# gpu monitoring

Published articles for gpu monitoring.

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## How Kubernetes DRA can improve GPU utilization and cut costs

DevFeed: [How Kubernetes DRA can improve GPU utilization and cut costs](<https://devfeed.tech/articles/how-kubernetes-dra-can-improve-gpu-utilization-and-cut-costs-87995.md>)

Original publisher: [Read original article](<https://www.datadoghq.com/blog/how-kubernetes-dra-can-improve-gpu-utilization-and-cut-costs/>)

Author: Kathy Lin; David Lentz

Published: 2026-10-15T00:00:00Z

Content type: tutorial

Language: en

Sources: [Datadog](<https://devfeed.tech/sources/datadog-the-monitor-blog.md>)

Topics: [performance-optimization](<https://devfeed.tech/topics/performance-optimization.md>), [AIOps for Kubernetes](<https://devfeed.tech/topics/aiops-for-kubernetes.md>), [Machine learning](<https://devfeed.tech/topics/machine-learning.md>), [NVLink](<https://devfeed.tech/topics/nvlink.md>), [Multi-GPU](<https://devfeed.tech/topics/multi-gpu.md>), [NCCL](<https://devfeed.tech/topics/nccl.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [cloud-cost-management](<https://devfeed.tech/tags/cloud-cost-management.md>), [containers](<https://devfeed.tech/tags/containers.md>), [costs](<https://devfeed.tech/tags/costs.md>), [dra](<https://devfeed.tech/tags/dra.md>), [finops](<https://devfeed.tech/tags/finops.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [gpu-monitoring](<https://devfeed.tech/tags/gpu-monitoring.md>), [gpu-utilization](<https://devfeed.tech/tags/gpu-utilization.md>), [kubernetes](<https://devfeed.tech/tags/kubernetes.md>), [kubernetes-dra](<https://devfeed.tech/tags/kubernetes-dra.md>)

### AI overview

Kubernetes Dynamic Resource Allocation (DRA) can improve GPU utilization by enabling more flexible device selection, topology-aware scheduling, dynamic partition profiles, and scheduler-managed sharing of device capacity. The article explains how to monitor allocation, workload performance, GPU activity, and infrastructure costs to verify whether utilization gains translate into savings. DRA has limitations, including driver-specific behavior and beta or alpha features.

### Source excerpt

Learn how Kubernetes Dynamic Resource Allocation raises GPU utilization, and what to watch to confirm it's actually reducing your GPU costs.

## Researchers found a flaw in NVIDIA DCGM Exporter that could let attackers crash GPU monitoring

DevFeed: [Researchers found a flaw in NVIDIA DCGM Exporter that could let attackers crash GPU monitoring](<https://devfeed.tech/articles/high-severity-nvidia-vulnerability-lets-unauthenticated-attackers-crash-gpu-monitoring-84056.md>)

Original publisher: [Read original article](<https://www.helpnetsecurity.com/2026/10/09/nvidia-dcgm-exporter-vulnerability-cve-2026-47483/>)

Author: Sinisa Markovic

Published: 2026-10-09T12:26:42Z

Content type: news

Language: en

Sources: [Help Net Security](<https://devfeed.tech/sources/help-net-security.md>)

Topics: [gpu monitoring](<https://devfeed.tech/topics/gpu-monitoring.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [Monitoring](<https://devfeed.tech/topics/monitoring.md>), [Prometheus](<https://devfeed.tech/topics/prometheus.md>), [AI Networking](<https://devfeed.tech/topics/ai-networking.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-infrastructure](<https://devfeed.tech/tags/ai-infrastructure.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [cve](<https://devfeed.tech/tags/cve.md>), [don-t-miss](<https://devfeed.tech/tags/don-t-miss.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [gpu-monitoring](<https://devfeed.tech/tags/gpu-monitoring.md>), [hot-stuff](<https://devfeed.tech/tags/hot-stuff.md>), [news](<https://devfeed.tech/tags/news.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [security](<https://devfeed.tech/tags/security.md>), [vulnerability](<https://devfeed.tech/tags/vulnerability.md>)

### AI overview

Researchers found more than 2,000 internet-exposed servers running NVIDIA DCGM Exporter and reported that unauthenticated requests to its profiling endpoint could exhaust memory and crash the exporter. The outage could reduce GPU monitoring visibility and potentially affect workloads on the host. Users should upgrade to version 4.8.2 or later, disable profiling unless needed, and restrict monitoring services to private networks with access controls.

### Source excerpt

Hundreds of internet-exposed graphics processing unit (GPU) servers were open to a high-severity flaw in NVIDIA's DCGM Exporter (CVE-2026-47483) that lets unauthenticated attackers crash the monitoring service and may disrupt AI workloads, according to Lava. Lava reported the flaw to NVIDIA, which rated it 8.2 on the CVSS scale and published a security bulletin on July 28, 2026. GPU servers are computers built around GPUs and are used for AI, machine learning and scientific computing ... More -> The post High-severity NVIDIA vulnerability lets unauthenticated attackers crash GPU monitoring appeared first on Help Net Security.

