As AI and large language model (LLM) workloads increasingly rely on GPU infrastructure, efficient GPU management becomes crucial for maintaining performance and cost-effectiveness. Inefficient GPU usage can lead to longer runtimes and increased expenses due to idle or underutilized resources. Datadog GPU Monitoring provides a comprehensive solution by offering real-time insights into GPU fleet health, utilization, and cost, allowing teams to quickly identify and resolve issues such as overprovisioning, resource contention, and hardware failures. The platform enables users to monitor cloud and on-premises deployments, track spending, and optimize GPU allocation to enhance operational efficiency. By addressing both workload inefficiencies and underlying hardware constraints, Datadog ensures that AI workloads run smoothly without unnecessary financial strain, thus supporting scalable and high-performing AI infrastructure.