As enterprises increasingly adopt cloud-native architectures, the rapid growth of metrics cardinality in observability systems like Prometheus has become a significant concern due to its impact on infrastructure costs and performance. This growth is driven by the complexity of microservices and Kubernetes environments, where each layer and component generates unique time series data, compounded by the ease of instrumentation and lack of centralized governance. High cardinality leads to increased infrastructure demands and can slow down query performance, affecting troubleshooting efficiency. To address this, enterprises are advised to gain visibility into which metrics and labels contribute most to cardinality, identify valuable metrics, and optimize data collection practices, such as adjusting scrape intervals and refining label usage. Tools like Grafana Cloud offer features for tracking and managing metrics cardinality, helping organizations attribute costs to specific teams and optimize their observability strategies effectively.