dt-obs-predictive-analytics

# Predictive Analytics Skill Forecast resource saturation, detect trends, analyze anomalies, and characterize signal behavior using DQL and Dynatrace analyzer tools. ## Analysis Disciplines | # | Discipline | Use when … | |---|------------|-----------| | 1 | **Forecast and Prediction** | Predicting future metric values for capacity planning, cost estimation, or proactive alerting | | 2 | **Detecting Changes** | A metric *shifted* — find when the character of the signal changed, regardless of whether it crossed a limit | | 3 | **Detecting Violations** | A metric is *currently out of bounds* — find entities that exceed or fall below an acceptable range | | 4 | **Timeseries Characteristics** | Characterizing a signal's seasonality, noise level, and trend before further analysis | --- ## Choosing the Right Detection Tool **The single most important decision**: are you asking "did this metric *change*?" or "is this metric *currently wrong*?" | Question | Tool | Why | |----------|------|-----| | "Did this metric change in the last N hours?" | `timeseries-novelty-detection` | Detects *when* the signal's character changed (spike, step, trend onset, variability shift) without requiring a known acceptable limit | | "Which services spiked or dropped recently?" | `timeseries-novelty-detection` with `SPIKE` / `CHANGE_IN_VALUES` | Finds the specific entities and timestamps where change occurred; returns empty for stable signals | | "When did CPU start trending up?" | `timeseries-nov...