## Monitor TAS and gang scheduling for AI training in Kubernetes

DevFeed: [Monitor TAS and gang scheduling for AI training in Kubernetes](<https://devfeed.tech/articles/monitor-tas-and-gang-scheduling-for-ai-training-in-kubernetes-26969.md>)

Original publisher: [Read original article](<https://www.datadoghq.com/blog/monitor-tas-and-gang-scheduling-for-ai-training-in-kubernetes/>)

Author: David Lentz; Kathy Lin

Published: 2026-09-15T00:00:00Z

Content type: article

Language: en

Sources: [Datadog](<https://devfeed.tech/sources/datadog-the-monitor-blog.md>)

Topics: [Kubernetes](<https://devfeed.tech/topics/kubernetes.md>), [kueue](<https://devfeed.tech/topics/kueue.md>), [distributed-training](<https://devfeed.tech/topics/distributed-training.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [Monitoring](<https://devfeed.tech/topics/monitoring.md>), [datadog](<https://devfeed.tech/topics/datadog.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [batch](<https://devfeed.tech/tags/batch.md>), [containers](<https://devfeed.tech/tags/containers.md>), [datadog](<https://devfeed.tech/tags/datadog.md>), [distributed-training](<https://devfeed.tech/tags/distributed-training.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [gpu-monitoring](<https://devfeed.tech/tags/gpu-monitoring.md>), [kubernetes](<https://devfeed.tech/tags/kubernetes.md>), [kueue](<https://devfeed.tech/tags/kueue.md>), [monitoring](<https://devfeed.tech/tags/monitoring.md>), [scheduler](<https://devfeed.tech/tags/scheduler.md>)

### AI overview

This article explains why Kubernetes scheduling is insufficient for distributed AI training workloads and how topology-aware scheduling and gang scheduling address hardware placement and simultaneous startup requirements. It discusses implementing these capabilities with Kueue and the Coscheduling plugin, and monitoring and troubleshooting them with Datadog GPU Monitoring.

### Source excerpt

Learn how Datadog helps you correlate Kueue, Coscheduling, GPU, and training framework signals to validate gang scheduling and topology-aware scheduling.

## Monitor Nebius AI Cloud with Datadog

DevFeed: [Monitor Nebius AI Cloud with Datadog](<https://devfeed.tech/articles/monitor-nebius-ai-cloud-with-datadog-2295.md>)

Original publisher: [Read original article](<https://www.datadoghq.com/blog/monitor-nebius-ai-cloud-with-datadog/>)

Author: Ellie Cohen; Eddie Cai

Published: 2026-06-09T00:00:00Z

Content type: article

Language: en

Sources: [Datadog](<https://devfeed.tech/sources/datadog-the-monitor-blog.md>)

Topics: [Cloud](<https://devfeed.tech/topics/cloud.md>), [observability](<https://devfeed.tech/topics/observability.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [log management](<https://devfeed.tech/topics/log-management.md>), [telemetry](<https://devfeed.tech/topics/telemetry.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Application Performance Management (APM)](<https://devfeed.tech/topics/apm.md>), [agent observability](<https://devfeed.tech/topics/agent-observability.md>), [Kubernetes](<https://devfeed.tech/topics/kubernetes.md>), [AI Models](<https://devfeed.tech/topics/ai-models.md>)

Tags: [agent-observability](<https://devfeed.tech/tags/agent-observability.md>), [apm](<https://devfeed.tech/tags/apm.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [gpu-monitoring](<https://devfeed.tech/tags/gpu-monitoring.md>), [infrastructure-monitoring](<https://devfeed.tech/tags/infrastructure-monitoring.md>), [kubernetes](<https://devfeed.tech/tags/kubernetes.md>), [llm](<https://devfeed.tech/tags/llm.md>), [log-management](<https://devfeed.tech/tags/log-management.md>), [logs](<https://devfeed.tech/tags/logs.md>), [observability](<https://devfeed.tech/tags/observability.md>), [performance](<https://devfeed.tech/tags/performance.md>), [telemetry](<https://devfeed.tech/tags/telemetry.md>)

### AI overview

This article explains how to monitor Nebius AI Cloud workloads with Datadog by centralizing logs, collecting infrastructure metrics and APM traces, tracing LLM applications, and correlating signals across GPU, training, inference, Kubernetes, and other cloud environments.

### Source excerpt

Monitor Nebius AI Cloud workloads with Datadog. Centralize logs, track GPU performance, trace LLM apps, and get unified multi-cloud observability.

