What is an advantage of using model-driven telemetry in the network?

A practical advantage of model-driven telemetry is that it sends structured data in machine-readable encodings, including JSON in supported implementations, making the data easier to consume with modern collectors and automation tools. Model-driven telemetry uses data models, commonly YANG, to define exactly which operational or configuration data is streamed. This is a major improvement over legacy monitoring approaches that repeatedly poll devices or parse human-oriented CLI output. The question option that points to structured JSON compatibility is the best available answer. Telemetry is not based on interrupt-driven polling; it is normally subscription based, either periodic or on-change. It also does not rely on MIB models as its primary structure in the way SNMP does. Parsing show command output is the older, brittle method that model-driven telemetry is intended to replace. The design benefit is cleaner, more predictable, and more programmable network state collection. Reference topics: model-driven telemetry, YANG data models, JSON encoding, subscription-based monitoring, network programmability.