How High-Relief Coin Design Principles Can Reduce Your AWS, Azure & GCP Cloud Spend

Ever notice how your cloud bill creeps up—even when you’re not deploying new features? I’ve been there. After years of helping teams cut AWS, Azure, and GCP costs by 30–60%, I found an unexpected muse: high-relief coins like the 2025 American Liberty. Their design philosophy—crafting maximum impact with minimal material—changed how I think about cloud spending. And it can change yours too.

The FinOps Mindset: Designing for Value, Not Just Cost

FinOps isn’t about frugality. It’s about value. I once helped a fintech team save $15k/month not by cutting servers, but by asking: Are you paying for what you need—or what you’ve always used? That’s the shift. Better architecture isn’t just cheaper—it’s faster, more scalable, and easier to maintain.

High-relief coins gave me another lens. They don’t just slap on more metal. They sculpt depth, refine edges, and eliminate waste—all to make a dollar coin feel like a masterpiece. That’s what we should aim for in the cloud: systems that feel intentional, not bloated.

Surprisingly, the parallels are everywhere. Let’s break down how coin design principles can reshape your cloud strategy.

Lessons from High-Relief Coin Design

• Depth of Value: Coins impress by building upward, not outward. In the cloud, that means using serverless or managed services—not just renting VMs. Less surface, more substance.

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• Precision Engineering: Every groove in a coin is calculated. In the cloud, that’s right-sizing—zero wasted CPU, memory, or storage.

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• Material Optimization: Coins use gold or silver only where it matters. Cloud workloads? Use reserved instances for steady traffic, spot for batch jobs. No overkill.

Applying High-Relief Principles to AWS Cost Optimization

AWS has the most tools—and the most traps for over-spending. Here’s how to approach it like a master engraver.

1. Use AWS’s “Depth” with Serverless Computing

High-relief coins don’t rely on thick metal. They use layered design. Same with AWS. Lambda, Fargate, and DynamoDB let you build systems without managing servers—so you pay for what you use, not what you “might.”

Real talk: A startup once used EC2 instances for a cron job that ran 2 minutes a day. $60/month. With Lambda? $0.03. That’s not optimization—it’s a mindset shift.

// Old way - paying for idle metal
const server = new EC2.Instance(this, 'MyServer', {
  instanceType: InstanceType.of(InstanceClass.M5, InstanceSize.LARGE),
  machineImage: new AmazonLinuxImage(),
  // $70/month, even if you use it 2 minutes/day
});

// New way - pay for actual work
const function = new lambda.Function(this, 'MyFunction', {
  runtime: lambda.Runtime.NODEJS_18_X,
  handler: 'index.handler',
  code: lambda.Code.fromAsset('lambda'),
  timeout: Duration.seconds(30),
  // $0 if no one uses it. Game over.
});

2. Precision Engineering with Right-Sizing

Coins are milled to the micron. Your EC2 instances shouldn’t be overbuilt. Use AWS Compute Optimizer to:

• Downsize instances running at 10% CPU
• Upgrade ones hitting throttling limits
• Switch to T4g for apps that burst, not run all day

I saved a SaaS company $22k/year by resizing 12 instances. No app changes. Just better fit.

3. Material Optimization with Reserved Instances & Savings Plans

Premium coins get premium pricing not because they’re flashy—but because they’re scarce. Reserved instances and savings plans work the same. Commit to usage, get a discount.

• EC2 Reserved Instances: 75% off for 1–3 year commitments
• Savings Plans: More flexible, up to 72% off for consistent usage

Pro move: Use AWS Cost Explorer to find your top 5 instance types. Commit to those first. Save 60% with minimal effort.

Azure Billing: The High-Relief Approach to Microsoft’s Cloud

Azure’s pricing is unique, but the coin mindset still fits. Think value engineering, not cost-cutting.

1. Leverage Azure’s “Depth” with Hybrid Benefits & Spot VMs

Got Windows Server or SQL Server on-prem? Use Azure Hybrid Benefit. You move your license to the cloud—85% off. It’s like re-minting old coins into new value.

Spot VMs are another gem. Up to 90% off for interruptible workloads. Great for batch processing, CI/CD, or dev environments.

2. Precision Engineering with Azure Advisor

Azure Advisor is your engraver’s chisel. It flags:

• VMs using only 5% CPU (resize or delete)
• Unattached disks (delete)
• Dev boxes running 24/7 (auto-shutdown)

I once found 47 idle VMs in a dev subscription. $3,200/month saved by turning them off at night.

