DevNet Associate (DEVASC) v1.0Infrastructure and AutomationMedium
A network engineer wants to automate the process of collecting real-time interface statistics (e.g., bandwidth utilization, packet drops) from a large number of routers and switches. The collected data needs to be continuously streamed to an analytics platform for immediate anomaly detection. Which network telemetry approach is best suited for this requirement?
- ASyslog
- BCLI Scraping
- CStreaming Telemetry
- DSNMP Polling
Show answer & explanationAnswer & explanation
Correct answer: C. Streaming Telemetry
Streaming Telemetry provides continuous, real-time data push from network devices, often using protocols like gRPC or NETCONF notifications, directly to a collector. This is ideal for immediate anomaly detection and large-scale data collection, unlike periodic polling or event-based logging.
Why the other options are wrong
- A. Syslog is primarily for event logging, not for continuous streaming of detailed interface statistics.
- B. CLI Scraping is inefficient, unstructured, and not suitable for real-time, high-volume data collection across many devices.
- D. SNMP Polling is periodic and pull-based, leading to higher latency and scalability issues for real-time, high-volume data.
Streaming Telemetry
Streaming Telemetry is a network monitoring approach where devices continuously push real-time operational data to a collector. It offers higher granularity, lower latency, and better scalability than traditional polling methods like SNMP.
- Continuous data push (pub/sub model)
- Real-time and high-frequency data
- Uses protocols like gRPC, NETCONF notifications
- Ideal for large-scale, dynamic environments
- Enables immediate anomaly detection
Memory trick: Stream your data, catch the real-time drama.