DATAFABRIX GUARDIAN · MODULE
Infrastructure Health — engineered for AI-class workloads.
Predictive failure detection. Autonomous remediation. Built around the Gen6 thermal-aware smart backplane telemetry surface.
Datafabrix Guardian is the predictive health module of the Datafabrix platform. It ingests high-fidelity telemetry from every device in your AI fleet, runs domain-aware machine learning continuously, and surfaces — and then autonomously remediates — failures long before they hit production traffic.
Predictive failure detection. Autonomous remediation. Built around the Gen6 thermal-aware smart backplane telemetry surface.
AI data centers are unforgiving environments. A single throttled GPU stalls a 1,024-node training run. A failed drive corrupts hours of checkpoint write-back. A power excursion takes down a rack of accelerators worth seven figures. And in 2026, fleets are scaling faster than the human teams that operate them.
Traditional monitoring is fundamentally reactive — it tells you what just broke. Guardian is fundamentally predictive — it tells you what is about to break, with 95% accuracy and 30 seconds of advance warning. Long enough for an autonomous playbook to drain the workload, migrate the tenant, or quarantine the device without anyone paging an on-call engineer.
Designed to operate on the high-fidelity telemetry generated by the upcoming Gen6 thermal-aware smart backplane, Guardian is the difference between firefighting and flying.
Models continuously baseline every device against fleet-wide percentiles and its own historical signature. Drift, anomaly, and impending-fault signatures are detected and scored 30 seconds before performance impact.
Triggered playbooks drain workloads, quarantine devices, rebalance memory pools, and re-route traffic — all without human intervention. Every action is logged, attributable, and reversible.
When something does break, Guardian correlates signal across power, thermal, PCIe, SSD, and GPU layers to attribute root cause in seconds — not hours of bridge calls.
RBAC, blast-radius limits, and policy-as-code ensure autonomous actions stay within configured guardrails. Your SRE team sets the constraints; Guardian operates inside them.
Every prediction — confirmed or refuted — improves the underlying models. Customers benefit from a data network effect that no single-tenant tool can match.
Three representative engagements that illustrate the kind of value Datafabrix Guardian delivers in the field.
A 1,024-GPU training run is 8 days in. A controller on rack 17 starts drifting on its PCIe error counters — invisible to standard monitoring.
Guardian detects the signature 30 s before the controller would have crashed. The playbook drains the rack, migrates the training tenant to a hot spare, and logs the incident with full attribution.
Zero hours of training lost. Engineering team learns about the swap from the daily report, not a page.
A storage tenant is pushing 3 DWPD across a 256-drive pool. Without intervention, 12 drives are projected to exit warranty within 60 days.
Guardian's SSD wear model flags the projection, recommends a workload-mix adjustment that extends life by 8 months, and triggers a procurement signal for spare inventory.
8 months of life extension. Procurement signal triggered in time to avoid emergency replacement at peak prices.
A cloud provider's largest enterprise tenant is approaching the SLA threshold for cluster availability. A subtle thermal pattern on one zone could trigger a violation.
Guardian's predictive model migrates the tenant's workload to a cooler zone before the violation would have triggered, then schedules cooling maintenance during the next maintenance window.
SLA preserved. Customer never sees a degradation. Cooling fix scheduled, not emergency-paged.
Tell us about your fleet and your top operational pain. We will map Datafabrix Guardian to a 90-day pilot scope — and quantify the expected outcome — within five business days.