Glossary¶
Quick Lookup¶
Common terms used in this module:
- Signal - a derived metric created from raw data
- Raw Metric - a directly recorded measurement from a system
- Derived Metric - a value calculated from one or more raw metrics
- Error Rate - proportion of errors relative to total requests
- Latency - the time required for a system to respond to a request
- Throughput - the volume of work processed by a system (for example, number of requests)
Raw Metric¶
A measurement recorded directly from a system. Examples:
- number of requests
- number of errors
- total latency
Raw metrics describe what happened but may not be the easiest values to interpret.
Signal¶
A signal is a derived metric designed to make system behavior easier to understand. Signals are usually created by combining or transforming raw metrics. Examples:
- error rate
- average latency per request
- throughput
Signals help analysts monitor system health and detect unusual behavior.
Error Rate¶
The proportion of failed requests relative to total requests. This signal helps identify reliability problems in a system.
Latency¶
The time required for a system to respond to a request. In this module, we often compute average latency per request:
Throughput¶
The amount of work processed by a system in a given observation period. Examples include:
- requests handled
- transactions processed
- messages delivered
Feature Engineering¶
The process of creating new variables (features or signals) from existing data. Signal design is a form of feature engineering for monitoring systems. Feature engineering often includes:
- ratios (errors / requests)
- averages (latency per request)
- aggregations (rolling means)
- transformations (log, scaling, normalization)
Signal Design¶
The process of creating useful signals from raw system metrics. Well-designed signals make system behavior easier to monitor and interpret, which is essential for continuous intelligence systems.