Observability is a measurement of how quickly a team can understand problems with their system, and it's essential for complex cloud architectures like Kubernetes. Microservices increase the surface area and frequency of software changes, making engineers need better visibility to understand performance and infrastructure. To achieve observability, one must track the overall health and capacity of nodes, monitor dynamic events, correlate log data from all services, understand how microservices communicate with each other, track service performance through integrated telemetry data, correlate performance information with business intelligence, and track requests from source to destination. Maintaining consistent insight into cluster performance is critical for maintaining efficiency, as it helps identify excess capacity that can be more efficiently utilized. By following these steps, engineers can explore, visualize, and troubleshoot their entire Kubernetes environment, leading to better reliability, performance, and efficiency in cloud-native applications and infrastructure.