What are dynamic or smart thresholds, and why would you enable them in NPM?

What are dynamic or smart thresholds, and why would you enable them in NPM?

• A. They rely on fixed baselines that never change.
• B. They apply to a single device and ignore historical data.
• C. They automatically adjust baselines based on historical data to reduce false positives and adapt to normal changes in network behavior.
• D. They disable alerting entirely.

Answer: (C)

Dynamic or smart thresholds adjust automatically based on historical data to establish baselines that reflect normal network behavior. They continuously learn from past measurements and move the threshold as the observed patterns shift, whether due to daily or weekly cycles, growing traffic, or gradual changes in usage. This means alerts trigger for genuinely unusual activity rather than for routine fluctuations, reducing false positives and alert storms. By adapting to the current normal, they stay relevant as the network evolves, so you’re alerted only when a deviation truly indicates an issue. For example, if a link’s typical usage increases over time, dynamic thresholds rise with it; a fixed threshold would either miss the new normal or cause unnecessary alerts.

Dynamic or smart thresholds adjust automatically based on historical data to establish baselines that reflect normal network behavior. They continuously learn from past measurements and move the threshold as the observed patterns shift, whether due to daily or weekly cycles, growing traffic, or gradual changes in usage. This means alerts trigger for genuinely unusual activity rather than for routine fluctuations, reducing false positives and alert storms. By adapting to the current normal, they stay relevant as the network evolves, so you’re alerted only when a deviation truly indicates an issue. For example, if a link’s typical usage increases over time, dynamic thresholds rise with it; a fixed threshold would either miss the new normal or cause unnecessary alerts.