KAYTUS has developed KSManage AI Data Centers to increase the visibility of full-stack O&M management of AI workloads. Operational robustness is increased along with faster incident management for complex AI environments. KSManage AI Data Centers can assist in addressing the difficulties that arise from the intricacies of AI operations. The first difficulty is related to the heterogeneity of the infrastructure of computation, storage, and networking. There is a lack of end-to-end visibility of problems that delay resolution and restoration processes.
Additionally, the rising workload for GPUs and storage raises the risks of hardware failure. Predictive mechanisms that detect potential hardware failure do not exist. Furthermore, AI systems such as AIGC and autonomous vehicles make it difficult to monitor. However, hardware failures remain challenging to link to any specific AI load. Fourthly, there is an additional difficulty due to human intervention in addressing the O&M requirements for AI data centers. Thus, mean time to repair is increased, which results in reduced service availability.
KSManage AI Data Centers Provides End-to-End Visibility
The KSManage AI Data Centers provides end-to-end visibility through the entire infrastructure stack.It collects real-time metrics from GPUs, CPUs, storage, and networks continuously. Additionally, it uses 3D visualization to map workloads across entire systems. Therefore, troubleshooting becomes faster and improves efficiency by up to 90%. KSManage AI Data Centers introduces predictive analytics for hardware health management. It identifies GPU and storage risks up to seven days in advance.
Moreover, it monitors temperature and workload to prevent system failures. KSManage AI Data Centers connects application workloads with network performance metrics. It tracks bandwidth, latency, and packet loss with high precision. As a result, it quickly identifies root causes of training interruptions. This prevents rollback and reduces wasted computing resources significantly.
KSManage AI Data Centers enables automated four-level O&M operations efficiently. It achieves high backup success rates and rapid fault detection. Additionally, it uses AI-driven algorithms to identify root causes quickly. Consequently, MTTR decreases while operational efficiency increases significantly. Finally, it reduces total cost of ownership through proactive maintenance.
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Source: Businesswire
