The Full Circle: Our Journey from Bare Metal to AWS and Back Again

How We Cut Infrastructure Costs While Improving Performance for High-Traffic Applications

The cloud computing revolution promised unlimited scalability, reduced operational overhead, and lower costs. For many years, we believed in that promise. Today, we're completing a full circle—returning to bare metal servers for our high-demand applications. This isn't a step backward; it's a strategic evolution based on hard data and real-world experience.

The Early Days: Owning Our Infrastructure (Early 2000s)

In the early 2000s, we operated like most technology companies of that era: we owned physical servers housed in data centers. These bare metal servers required significant upfront capital investment, but the ongoing costs were relatively predictable—primarily consisting of:

• Initial hardware procurement costs
• Monthly colocation fees for rack space, power, and cooling
• Periodic hardware refresh cycles

This model worked well enough, but we noticed a concerning trend: data center rental fees continually increased over time, squeezing our margins and making infrastructure costs less predictable year over year.

The AWS Era: Embracing the Cloud

When Amazon Web Services matured, the value proposition was compelling: pay only for what you use, scale on demand, and eliminate upfront infrastructure costs. We migrated our operations to AWS and immediately appreciated several benefits:

• No upfront hardware costs: We could launch projects without capital expenditure
• Elastic scalability: Resources could grow and shrink with demand
• Reduced operational complexity: AWS managed the underlying infrastructure

For years, this worked exceptionally well. We launched numerous projects, experimented rapidly, and scaled successfully. AWS became the foundation of our infrastructure strategy.

The Awakening: When Cloud Costs Stopped Making Sense

As our applications matured and traffic patterns became more predictable, we began to notice something troubling in our monthly AWS bills. The problem wasn't where we expected it to be.

The Traffic Cost Crisis

AWS charges between $0.05 and $0.09 per GB for outbound data transfer to the internet, depending on volume and service type. For applications with modest traffic, these costs remain manageable. But for high-demand applications—particularly in e-commerce and blockchain infrastructure—the egress charges became our largest expense category.

We discovered what many companies are now learning: AWS charges significantly more for data transfer than competitors, with outbound data costs starting at $0.09 per GB. When you're serving millions of API requests, streaming blockchain data, or running high-traffic e-commerce platforms, these cents-per-gigabyte add up to tens of thousands of dollars monthly.

The revelation was stark: we were spending more on traffic than on the actual computing and memory resources powering our applications.

The "Convenience Tax"

Every layer of our stack carried a 'convenience tax'—we were paying AWS for the privilege of not managing underlying hardware. For small, unpredictable workloads, this tax is absolutely worth paying. But for large, stable applications with predictable resource needs, we were essentially paying a premium for flexibility we weren't using.

The Data That Changed Our Strategy

Let's look at the numbers that drove our decision:

AWS Cost Structure for High-Traffic Applications

• Computing instances: ~30% of total cost
• Storage: ~10% of total cost
• Data transfer (egress): ~60% of total cost

This distribution is common for bandwidth-intensive applications. Companies like OneUptime and Prerender found they could cut infrastructure costs by over 50% by migrating from AWS to bare metal servers.

Real-World Examples

The trend of cloud repatriation isn't new—we're joining a growing number of companies:

• Dukaan, an Indian e-commerce startup, reduced their AWS bill from $80,000 per month to approximately $5,000 by migrating to bare metal servers with Hetzner
• OneUptime saved over $230,000 annually by moving from a 28-node AWS Kubernetes cluster costing $38,000 monthly to bare metal infrastructure
• Dropbox saved nearly $75 million over two years by moving to their own infrastructure

Where AWS Still Wins: Low-Traffic and Variable Workloads

It's crucial to understand that AWS remains the right choice for many scenarios:

Perfect for AWS:

• Startup projects: Applications with minimal traffic benefit from pay-as-you-go pricing
• Variable workloads: Applications with unpredictable traffic spikes
• Serverless architectures: Lambda functions with sporadic invocations
• Geographic distribution: Applications requiring presence in many regions

For a low-traffic application using Lambda and API Gateway, AWS charges are minimal because you only pay for actual usage. The infrastructure scales to zero when idle, resulting in near-zero costs during quiet periods.

Where Bare Metal Wins:

• High-traffic applications: Consistent, predictable load patterns
• Bandwidth-intensive workloads: E-commerce platforms, blockchain nodes, media streaming
• Performance-critical applications: Where the "noisy neighbor" problem is unacceptable
• Cost-sensitive operations: Where infrastructure is a significant expense

The Migration Back: Strategic Considerations

Our return to bare metal isn't a complete abandonment of cloud services—it's a hybrid approach that optimizes for cost and performance where it matters most.

Cost Comparison: Traffic Economics

OVHcloud's inclusion of unmetered bandwidth is a major cost advantage for applications with high data egress, while hyperscalers like AWS typically charge substantial egress fees. Similarly, providers like Hetzner offer generous traffic allowances that make them economically attractive for bandwidth-intensive applications.

For our workloads, the math was compelling:

• AWS: $0.09/GB for first 10TB, decreasing to $0.05/GB after 150TB
• Bare Metal (Hetzner/OVHcloud): Effectively unlimited or included in base cost

At our traffic levels, this difference translates to thousands of dollars in monthly savings on bandwidth alone.

