Docs » Configure detectors and alerts in SignalFx µAPM » Use default alert conditions in SignalFx µAPM » Latency - historical anomaly

Latency - historical anomaly 🔗

Note

This page explains how to use this condition when you are creating a µAPM detector. If you are creating an Infrastructure or Custom Metrics detector, see this page instead.

What this alert condition does 🔗

Alerts when latency anomalously spikes compared to the same periods in the past (for cyclical or seasonal data). Anomaly can be defined through number of deviations from historical norm or percentage change compared to historical norm.

When to use this alert condition 🔗

Use this alert condition to monitor values where patterns that repeat over known, fixed periods of time. To specify the period of time over which patterns repeat, use the Cycle length parameter. For example, the count of concurrent logins in your environment may have a weekly pattern in which Monday mornings generally have more logins than Friday nights, and latency might normally vary between those times. To compare current and historical Monday morning values, set Cycle length to 1w.

Basic settings 🔗

PARAMETER VALUES USAGE NOTES
Cycle length Integer >= 1, followed by time indicator (s, m, h, d, w), e.g. 30s, 10m, 2h, 5d, 1w. Value should be significantly larger than the signal resolution. The time range that reflects the cyclicity of your signal. For example, a value of 1w indicates your signal follows a weekly cycle (you want to compare data for a Monday morning with previous Monday mornings). A value of 1d indicates your signal follows a daily cycle (you want to compare today’s data with data from the same time yesterday, the day before, etc.)
Trigger Sensitivity Low, Medium, High, Custom Approximately how often alerts will be triggered, where Low can result in fewer alerts being triggered and alerts taking longer to clear (least flappy). Choose Custom to modify the settings that determine triggering and clearing sensitivity (listed below).

Advanced settings 🔗

PARAMETER VALUES USAGE NOTES
Alert based on Deviations from history, Percentage change If the short-term variation in a signal is small relative to the scale of the signal, and the scale is somehow natural, using Percentage change is recommended; using Deviations from history may trigger alerts even for a large number of standard deviations.
Percentile to monitor (when Alert based on is Percentage change) 50, 90, 99 The percentile to monitor. For example, a value of 90 measures changes in the 90th percentile latency value.
Current window Integer >= 1, followed by time indicator (s, m, h, d, w), e.g. 30s, 10m, 2h, 5d, 1w. Value should be smaller than Cycle length, and should be significantly larger than the signal resolution. The time range against which to compare the data; you can think of this as the moving average window. Higher values compute the change over more datapoints, which generally smoothes the value, resulting in lower sensitivity and potentially fewer alerts.
Historical window Integer >= 1, followed by time indicator (s, m, h, d, w), e.g. 30s, 10m, 2h, 5d, 1w. Value should be smaller than Cycle length, and should be significantly larger than the signal resolution. The time window that defines normal values. For example, 1w indicates values from the preceding week can be considered normal.
Number of previous cycles Integer >=1 and <= 8 Works in conjunction with cycle length. The number of cycles to use for setting a historical norm, or baseline. For example, if your cycle length is 1w, this value specifies how many prior weeks you want to use when computing a historical norm. To consider last week the norm, use the value 1; to consider the mean of the last 4 weeks the norm, use the value 4. Higher values mean more data is used to define the baseline.
Trigger threshold and Clear threshold (when Alert based on is Deviations from history) Number >= 0; Clear threshold must be lower than Trigger threshold

The number of standard deviations away from the norm required to trigger or clear an alert.

For example, a trigger value of 3.5 will trigger an alert when the values being compared differ by 3.5 standard deviations or more. Higher values result in lower sensitivity and potentially fewer alerts.

A clear value of 2.5 will clear the alert when the values being compared differ by 2.5 standard deviations or less. Higher values result in alerts taking longer to clear.

Trigger threshold % and Clear threshold % (when Alert based on is Percentage change) Number between 0 and 100, inclusive; Clear threshold must be lower than Trigger threshold.

The percentage difference from the historical norm required to trigger or clear the alert.

For example, a trigger value of 30 will trigger an alert when the values being compared differ by 30% or more. Higher values result in lower sensitivity and potentially fewer alerts.

A clear value of 20 will clear the alert when the values being compared differ by 20% or less. Higher values result in alerts taking longer to clear.

Exclude errors Yes, No Whether to include or exclude error spans from the calculations.
Min. req/sec (absolute) Number Minimum requests/second required in current window to trigger or clear the alert; prevents alerts for sparse data.
Min. req/sec (% of history) Number between 0 and 100, inclusive Minimum requests/second, as a percentage of the historical rate, required in current window to trigger or clear the alert; prevents alerts for sparse data.