AI Infrastructure SLAs: Uptime Guarantees, Credits, and Remedies for GPU Services

GPU cloud providers typically offer three SLA tiers. Standard tier guarantees 99.5 percent monthly uptime, offering 10 percent credits for falling below 99.5 percent but above 99.0 percent. Advanced tier at 99.9 percent uptime provides 25 percent credits below threshold with 5 percent per additional 0.1 percent shortfall. Premium tier at 99.95 percent uptime includes 50 percent credits plus contractual penalties of 15-20 percent of monthly spend for major incidents exceeding 30 minutes per quarter.

Enterprise AI workloads training for 7-14 days continuously require the Premium tier. A single 30-minute interruption during a 10-day training run can invalidate the entire job due to checkpoint inconsistency, wasting $120,000-$180,000 in compute costs for a 256-H100 cluster. AWS P5 instances carry a 99.99 percent multi-AZ SLA while single-AZ SLA is 99.5 percent, a distinction worth approximately $35,000 monthly per 100 H100s in credit exposure.

Service credits are calculated differently across providers. Most calculate against the affected resource hourly cost, not total monthly spend. For a 256-H100 cluster at $3.50/GPU-hour, a 25 percent credit on a 2-hour outage yields $448 recovery, representing only 0.3 percent of the monthly $161,280 spend. Only 35 percent of eligible credits are claimed according to infrastructure audit firms.

Credit stacking is an advanced strategy. A production inference pipeline running across two cloud providers can maintain 99.995 percent effective availability through failover while collecting credits from each provider individually. At $500,000 monthly GPU spend, this approach generates $25,000-$40,000 monthly in recoverable credits while improving actual uptime beyond any single provider guarantee.

Enterprise GPU agreements exceeding $1 million annual spend should negotiate three SLA dimensions beyond standard terms. Aggregated multi-region uptime averaging across geographic deployments reduces single-region outage exposure. Scheduled maintenance windows with 14-day notice should not count toward SLA. Force majeure carve-outs specific to power grid constraints account for 45 percent of cloud provider outages exceeding 30 minutes in 2024-2025.

Internal monitoring must complement provider SLAs. Teams should deploy independent health checks from three geographically distributed locations measuring end-to-end status every 60 seconds. Automated credit claim systems can submit requests within 15 minutes of incident detection. Companies with automated claim workflows recover 92 percent of eligible credits versus 28 percent for manual processes, a $90,000-$180,000 annual difference at $500,000 monthly GPU spend.

Advanced SLAs include non-monetary remedies that often provide greater value than credits. Extended reservation rights allow rolling committed term by the outage duration. Priority queue access guarantees job start within 15 minutes of submission. Some providers offer dedicated capacity pools reserving 5-10 percent of cluster capacity for Premium SLA customers.

The most aggressive remedy structures include liquidated damages for training job failures. For a contract of $2 million annual GPU spend, damages of 3x the cost of lost compute time for failed training runs exceeding 48 hours represent genuine provider accountability. Only 12 percent of GPU procurement contracts include performance-based damages, down from 28 percent in 2023.