GLOBALATLAS AI · Infrastructure by workload
Infrastructure by workload
A solution combines compute, data and recovery. These guides describe the architecture to plan; the final resource configuration is selected separately.
Start from the application workflow
Build and operate a product
AI startups
Separate experiments from customer-facing inference so model changes do not disrupt the application.
Explore →Infrastructure for developers
Build a reproducible development environment with explicit images, credentials and project boundaries.
Explore →SaaS infrastructure
Separate stateless application workers from stateful databases and customer files.
Explore →Work with data and graphics
GPU rendering
Match the GPU to the renderer, scene memory and supported acceleration backend.
Explore →Machine learning infrastructure
Separate data preparation, training and serving; these stages need different compute and storage profiles.
Explore →Data science infrastructure
Interactive analysis depends on dataset size, working memory and reproducible environments.
Explore →