dcgm

GPU Cluster Monitoring (GCM): Large-Scale AI Research Cluster Monitoring

GPU Observability with workload attribution. One OTLP agent per node ties hardware metrics (NVIDIA, AMD, Intel Gaudi) to the K8s pod or Slurm job burning the GPU.

Diff your NetBox/Nautobot intent against LLDP, Redfish and DCGM. Apache-2.0.

A virtual GPU hall: emulated switches, BMCs and GPUs with fault injection. Apache-2.0.

Hands-on GPU/HPC infrastructure operations: K8s GPU scheduling, HAMi sharing, Slurm, observability & vLLM inference. Learn it free on a laptop; validate on one cheap GPU.

Autoscale NVIDIA Triton on Kubernetes by GPU utilisation — DCGM, Prometheus adapter, HPA, GPU time-slicing. Tested end-to-end.

top-like TUI for per-pod GPU usage in Kubernetes (zero cluster footprint)

Single-file interactive study tool for the NVIDIA NCP-AI Operations exam: quiz, flashcards, guided labs, and a stateful BCM/Slurm/Kubernetes/DCGM command sandbox.

GPU 风扇控制台：按 GPU 温度闭环调速服务器机箱风扇（IPMI raw + FastAPI + Vue3 + SQLite，DCGM/Prometheus 数据源，带安全护栏/看门狗），附带按 CPU 温度控速的 Dell PowerEdge 旧版脚本 | Web-based IPMI server fan control driven by GPU temperature

面向HCU卡的Go语言管理与监控工具，提供设备发现、健康诊断、遥测数据采集、进程监控和性能压力测试能力，并支持CLI与REST API调用。

Simulate NVIDIA GPUs for testing. 7 behavior profiles, scale to 1000+ GPUs, Docker-ready Prometheus exporter using DCGM

Moved to freelensapp/freelens-gpu-extension (npm @freelensapp/gpu-extension)

Freelens extension for GPUs

FakeAI: Rapid Development and Testing for AI Infrastructure

End-to-end observability for disaggregated LLM inference on EKS — DCGM metrics, KEDA autoscaling on GPU signals, per-namespace cost attribution, multi-agent OTel tracing, and Istio mTLS. Reference implementation for the OpenTelemetry AI Inference Platform blueprint.

Self-hosted, read-only GPU fleet reliability & capacity intelligence for Kubernetes. Correlates DCGM/Prometheus telemetry with K8s state into deterministic incident reports.

GPU-native agent-swarm orchestration for the NVIDIA AI stack — NeMo, NIM, Triton, DCGM, NGC, NIXL, OpenShell. Spawn GPU-pinned agent teams across DGX/HGX nodes with NVLink-aware scheduling, task DAGs, adaptive scheduling, and full observability.

Find out how many GPU-hours you're paying for and not using

Self-hosted GPU monitoring and cost intelligence: live NVIDIA metrics, idle and waste detection, exact per-workload cost attribution, alerts and inference metrics, with a demo mode that needs no GPU.

Automated acceptance toolkit for Linux deep learning GPU servers