3. Material Optimization with Azure Reserved VM Instances

Azure RIs cut costs by up to 72%. Unlike AWS, they can apply to shared VMs—more flexibility, same savings.

Quick win: Model a 3-year commitment for your most stable VMs. A D8s v3 drops from $0.384/hr to $0.122/hr. 68% savings. No service changes.

GCP Savings: The High-Relief Model for Google’s Platform

GCP’s pricing is built for efficiency. It rewards smart design—just like high-relief coins.

1. Use GCP’s “Depth” with Committed Use Discounts & Sustained Use Discounts

GCP offers two ways to save:

• Committed Use: Up to 57% off for 1–3 year commitments (like AWS RIs)
• Sustained Use: Automatic discounts when you use 25%+ of the month. No contract. Just reward for consistency.

I call this “set it and forget it” cost control. The cloud pays you back for using it.

2. Precision Engineering with GCP’s Sizing Recommendations

GCP’s Recommender analyzes your usage and suggests:

• Smaller VMs for underused workloads
• Larger ones for CPU-starved apps
• Better machine types (e.g., N2 over N1)

One team saved $12k/month by switching to E2-standard-4 for a low-traffic web server.

3. Material Optimization with Preemptible VMs & Custom Machine Types

GCP’s preemptible VMs are 91% cheaper than standard. They can vanish with 30 seconds’ notice—perfect for batch jobs or stateless services.

Even better: custom machine types. Need 4 CPUs and 12GB RAM? Don’t settle for 8/32. Pay for exactly what you use.

# Standard - overbuilt
gcloud compute instances create example-vm \
  --machine-type=n2-standard-8 \
  # 8 vCPUs, 32GB RAM. Even if you need half.

# Custom - high-relief efficiency
gcloud compute instances create custom-vm \
  --custom-cpu=4 \
  --custom-memory=12GB \
  # Zero waste. Maximum clarity.

Cross-Cloud Serverless Computing Costs: The Ultimate High-Relief Design

Serverless is where the coin analogy shines. It’s sculpted architecture—no wasted material, just clean execution.

1. AWS Lambda Cost Optimization

• Right-size memory: Use Lambda Power Tuning to find the sweet spot. 512MB might be 40% cheaper—and just as fast.
• Cut execution time: Optimize code, reduce dependencies. Faster = cheaper.
• Provisioned concurrency: For high-traffic functions, pre-warm instances. Faster response, fewer cold starts.

One team cut Lambda costs by 35% just by tuning memory from 1024MB to 512MB.

2. Azure Functions Cost Optimization

Azure Functions has two plans:

• Consumption: Pay per invocation. Great for spiky traffic.
• Premium: Fixed monthly fee + pay-per-use. Better for steady traffic.

Ask: Is your function busy 20+ hours a day? If yes, Premium often wins.

3. GCP Cloud Functions Cost Optimization

GCP wins on generosity:

• First 2 million invocations free monthly
• Free egress and memory up to generous limits
• Scales to zero—no idle costs

But remember: serverless works best for event-driven tasks. Not everything should be a function.

Implementing the High-Relief Cloud Cost Optimization Framework

Enough theory. Here’s how to start—today.

1. Assess Your Current State

• Pull a cost report. Break it down: service, environment, team.
• Find the 20% of resources eating 80% of your budget.

No guessing. Just data.

2. Apply High-Relief Design Principles

• Depth: Can you replace a 24/7 server with serverless or containers?
• Precision: Right-size everything. Use tools like Compute Optimizer or Recommender.
• Material Optimization: Commit to RIs or Savings Plans for stable workloads.

3. Automate Optimization

• Set budget alerts. Catch spikes early.
• Auto-shut down dev/test resources at night.
• Use policy-as-code to block oversized VMs.

4. Measure and Iterate

• Track cost per transaction, not just total spend.
• Review quarterly. Celebrate wins with your team.
• Reward cost-conscious engineers. Make efficiency a culture.

Conclusion: The High-Relief Future of Cloud Cost Optimization

High-relief coins show us the power of intentional design. They don’t waste material. They maximize impact. That’s the future of cloud spending.

Remember this:

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1. Use depth: Serverless, managed services, hybrid benefits. Go vertical, not horizontal.
2. Engineer precisely: Right-size. Automate. Tune.
3. Optimize material: Commit to pricing. Use spot/preemptible for batch.
4. Measure value: Track cost per user, transaction, or feature. Not just dollars.

The 2025 American Liberty coin isn’t just a collector’s item. It’s a design manifesto. Apply its principles, and you won’t just save money—you’ll build systems that feel right. Less waste. More meaning. That’s what efficient cloud architecture should be.

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