Nutanix has built its platform around simplifying the data centre and hybrid cloud. In an AI context, this is particularly relevant because most organisations do not start out with large, dedicated AI environments.
AI is often adopted gradually. Pilot projects grow. New services are introduced. Experimentation takes place in parallel with day to day operations.
This creates a different need from that of hyperscale environments.
The challenge is not necessarily maximum performance – but flexibility, control and integration.
AI related workloads can:
- Require a temporary increase in compute
- Put a different kind of load on storage systems
- Change traffic patterns within the data centre
- Raise new security considerations
A platform approach can make it easier to adjust capacity over time, without building separate structures for each new technology.
But the same principle applies here too:
Scalability does not mean you should scale to the maximum from day one.
nLogic helps customers to:
- Assess their level of maturity
- Understand how AI affects existing architecture
- Identify which components actually need upgrading
- Create a step by step development plan
AI can be transformative. But in most organisations, the transformation happens gradually. Infrastructure should therefore be built so that it can evolve – not so that it assumes a future scenario that may never happen.
The right choice of platform is about balancing flexibility, cost and control.
Get in touch for more information