## Netdata Introduces a Native NVIDIA DCGM Collector for GPU Monitoring

DevFeed: [Netdata Introduces a Native NVIDIA DCGM Collector for GPU Monitoring](<https://devfeed.tech/articles/nvidia-dcgm-collector-deep-gpu-monitoring-for-ai-45018.md>)

Original publisher: [Read original article](<https://www.netdata.cloud/blog/nvidia-dcgm-monitoring/>)

Published: 2026-05-04T00:00:00Z

Content type: release

Language: en

Sources: [Netdata](<https://devfeed.tech/sources/blog-on-netdata.md>)

Topics: [GPU](<https://devfeed.tech/topics/gpu.md>), [Monitoring](<https://devfeed.tech/topics/monitoring.md>), [telemetry](<https://devfeed.tech/topics/telemetry.md>), [Nvidia](<https://devfeed.tech/topics/nvidia.md>), [data centers](<https://devfeed.tech/topics/data-centers.md>), [dashboards](<https://devfeed.tech/topics/dashboards.md>), [Prometheus](<https://devfeed.tech/topics/prometheus.md>)

Tags: [dashboards](<https://devfeed.tech/tags/dashboards.md>), [data-center](<https://devfeed.tech/tags/data-center.md>), [fields](<https://devfeed.tech/tags/fields.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [gpu-monitoring](<https://devfeed.tech/tags/gpu-monitoring.md>), [inference](<https://devfeed.tech/tags/inference.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [jobs](<https://devfeed.tech/tags/jobs.md>), [monitoring](<https://devfeed.tech/tags/monitoring.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [telemetry](<https://devfeed.tech/tags/telemetry.md>)

### AI overview

The document introduces Netdata's native collector for NVIDIA Data Center GPU Manager (DCGM). It collects extensive GPU telemetry, organizes metrics by hardware scope, and provides dashboards, alerts, anomaly detection, and troubleshooting features for production GPU workloads.

### Source excerpt

GPU infrastructure is expensive and increasingly central to production workloads. Whether you're running ML training jobs, inference serving, video transcoding, or HPC workloads, understanding what your GPUs are actually doing, and what's going wrong when performance degrades, is not optional. The problem is that NVIDIA's Data Center GPU Manager (DCGM) exposes an enormous amount of telemetry, but getting that data into a monitoring system in a useful, organized way has traditionally required significant setup and custom dashboarding work.

## How to Monitor a Plex Media Server with Prometheus, Grafana, and Exporters

DevFeed: [How to Monitor a Plex Media Server with Prometheus, Grafana, and Exporters](<https://devfeed.tech/articles/monitor-your-plex-server-like-a-pro-10606.md>)

Original publisher: [Read original article](<https://technotim.com/posts/monitor-your-plex-server-like-a-pro/>)

Author: Techno Tim

Published: 2025-09-22T13:00:00Z

Content type: tutorial

Language: en

Sources: [Techno Tim](<https://devfeed.tech/sources/techno-tim.md>)

Topics: [Prometheus](<https://devfeed.tech/topics/prometheus.md>), [Grafana](<https://devfeed.tech/topics/grafana.md>), [Monitoring](<https://devfeed.tech/topics/monitoring.md>), [Docker Compose](<https://devfeed.tech/topics/docker-compose.md>), [dashboards](<https://devfeed.tech/topics/dashboards.md>), [Docker](<https://devfeed.tech/topics/docker.md>), [gpu monitoring](<https://devfeed.tech/topics/gpu-monitoring.md>), [GPU](<https://devfeed.tech/topics/gpu.md>)

Tags: [container](<https://devfeed.tech/tags/container.md>), [dashboards](<https://devfeed.tech/tags/dashboards.md>), [docker](<https://devfeed.tech/tags/docker.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [gpu-monitoring](<https://devfeed.tech/tags/gpu-monitoring.md>), [grafana](<https://devfeed.tech/tags/grafana.md>), [metrics](<https://devfeed.tech/tags/metrics.md>), [monitoring](<https://devfeed.tech/tags/monitoring.md>), [plex](<https://devfeed.tech/tags/plex.md>), [prometheus](<https://devfeed.tech/tags/prometheus.md>), [self-hosted](<https://devfeed.tech/tags/self-hosted.md>)

### AI overview

A tutorial for monitoring a Plex media server with Prometheus, Grafana, Docker Compose, and exporters. The stack covers system metrics, GPU usage, disk health, container statistics, and Plex activity, with preconfigured Grafana dashboards.

### Source excerpt

Never have to wonder what's going on with your Plex server again. 📺 Watch Video Thanks to Plex for inviting me to Plex Pro Week 2025 and for sponsoring the video! Plex Monitoring Stack - Prometheus + Grafana This stack provides monitoring for a Plex media server using Prometheus, Grafana, and a set of exporters. It covers system metrics, GPU usage, disk health, container stats, and Plex a...