Huawei lists “Performance bottleneck analysis” as one of the major DME IQ intelligent-computing capabilities, together with noisy-neighbor analysis, disk-risk prediction, workload planning, performance-exception detection, and capacity prediction.
DME IQ uses collected performance and configuration data to assess whether storage workloads are operating normally, whether resources are balanced, or whether resource pressure has resulted in overload. Accordingly, the load-status classifications in this interface are Balanced, Overloaded, and Normal.
Optimizable is not one of the load-status values in this classification. Optimization is an O & M action or analytical recommendation rather than the load state assigned to a resource on the Performance Bottlenecks page.
The broader course explains that DME IQ uses cloud-native AI, machine learning, and deep-learning analysis for performance prediction, fault reporting, capacity prediction, risk prediction, and proactive O & M. These capabilities supply the data used by bottleneck analysis.
The retrieved Training/Lab text explicitly documents the Performance Bottleneck Analysis capability, although it does not separately reproduce the UI table containing the three status-label names.
Study Guide Topics: Data Storage Management and O & M → DME IQ → Performance Bottleneck Analysis → Intelligent Computing → Performance Diagnosis.