Performance Gains: The Noisy Neighbor Problem

Beyond cost savings, we've observed measurable performance improvements. While subjective and difficult to quantify definitively, our applications running on bare metal consistently outperform their AWS counterparts. This aligns with the fundamental architecture:

• Bare metal offers better performance as there are no multi-tenant or hypervisor overheads, and application workers run faster with no hypervisor to slow them down
• Dedicated resources eliminate the 'noisy neighbor' issue often experienced in shared hosting environments, where multiple customers sharing server resources can lead to performance degradation

The Trade-offs: What We Lost

Honesty requires acknowledging what we gave up:

Reduced Instant Scalability

AWS allows you to spin up dozens of instances in minutes. Bare metal provisioning takes longer—hours or days rather than minutes. However, for applications with predictable traffic patterns, this isn't the limitation it might seem.

Failover Complexity

High availability on AWS is relatively straightforward with auto-scaling groups and load balancers. On bare metal, we need to implement:

• Physical load balancers or software-based solutions
• Floating IP configurations for failover
• More manual intervention during failures

That said, achieving truly flawless failover in AWS requires significant investment as well. The problem exists in both environments; it's just differently shaped.

Increased Operational Responsibility

We're now responsible for hardware maintenance, OS patching, and infrastructure monitoring. However, the actual hands-on time required is comparable to the time previously spent on AWS cost optimization, IAM policy management, and chasing deprecations.

Our Hybrid Approach

We're not abandoning AWS entirely. Our current strategy leverages the strengths of both platforms:

Bare Metal:

• High-traffic e-commerce platforms
• Blockchain infrastructure nodes
• Database clusters with predictable load
• Applications where performance consistency is critical

AWS:

• Development and testing environments
• Low-traffic applications and APIs
• Serverless functions for event-driven tasks
• Services requiring rapid geographic expansion
• Backup and disaster recovery storage

Implementation Strategy: How We Migrated

Our migration followed a careful, risk-managed approach:

1. Benchmarking: Tested bare metal performance with representative workloads
2. Pilot Migration: Moved non-critical services first
3. Gradual Traffic Shifting: Used the Strangler Fig Pattern to gradually shift traffic from AWS to bare metal infrastructure without downtime
4. Monitoring and Adjustment: Extensive monitoring at each stage with instant rollback capability
5. Full Migration: Once stable, moved remaining high-traffic applications

Key technologies that enabled smooth migration:

• Kubernetes: Portable container orchestration across environments
• Infrastructure-as-Code: Terraform and similar tools for reproducible deployments
• Automation: CI/CD pipelines that work identically across cloud and bare metal

The Results: By the Numbers

After completing our migration of high-demand applications:

• Cost Reduction: 60-75% lower infrastructure costs for migrated applications
• Performance Improvement: Measurably lower latency and higher throughput
• Predictability: Fixed monthly costs instead of variable cloud bills
• Control: Complete hardware and network stack control

Lessons Learned

1. Cloud Isn't Always Cheaper

The "cloud is cheaper" narrative assumes you're paying only for what you need. For applications with consistent, high resource utilization, this assumption breaks down. Organizations can see savings of over 70% by switching to bare metal servers compared to public cloud costs.

2. Traffic Costs Are the Hidden Killer

AWS egress fees serve as a business strategy tool—by making data movement costly, AWS incentivizes customers to keep workloads within their ecosystem. For bandwidth-intensive applications, these fees can exceed compute costs.

3. The Right Tool for the Right Job

There's no universal answer. Small projects, variable workloads, and applications requiring rapid global distribution benefit from cloud platforms. Large, predictable workloads with high bandwidth needs are often more economical on bare metal.

4. Hybrid is Realistic

Hybrid cloud solutions allow companies to enjoy the benefits of both cloud and on-premises infrastructure. We don't have to choose one or the other—we can optimize each workload individually.

Looking Forward

The infrastructure landscape continues evolving. Cloud providers are responding to customer concerns about egress fees with new pricing models and offerings. Bare metal providers are adding cloud-like features—API-driven provisioning, automation, and managed services.

Our journey from bare metal to cloud and back to bare metal reflects a maturing understanding of infrastructure economics. The cloud revolution taught us valuable lessons about automation, scalability, and operational efficiency. Now we're applying those lessons to infrastructure models that better match our specific workload characteristics.

Recommendations for Others

If you're experiencing ballooning cloud costs, especially around data transfer:

1. Analyze your bill: Break down costs by category. If traffic exceeds 30% of your bill, you're a candidate for bare metal.

2. Identify stable workloads: Applications with predictable traffic and resource needs benefit most from migration.

3. Start small: Migrate one non-critical application as a proof of concept.

4. Consider hybrid: You don't have to move everything—optimize each workload independently.

5. Account for operational overhead: Ensure you have the expertise to manage bare metal infrastructure.

6. Use modern tools: Kubernetes, Terraform, and automation tools make bare metal as manageable as cloud.

Conclusion

The cloud promised us flexibility and cost savings, and for many use cases, it delivers exactly that. But as applications mature and traffic grows, the economics can shift dramatically. Our return to bare metal for high-demand applications isn't a rejection of cloud computing—it's an evolution toward a more nuanced, optimized infrastructure strategy.

By understanding the true total cost of ownership across different infrastructure models, we've built a hybrid approach that gives us the best of both worlds: cloud flexibility for variable workloads and bare metal economics for predictable, high-traffic applications.

The future of infrastructure isn't cloud-only or on-premises-only. It's intelligent, workload-specific optimization that leverages the right platform for each application's unique characteristics.

Have you experienced similar challenges with cloud costs? We'd love to hear about your infrastructure journey in the comments below.