Scaling workstation deployments is never straightforward. IT teams need to balance performance, cost, manageability, and security, but the trade-offs between approaches can be significant. In this blog, we’ll walk through the three most common deployment models, highlight their limitations, and introduce how newer solutions like Computle illustrate a different path.
Common deployment models
Scenario 1: Office-based, self-managed workstations
Most organizations start here: buying machines from major vendors, installing them onsite, and letting users work locally. It’s cost-effective and low-overhead, but scaling quickly exposes cracks.
| Trade-off | Description |
|---|---|
| Operational overhead | High-performance hardware generates heat and noise, often requiring additional cooling. |
| Scalability limits | Every new user means procurement cycles, delivery delays, and physical setup. |
| No central management | Each machine must be updated and patched individually. |
| Security risks | Physical access increases the risk of data exposure. |
| Fixed resources | Users are locked into hardware specs, even if their workload changes. |
Example TCO data shows that while entry costs are low, three-year totals rise quickly with higher-end GPUs, especially when accounting for management overhead.
Scenario 2: Adding remote access
To enable flexible working, many organizations retrofit tools like Parsec or Teradici (HP Anyware) onto office workstations. This provides remote access but introduces a new layer of complexity.
| Trade-off | Description |
|---|---|
| Integration complexity | Remote access must be configured, secured, and maintained separately. |
| Performance limits | Latency and bandwidth can degrade user experience, especially for graphics-heavy tasks. |
| Office dependency | Users remain tied to office connectivity, power, and physical security. |
| Management gaps | No ability to centrally re-image, reboot, or reassign machines. |
| Extra hardware | Users need certified access devices (e.g., dual-4K setups). |
Costs increase as organizations add licensing and access hardware, often eroding the initial savings of local workstations.
Scenario 3: Adding a management layer with VDI
At larger scales, organizations often turn to Virtual Desktop Infrastructure (VDI). Solutions like VMware Horizon or Citrix provide centralized provisioning, monitoring, and lifecycle management. But the complexity is not trivial.
| Trade-off | Description |
|---|---|
| Cost escalation | Enterprise VDI licensing can double total cost of ownership. |
| Technical complexity | Requires specialist knowledge across virtualization, networking, and storage. |
| Performance compromises | Shared infrastructure introduces contention, leading to lag under load. |
| Infrastructure overhead | Significant upfront investment in servers, storage, and redundancy is required. |
| Operational burden | Teams must manage hypervisors, templates, brokers, and multi-layer troubleshooting. |
Even with strong security and centralisation, per-user costs can climb dramatically when licensing, hardware, and energy are factored in.
A newer approach: Dedicated performance with cloud-style management
This is where solutions like Computle illustrate an alternative. Instead of choosing between dedicated workstations or centralised management, it delivers both:
- Dedicated performance: Each user gets a private CPU, GPU, RAM, and storage, with no contention.
- Enterprise management: Central imaging, patching, and provisioning without VDI overhead.
- Global access: Low-latency connectivity through strategically placed data centres.
- Built-in security: Entra ID, MFA, and compliance frameworks included.
- Operational simplicity: No servers, hypervisors, or storage arrays to maintain.
- Predictable OpEx: Simple monthly subscription replaces unpredictable CapEx.
Cost modeling shows that dedicated blade workstations delivered this way can reduce TCO by up to 27% over VDI, while providing superior and more consistent performance.
Key takeaways
While this blog has focused on exploring the three most common deployment models, there are four key takeaways that we should focus on:
- Office workstations: Cheap but don’t scale and lack management/security.
- Remote-enabled workstations: Extend access but add complexity and dependency.
- VDI: Centralises management but at the cost of licensing, complexity, and performance.
- Newer models (e.g., Computle): Combine the strengths of dedicated hardware with the manageability of VDI, without the trade-offs.
In short: scaling workstation deployments isn’t about choosing between performance, cost, or manageability - it’s about understanding the trade-offs of each model, and recognizing when a hybrid approach offers a better balance.
