Observing Kubernetes can be likened to bird-watching, where understanding the distinct signals emitted by various components is more critical than having the perfect tools. Key components to observe include the control plane, nodes, pods, and containers, each emitting signals categorized into metrics, logs, and traces. These signals help deduce the cluster's status and are crucial for a Kubernetes cluster administrator. Metrics provide numerical insights over time, logs offer records of actions, and traces capture request pathways. Effective Kubernetes observability requires integrating various tools and best practices, such as dashboards for visualization and machine learning for anomaly detection, to maintain operational efficiency and preemptively address potential issues. Elastic Observability is highlighted as a comprehensive solution for managing and analyzing these signals to ensure a holistic view of the Kubernetes environment.