Cloud vs On-Premise
Cloud and on-premise are deployment choices driven by data residency, latency, cost, and operating model. Enterprise AI can run in managed APIs, VPC/private cloud, or on-premise model hosting.
Quick Summary
Cloud and on-premise are deployment choices driven by data residency, latency, cost, and operating model. Enterprise AI can run in managed APIs, VPC/private cloud, or on-premise model hosting.
Definition: Cloud
Services and infrastructure delivered by a cloud provider, including private VPC patterns.
Definition: On-Premise
Infrastructure operated in the organization’s own data centers or dedicated facilities.
Comparison table
| Dimension | Cloud | On-Premise |
|---|---|---|
| Control | Shared responsibility with provider | Higher direct infrastructure control |
| Scale | Elastic by default | Capacity planned explicitly |
| Data residency | Region/config dependent | Physical location known |
| AI model hosting | Managed APIs or private cloud endpoints | Ollama/open weights or private clusters |
| Best fit | Speed, elasticity, managed ops | Strict residency or air-gapped needs |
Business use cases
Cloud
- Managed LLM APIs behind a gateway
- Cloud ERP extensions
- Elastic document pipelines
On-Premise
- Private model inference for sensitive data
- Regulated workloads with local residency
- Factory-floor offline constraints
Decision guidance
Choose based on data classification and operating capability, not fashion. Many programmes are hybrid: cloud apps with private inference for sensitive workloads.
Key Takeaways
- Cloud: Services and infrastructure delivered by a cloud provider, including private VPC patterns.
- On-Premise: Infrastructure operated in the organization’s own data centers or dedicated facilities.
- Decision: Choose based on data classification and operating capability, not fashion. Many programmes are hybrid: cloud apps with private inference for sensitive workloads.
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