Scale-out systems with explicit operations
Design nodes, fabric, storage, scheduling and operational ownership from the workload outward.
Multi-node platforms for distributed simulation, shared AI training/inference, high-throughput jobs and organisation-scale technical computing.
Good fit
When this platform form earns its place
- One system cannot meet the aggregate capacity, concurrency or resilience need.
- Software can use distributed or scheduled resources effectively.
- The organisation can own or procure cluster operation, identity, updates, monitoring and support.
Architecture inputs
Questions before component selection
- Can the workload scale across nodes, GPUs or independent jobs?
- Fabric latency/bandwidth and storage I/O profile?
- Scheduler, containers, identity, licences and user environment?
- Deployment, monitoring, updates, backup and operational competence?
Commercial boundary
Indicative until formally quoted
Public configurator values derive from the maintained price data but expose only simplified starting/configured totals. Final scope, availability, export compliance, price and terms are confirmed by formal quotation.