When you are creating conditions, the Policy Editor counts the number of metrics that apply to the conditions you have set. To view those metrics, click on the link. This link opens the list of matching metrics in a new tab.
Policy Name> Edit Policy > Conditions > Add Metric Conditions.
Use the Match Conditions feature to toggle between enforcing all conditions listed or just any one condition. See below:
A Baseline Deviation test triggers an event and other optional notifications when the current value of a metric is above and/or below 4 standard deviations from its normal operating range. A Baseline Deviation test can also be used to trigger an event when the value of a metric is or is not deviating from its normal operating range. Metricly determines the normal operating range of a metric based on the history of the actual values for that metric. The different Baseline Deviation tests are described below:
A Contextual Deviation test can be used to indicate when the value of a metric is above and/or below 4 standard deviations from its expected value. A Contextual Deviation test can also be used to indicate when a metric is deviating when it should not be, or is not deviating when it should be. Metricly determines the expected value for a metric based on the actual values of other correlated metrics in the learned model. The different Contextual Deviation tests are described below:
A Static Threshold test is used to trigger an event and other optional actions when the value of a metric is more than, less than, equal to, or not equal to a specified level. The level for a Static Threshold test can be any real number; the unit of the level depends on the metric to which it is applied.
For example, you can use a Static Threshold test to execute an event when the current value for the metric “CPU Utilization” is greater than 95%.
A Sudden Change deviation test is used to indicate the difference between expected change and unexpected change on a certain metric. This is achieved by using historical data to predict future data intervals. The historical data used to determine the future interval is a sliding window of one hour that contextualizes future intervals.
The Analytics Engine uses the following steps to detect a sudden change:
Percent change = |(observed value - projected value)| / |projected value|
Metric thresholds are unchanging levels that are compared against another metric’s current value. A Metric Threshold test can be used to indicate when the value of the specified metric is more than, less than, equal to, or not equal to another metric.