type and term

CUD Types Explained

Google offers two types of CUDs:

Resource-Based CUDs

You commit to a specific amount of vCPUs and memory in a specific region for a specific machine family.

• Stable production workloads
• Known machine types and regions
• Predictable capacity needs

• Locked to specific machine family (N2, E2, etc.)
• Locked to specific region
• Can't apply to other services

Spend-Based (Flexible) CUDs

You commit to spending a certain dollar amount per hour across eligible services.

• Variable workloads
• Multiple services (Compute, GKE, Cloud SQL)
• Companies still optimizing architecture
• When you don't know exact machine types yet

• Lower discount than resource-based
• Still region-specific

CUD Decision Framework for SMBs

Step 1: Do You Qualify?

Minimum recommended spend: Your compute costs should be significant and stable enough to justify the commitment.

If your compute spend fluctuates heavily or you're still experimenting with architecture, Sustained Use Discounts (automatic, free) will cover you.

Step 2: Assess Workload Stability

Ask yourself:

Step 3: Choose Your Coverage Level

Conservative (Recommended for SMBs): Cover 30-50% of stable spend

Why not 100%? Because:

• Your needs will change
• Some workloads will be retired
• SUDs cover uncommitted usage (up to 30% automatic discount)

• Monthly GCP compute: $8,000
• Stable baseline: ~$6,000 (75% of total)
• Recommended CUD coverage: $2,000-3,000 (30-50% of baseline)

Step 4: Resource vs Flexible CUDs

Use this decision tree:

Do you know EXACTLY what instances you'll run for 1-3 years?
├── YES → Do they all fit one machine family?
│         ├── YES → Resource-based CUD (higher savings)
│         └── NO → Flexible CUD
└── NO → Flexible CUD

When in doubt: Start with flexible CUDs. Lower discount, but more forgiving.

CUD Calculator: Real Example

Let's walk through a real scenario.

Company profile:

• Monthly GCP compute spend: $10,000
• Mix of Compute Engine and GKE
• Primary region: us-central1
• Stable production workload: ~70% of spend

Calculation

Step 1: Identify stable baseline

• $10,000 × 70% = $7,000 stable monthly spend

• Conservative: 40% of baseline = $2,800/month commitment

• Multiple services (Compute + GKE) → Flexible CUD
• Convert to hourly: $2,800 ÷ 730 hours = $3.84/hour commitment

• 1-year term: Save $9,408/year
• 3-year term: Save $15,456/year

When NOT to Buy CUDs

CUDs aren't always the right choice. Skip them if:

1. You're Still Experimenting

2. Spend Is Too Low to Justify Commitment

3. You Might Change Clouds

4. Your Workloads Are Spiky

5. You Have Unused CUD Capacity

Common CUD Mistakes (And How to Avoid Them)

Mistake 1: Over-Committing

Problem: Committing to 100% of current spend, then usage drops.

Solution: Start at 30-50% coverage. You can always buy more CUDs later.

Mistake 2: Wrong Region

Problem: Buying CUDs in us-east1 when you're expanding to europe-west1.

Solution: Only commit to regions where you have established, stable workloads.

Mistake 3: Ignoring Flexible CUDs

Problem: Buying resource-based CUDs for workloads that change machine types.

Solution: Use flexible CUDs unless you have rock-solid workload requirements.

Mistake 4: Forgetting SUDs Exist

Problem: Thinking you need CUDs for any discount.

Solution: Remember that Sustained Use Discounts apply automatically to any VM running 25%+ of the month. You're already getting 20-30% off.

Mistake 5: Not Monitoring Utilization

Problem: Buying CUDs and forgetting about them.

Solution: Monthly review of CUD utilization. Target: 80%+ utilization.

How SUDs and CUDs Work Together

Many people don't realize: SUDs (Sustained Use Discounts) are automatic and stack on top of CUDs.

How SUDs work:

• After 25% of month usage: automatic discount kicks in
• Discount increases through the month
• Maximum ~30% discount at 100% monthly usage
• Applied automatically—no action needed

1. CUDs cover your committed baseline (28-55% off)
2. SUDs cover any additional usage (up to 30% off)

How to Monitor CUD Utilization

After buying CUDs, monitor monthly:

In GCP Console

1. Go to Billing → Commitments
2. Check utilization percentage
3. Target: 80%+ utilization

What to Do If Utilization Is Low

• Workloads were retired
• Migrated to different region
• Changed machine families
• Seasonal usage you didn't account for

Step-by-Step: Buying Your First CUD

Ready to buy? Here's the process:

1. Analyze Current Spend (1 hour)

• Export last 3-6 months of billing data
• Identify stable baseline
• Note primary regions and services

2. Calculate Commitment (30 minutes)

• Use the calculator above
• Start conservative (30-40% of baseline)
• Choose flexible vs resource-based

3. Purchase CUD

1. Console → Billing → Commitments
2. Select commitment type
3. Choose region
4. Enter commitment amount
5. Select term (start with 1-year if unsure)
6. Review and purchase

4. Set Up Monitoring

• Create monthly reminder to check utilization
• Set budget alerts for unexpected changes
• Document what the CUD covers

5. Review Quarterly

• Is utilization healthy?
• Should you buy more?
• Any workload changes coming?

Key Takeaways

1. CUDs save 28-55% but require commitment
2. Start conservative: 30-50% of stable baseline
3. Flexible CUDs are safer for most SMBs
4. Monitor utilization monthly: Target 80%+
5. SUDs are automatic: You're already getting some discount
6. Don't over-commit: You can always buy more later

Want help analyzing your CUD opportunities? GCP FinOps shows CUD utilization and recommends optimal commitment levels.