In short
Hyperscalers (AWS, Azure, Google Cloud) and whitesky represent two fundamentally different approaches to cloud infrastructure. Hyperscalers own the hardware and rent you capacity. whitesky enables you to own and operate your own cloud infrastructure. The choice depends on your priorities around data control, cost structure, and operational preferences.
Overview
Hyperscalers have transformed how many organizations consume IT infrastructure. However, their public cloud model comes with certain trade-offs: egress fees, vendor lock-in, data residency concerns, and sometimes unpredictable costs. whitesky offers an alternative for organizations that want cloud-native capabilities without giving up infrastructure control.
Key differences
Infrastructure ownership
| Aspect | whitesky | Hyperscalers |
|---|---|---|
| Who owns the hardware | You or your partner | The hyperscaler |
| Where data resides | Your datacenter or partner facility | Hyperscaler datacenters |
| Infrastructure control | Full control | Limited to what the provider offers |
| Capital expenditure | Hardware purchase (or partner model) | Operating expense only |
Cost structure
| Aspect | whitesky | Hyperscalers |
|---|---|---|
| Compute pricing | Predictable (hardware-based) | Variable (usage-based) |
| Storage pricing | Predictable | Variable, often tiered |
| Egress fees | Not charged | Per-GB charges (vary by service and region; some free-tier exceptions) |
| Unexpected costs | Low likelihood | Common with complex pricing |
| Billing complexity | Simple | Often requires FinOps expertise |
Data sovereignty
| Aspect | whitesky | Hyperscalers |
|---|---|---|
| Data residency | Control where data resides | Limited to hyperscaler’s regions |
| GDPR compliance | Straightforward (EU operations) | Requires transfer-risk assessment (US parent companies) |
| Audit capabilities | Full infrastructure access | Limited to what provider exposes |
| Data portability | Full (you own everything) | Limited by egress costs |
Feature comparison
Core services
| Service | whitesky | AWS | Azure | GCP |
|---|---|---|---|---|
| Virtual machines | Cloudspaces | EC2 | VMs | Compute Engine |
| Object storage | Objectspaces | S3 | Blob Storage | Cloud Storage |
| Kubernetes | Containerspaces | EKS | AKS | GKE |
| Load balancers | Built-in | ELB/ALB/NLB | Load Balancer | Cloud LB |
| VDI | Built-in | WorkSpaces | Windows 365 / AVD | Partner VDI / Cloud Workstations |
Important differences
| Aspect | whitesky | Hyperscalers |
|---|---|---|
| API compatibility | whitesky APIs | Provider-specific APIs |
| Ecosystem | Growing partner network | Massive third-party ecosystem |
| Global reach | Through federation | Extensive global regions |
| Managed services | Yes | Extensive managed service catalog |
| Serverless | Roadmap | Extensive serverless offerings |
When to choose whitesky
Consider whitesky if:
- Data sovereignty is critical - you need data to stay in specific locations you control
- Cost predictability matters - you want to avoid unexpected billing
- You have existing hardware - leverage investments in infrastructure
- You want predictable data transfer - data-intensive workloads avoid per-GB charges
- You prefer independence - avoid vendor lock-in and dependency on a single provider
- You’re an MSP - build your own cloud under your brand
When hyperscalers may fit better
Hyperscalers may remain appropriate if:
- You need global scale quickly - existing infrastructure already in place
- You need specialized services - machine learning, IoT, specific managed databases
- You prefer OpEx only - no capital investment in hardware
- Your team has deep hyperscaler expertise - leverage existing skills
- You’re a startup - minimal upfront investment, pay-as-you-go
Hybrid and multi-cloud
Many organizations use both approaches strategically:
- Hyperscalers for: burst capacity, specialized services, global reach
- whitesky for: core workloads, sovereignty-sensitive data, predictable costs
whitesky’s federation model can integrate with hyperscalers for backup and disaster recovery scenarios.
Migration from hyperscalers
Moving workloads from a hyperscaler to whitesky:
- Assessment - evaluate workloads for migration suitability
- Sizing - determine infrastructure requirements
- Migration - import VM images or re-platform applications
- Optimization - leverage whitesky features for cost efficiency
Get started
Contact whitesky to discuss your infrastructure strategy and whether a private cloud approach fits your organization’s needs.
Request a demo to see whitesky capabilities and discuss your specific requirements.