AWS vs Private Cloud: When Cloud Costs Get Out of Control
If your workloads are predictable, AWS may be costing more than it should. KORE provides predictable fixed-cost private cloud pricing for stable workloads, while AWS costs can vary based on usage, transfer, support, monitoring and surrounding services.
Why teams hit a cost wall in public cloud
AWS can be a strong platform, but cost complexity grows quickly as estates mature. Teams commonly face unpredictable monthly bills, egress fees that are difficult to forecast, and pricing models that require continuous optimisation effort.
To stay performant, many organisations overprovision. The result is paying for idle headroom while still dealing with cost spikes from data movement, snapshots, and service interactions. Support can also become slower and less contextual when issues move through layered support paths.
For stable, VM-heavy or compliance-sensitive workloads, a fixed-cost private cloud model is often commercially cleaner and operationally easier to govern.
AWS vs KORE Private Cloud Cost Calculator
Compare fixed KORE private cloud pricing against a realistic AWS monthly estimate for predictable VM workloads.
KORE Fixed Monthly Price
AWS Estimated Monthly Price
AWS equivalent instance shape: 32 vCPU / 128 GB RAM
AWS estimate uses a general-purpose instance ratio of approximately 4 GB RAM per vCPU. AWS instance sizes bundle CPU and memory, so memory is not priced separately.
Estimated saving with KORE: €566.12/month, around 38% lower than AWS.
AWS pricing varies by region, operating system, commitment term, architecture and usage. This calculator compares core VM cost components and should not be treated as a formal AWS quote.
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AWS vs KORE Private Cloud
| Category | AWS | KORE Private Cloud |
|---|---|---|
| Pricing model | Pay-as-you-go with multiple usage meters | Fixed monthly pricing based on agreed resources |
| Monthly predictability | Can vary significantly month to month | High predictability with stable monthly billing |
| Data transfer costs | Egress and inter-service transfer charges apply | Included allowances with clear limits and terms |
| Resource allocation | Elastic but often tuned around variable consumption | Dedicated resources sized to your workload |
| Performance consistency | Depends on architecture and service mix | Consistent performance from reserved capacity |
| Infrastructure control | Strong platform tooling, less low-level control | Direct control of virtual infrastructure choices |
| Support model | Tiered support plans and ticket-based escalation | Direct access to engineers familiar with your estate |
| Sovereignty | Region-based, shared global hyperscale model | UK/EU private cloud options with clear data residency |
| Best fit | Highly variable, cloud-native workloads | Stable workloads requiring control and budget certainty |
Cost example: predictable capacity vs variable billing
Scenario: 16 vCPU, 64 GB RAM, 4 TB storage, moderate data transfer.
AWS estimate
Variable / usage-dependent
KORE model
Fixed monthly pricing
Pricing above is indicative by model only and not a formal quote.
When AWS makes sense
- Global burst scaling requirements across multiple regions.
- Deep use of cloud-native managed services.
- Highly variable workloads.
- AWS-native architectures (Lambda, DynamoDB, etc).
When private cloud wins
- Predictable workloads.
- VM-heavy environments.
- Compliance and sovereignty requirements.
- Fixed monthly budgets.
- Consistent performance requirements.
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