Monitor everything from a single pane of glass

WhiteFiber’s observability platform offers real-time monitoring of compute resources across all workloads—baremetal, virtualized, and containerized—enabling end-to-end visibility into your AI infrastructure.

  • bullet point check icon

    Out-of-the-box dashboards and customizable alerts

  • bullet point check icon

    Monitor critical metrics like GPU utilization, temperature, and inference latency

  • bullet point check icon

    Rapidly identify bottlenecks to optimize performance and prevent hardware issues.

By correlating GPU metrics with broader infrastructure data, we ensure seamless troubleshooting and peak efficiency for your AI workloads.

01.

Proactive Issue Detection and Resolution

Customizable alerts and intelligent dashboards identify performance bottlenecks like GPU overheating, memory utilization spikes, and inference latency, enabling rapid optimization and preventing costly downtime.

02.

End-to-End Infrastructure Correlation

Correlate GPU metrics with broader infrastructure data—including logs, traces, and model performance metrics—for seamless troubleshooting and actionable insights across your entire AI stack.

03.

Support for Diverse GPU Architectures

Monitor all major NVIDIA GPU architectures and technologies, from A100s to Hopper and NVLink, ensuring compatibility and performance optimization for any workload at scale.

04.

REAL-TIME MONITORING ACROSS ENVIRONMENTS

Track GPU performance and usage in real time, whether your workloads are on-premises, in the cloud, or containerized, ensuring complete visibility into your AI infrastructure.

Track storage performance metrics like read/write speeds, IOPS, and cache usage to ensure seamless data delivery for I/O-intensive AI workloads, minimizing training and inference delays.

Gain insights into network performance with metrics on bandwidth, latency, and packet loss, supporting high-speed interconnects like InfiniBand and RoCEv2 to optimize data flow for distributed AI workloads.

Proactively detect and mitigate security risks with real-time monitoring of access logs, anomaly detection, and encryption status, ensuring data integrity without compromising performance.

Integrate storage, network, and GPU observability into a single platform, correlating metrics to provide a holistic view of AI infrastructure health and performance, driving faster decision-making.