CCNP Practice Question: A network operations center (NOC) is deploying…

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✓

  Google Protocol Buffers (GPB) encoding.

  Why this is correct

  GPB (Google Protocol Buffers) is a binary, schema-based serialization format that produces compact payloads, drastically reducing bandwidth and CPU overhead compared to text encodings. Its generated codecs and native support in gRPC make it the standard choice for high-volume, model-driven streaming telemetry on Cisco platforms. Because the schema is defined in .proto files and tied to YANG models, decoding is fast and unambiguous, even under sustained telemetry rates.

• ✗

  JSON encoding.

  Why it's wrong here

  JSON is a text-based, human-readable format that is far more verbose than GPB, leading to larger payloads and increased bandwidth consumption. Parsing JSON requires CPU-intensitive string handling, which becomes a bottleneck when thousands of telemetry updates arrive per second. While JSON is usable with YANG data models, its lack of a schema for binary efficiency and its per-message overhead make it suboptimal for real-time streaming telemetry, where minimal latency and resource usage are critical.

• ✗

  XML encoding.

  Why it's wrong here

  XML is an overly verbose, text-based markup language that wraps every data element in opening and closing tags, often including namespaces, making its payloads significantly larger than even JSON. Parsing XML is CPU-heavy and memory-intensive because the parser must construct a full document tree, which is impractical for high-frequency streaming telemetry. Although XML is used in NETCONF for configuration management, its bulky nature and slow processing eliminate it as a viable encoding for real-time network telemetry streaming over gRPC or gNMI.

• ✗

  CSV encoding.

  Why it's wrong here

  CSV is a simple flat-file format that can represent only tabular data, not the nested, hierarchical structures typically found in YANG-based telemetry models. It lacks a formal schema, data typing, and standardized mapping to telemetry concepts, so a collector would be unable to interpret fields reliably without external context. Worse, commas, quotes, and newlines within data values can break the semantics, and the absence of compression or binary optimization makes CSV unsuitable for high-volume streaming telemetry on network devices.