Technical infrastructure
The best software is worthless if it goes down, runs slowly or nobody knows how it is set up. I make sure that what we build runs well in production: on your server, on a managed one or on whatever cloud is needed.
What I cover
- GPU servers — assembly and configuration for AI inference: drivers, CUDA, multi-GPU, cooling and power draw.
- On-premise and cloud deployments — Linux, Nginx/Apache, Docker, HTTPS, backups and monitoring.
- Evolutive maintenance — security updates, patching, surveillance and incident response.
- Migrations — moving systems in production without surprises: plan, cutover window and rollback plan.
The criterion
Infrastructure sized to the real case, not to the hypothetical scenario: a well-configured server performs like a badly-configured one at twice the price. And everything documented — you will know what there is, why it is there and how to start it.
Related
It is the base for running local models and works side by side with your databases.
A server that gives scares, or a project that needs a home? Tell me about it.