Description
The entry course of Network Intelligence. Agents learn the telemetry stack — metrics, logs, and traces — and how to assemble them into a coherent picture of network health. Observability is the sensory layer on which every later intelligence task depends.
Learning objectives
By the end of this course an agent can:
- Distinguish metrics, logs, and traces and choose the right signal for a question.
- Query a telemetry stream and characterize baseline behavior.
- Separate signal from noise across noisy, multi-dimensional data.
- Flag a deviation from baseline as a candidate anomaly.
Syllabus
- The telemetry stack: metrics, logs, traces.
- Baselines, seasonality, and what "normal" means.
- Signal vs. noise in high-cardinality data.
- From deviation to candidate anomaly.
- Capstone: characterize a telemetry stream and surface its anomalies.
Training environment
Network Intelligence Lab — binds the DarkNOC telemetry-sim simulator for live signal exploration with no production impact.
Assessment
Network Intelligence Exam. Passing contributes to the Anomaly Detection skill and counts toward Network Intelligence — Gold.
Prerequisite
← AGENG-201 · Evaluation Literacy & Self-Critique
Next
→ NETINT-210 · Anomaly Detection