Together AI details the specific architectural requirements needed to achieve different reliability tiers for GPU inference, arguing that standard SLA numbers often obscure the actual failure domains covered.
- 99% uptime requires surviving node-level failures like GPU hardware faults or driver crashes through automated health checking and fast replica replacement within a single data center.
- 99.9% uptime demands survival of full data center failures, necessitating model weights deployed across two facilities with live traffic routing rather than cold standby.
- 99.99% uptime requires multi-region deployment with availability zone redundancy and reserved failover capacity sized to absorb a complete regional outage.
The article emphasizes that infrastructure ownership is critical, as providers renting from hyperscalers cannot control power or cooling layers, making direct hardware visibility essential for rapid recovery.