Reliability | Hedgehog

Reliability - Human Error is the Enemy

Traditional networks rely on fragile, manual CLI configurations. Depending on operators to perfectly execute complex routing updates across hundreds of switches is a leading cause of cluster-wide outages.

Automation Changes the Equation

Hedgehog replaces manual configuration with declarative, infrastructure-as-code automation. By managing outcomes rather than individual network gear, the fabric automatically enforces state, drastically shrinking the margin for human error.

See how Reliability impacts the economic return on your AI Network

The Stakes Have Changed for Inference

In AI training, a network outage delays a batch job—frustrating, but it happens without immediate customer impact. However, for inference, the RoCE network is a critical part of the live production stack. If the fabric isn't designed correctly and handled well, network failures translate directly into customer downtime.

Hyperscaler Stability from Day One

Instead of treating every cluster as a bespoke science project requiring months of manual debugging, operators deploy a pre-validated, hyperscaler-grade fabric. The network is rigorously tested and highly stable from the moment it is powered on.

3D abstract illustration of a hyperscale AI data center network fabric a dynamic lattice of luminous data threads weaving through minimal whitebox swi

Resilience Through Open Architecture

Proprietary systems can create rigid, single points of failure. An open Ethernet fabric ensures that no single hardware or software layer is a hostage, allowing you to build a highly resilient system on your terms.

Deep, Proactive Observability

You can't ensure reliability if you can't see the fabric's state. Hedgehog integrates cleanly with standard observability stacks, providing the absolute transparency needed to spot and resolve anomalies before they escalate into job-killing incidents.