How do dashboards support anomaly detection in telemetry?

• A. They offer visual cues, trend graphs, thresholds, and automated alerts to identify deviations and trigger investigations.
• B. They generate predictive models without user interaction.
• C. They provide raw logs only.
• D. They replace human analysis entirely.

Answer: (A)

Dashboards support anomaly detection by combining visual trends, baselines, thresholds, and alerts into a single, actionable view. They present telemetry as time-series charts so you can see how metrics evolve over time and quickly spot deviations from normal patterns. Baselines or moving averages help you determine what “normal” looks like, while thresholds highlight when a metric crosses a critical limit. When something anomalous happens, automated alerts triggered from these thresholds or anomaly signals notify you to investigate, so you can respond quickly. This setup lets you correlate different metrics—like CPU usage, error rates, and latency—to understand the root cause of an anomaly, rather than sifting through raw data. Dashboards don’t replace human analysis; they enhance it by turning complex data into clear, timely insights.