120+
Mapped GPU metrics
Security, telemetry, anomaly, cost, trust and compliance-related signals are represented in the internal architecture. The public page treats this as a scope count, not verified coverage quality.
Phase 2 · infrastructure asset
GPU Sentinel.
See the GPU as a security and operations surface.
GPU Sentinel is an implemented Phase 2 infrastructure system organized around GPU telemetry, anomaly and threat detection, operational control, FinOps, audit/forensic posture and hardware-trust questions. Internal implementation and benchmark materials exist; independent performance, security, compliance and production validation remain Phase 3 work.
Implemented · internally tested120+ mapped metrics18 internal categoriesIndependent validation pending
GPU Sentineltelemetry → decision → control
TelemetryNVML · DCGM · CUPTI · orchestration
Detectionrules · statistics · anomaly · ensemble
Controlpolicy routing · response · isolation
Forensicsaudit trail · evidence packaging
FinOpsutilization · attribution · right-sizing
Hardware trusttenant isolation · accelerator integrity
Internal scope map
Scope counts describe the system—not its performance.
The Phase 2 material consistently maps a broad GPU-specific measurement surface. These counts are useful for understanding architectural depth, but they are not substitutes for independent benchmark results.
18
Internal categories
The metric map is grouped across multiple operational and security categories. Exact definitions and category membership belong to controlled technical review.
3
Accelerator classes referenced
Internal benchmark materials reference A100, H100 and RTX 4090 test surfaces. This establishes an internal test record, not third-party benchmark confirmation.
Count boundary: the public page deliberately avoids converting metric count, category count or hardware coverage into claims of production readiness, benchmark superiority or certified security effectiveness.
Architecture
A connected infrastructure stack, not a dashboard-only concept.
GPU Sentinel is structured as a layered system rather than a single monitoring surface. The public technical layer focuses on architecture that can be described without converting internal work into external performance or market claims.
01
Make accelerated compute observable.
The technical architecture names NVML, DCGM, CUPTI, Kubernetes surfaces, cloud/billing connectors, OpenTelemetry and related collectors as implementation or integration surfaces.
NVMLDCGMCUPTIKubernetesOpenTelemetry
02
Multiple detection families.
Rule/signature logic, statistical anomaly methods, machine-learning anomaly detection and ensemble-style decision logic are represented in the technical record. The public layer groups them as detection families rather than presenting a single algorithm-count claim.
Rule / signatureStatistical anomalyIsolation methodsEnsemble logic
03
Detection has operational consequences.
The system model extends from observation into severity, routing, containment and isolation concepts. Exact trigger thresholds and escalation logic remain security-sensitive and require controlled review.
SeverityPolicy routingContainmentIsolation
04
Security and efficiency share telemetry.
Utilization, idle control, workload attribution, right-sizing, forecasting and capacity questions form a second operational lane. The public layer does not present modeled savings percentages as validated outcomes.
UtilizationAttributionRight-sizingForecasting
05
Map evidence, don’t claim certification.
The architecture includes audit mapping, forensic packaging and chain-of-custody concepts. Regulatory and enterprise-framework references are treated as mapping targets, not as certification or verified compliance.
Audit mappingForensic packageChain of custodyExport surfaces
06
Extend review toward accelerator isolation.
MIG, SR-IOV, tenant isolation and high-value accelerator classes appear in the technical surface as hardware-trust questions. OEM integration and hardware-level assurance remain validation targets rather than public proof.
MIGSR-IOVTenant isolationHardware trust
Architecture boundary: listing an integration surface does not imply every connector or containment path was deployed in a production environment. The page distinguishes documented architecture and implementation work from Phase 3 deployment validation.
Internal implementation & testing
The asset has an internal technical record.
The Phase 2 technical record includes implementation/prototype materials and hardware-specific internal benchmark work. Run-specific performance numbers are not used as public results before independent reproduction and technical review.
Internal materials reference telemetry collection, anomaly/threat logic, response paths and GPU-class benchmark work. A100, H100 and RTX 4090 are named across the technical record. Exact timing, true/false-positive rates, memory overhead and latency are not treated here as validated public results.
Testing boundary: “internally tested” means internal execution and benchmark material exists. It does not mean independent reproduction, penetration-test validation, production readiness, compliance certification or third-party benchmark confirmation.
01
Telemetry surface
GPU/device and orchestration signals are mapped into an operational collection layer.
02
Detection logic
Multiple detection approaches are represented across rule, anomaly and ensemble-style decision paths.
03
Threat-pattern testing
Internal records reference attack-pattern test material around GPU misuse and infrastructure threats.
04
Hardware-class benchmark references
A100, H100 and RTX 4090 appear in internal benchmark references; raw methods and results remain controlled.
05
Response & forensic paths
Severity, containment, isolation and forensic packaging are documented as system paths.
06
Independent reproduction
External benchmark design, adversarial testing and reproducibility belong to Phase 3 technical review.
Operational lanes
Several buyer problems can meet at the same telemetry layer.
GPU Sentinel is most coherent when read as shared infrastructure with several possible productization lanes. The public page keeps the lanes, but not unverified ROI or market-superiority claims.
Security
Detect misuse and anomalies.
GPU-native telemetry can support review of unauthorized workloads, anomalous behavior and infrastructure-integrity events.
FinOps
Connect utilization to spend.
Attribution, idle detection, right-sizing and forecasting can turn the same telemetry surface into an efficiency and capacity-management lane.
Audit / Forensics
Preserve reviewable traces.
Evidence packaging, chain-of-custody concepts and audit mappings extend the system beyond alerts toward post-incident and procurement review.
Hardware trust
Review isolation at the accelerator layer.
Tenant isolation, MIG/SR-IOV and accelerator-integrity questions create a path toward cloud, enterprise and hardware-adjacent review.
Review boundary
What this page can support—and what still has to be proved.
GPU Sentinel should be treated as a Phase 2 technical asset with architecture, implementation and internal testing. The strongest commercial, security and performance conclusions remain open questions for Phase 3.
Supported at this layer
The public technical layer can describe the system’s architecture and internal technical record without presenting internal claims as independent validation.
A broad GPU-specific metric and category map exists.
Telemetry, detection, response, FinOps, forensics and hardware-trust layers are documented.
Implementation/prototype materials and internal benchmark references are part of the Phase 2 record.
A100, H100 and RTX 4090 are named in internal benchmark materials.
Still reserved for Phase 3
The page does not convert internal scope or internal runs into production or market validation.
No public claim of a readiness percentage, production certification or enterprise deployment validation.
No public claim of exact detection time, TP/FP rate, memory overhead or latency performance.
No public claim of exact savings, capacity gains or guaranteed ROI.
No claim of regulatory certification, unique market category ownership, or absence of comparable products.
Security disclosure boundary: exact thresholds, signatures, model parameters, escalation rules, containment logic and other sensitive operational detail should remain in controlled technical review. Evidence consolidation remains a later MZN-wide step.
Continue the technical route
GPU Sentinel moves Phase 2 from model systems into accelerated infrastructure.
Return to Phase 2 for portfolio context, go back to Tokenizer for the model-system layer, or continue to HUAI for the broader capability-architecture route.