Observability is an approach to understanding complex software systems by collecting, visualizing, and analyzing telemetry data in real-time. It goes beyond traditional monitoring techniques by providing a fully connected view of all software telemetry data, allowing teams to master the performance of their digital architecture, accelerate innovation, and reduce operational costs. Observability requires integrating three essential components: collecting exhaustive and granular telemetry data, correlating and contextualizing the data, and visualizing the data and making it actionable. It also enables connection, contextualization, and curation, allowing teams to analyze telemetry data in real-time, visualize complex systems, and surface critical information and insights quickly. Modern observability collects four major complementary telemetry classes: metrics, events, logs, and traces (M.E.L.T.), ensuring exhaustive and open collection by complementing proprietary agents with open-source tools. It guarantees interoperability of all types of data and telemetry, automatically identifying, creating, and maintaining entities, and surfacing connections between them. Observability also enables visibility, actionability, and programmability, allowing teams to build applications that optimize software investments, measure efficiency in real-time, and make objective decisions to maximize performance. With the increasing demands of digital transformation, companies must adopt observability to achieve optimal speed and performance, differentiate themselves from competition, and meet customers' expectations.