ManageEngine® SQLDBManager Plus


Anomaly Detection

<< Prev

Home

Next >>

 

Anomaly Detection

 

Anomaly detection helps you know if there is gradual performance degradation by defining Anomaly Profiles on performance metrics.  By creating Anomaly profiles, you can define rules wherein the current data is compared with previously reported best data.

 

For eg., if the load on the server increases over a period of time, response time will gradually be affected. By using Anomaly detection, you would be able to detect this performance problem.

 

How Anomaly Detection Works?

 

Anomaly Profiles can be created based on

Anomaly Dashboard: This dashboard facilitates viewing through all the performance metrics and helps in easy troubleshooting.

 

anomaly-flow

 

Baseline Values:

 

Anomaly happens when the current set of values don't confirm to the baseline range values. Current Attribute values are compared against the reported data in a particular week [baseline week].


 

Creating Anomaly Profile based on Baseline values



Custom Expressions

 

Anomaly is detected when current data doesn't confirm to the user defined rules [based on system variables]. For eg., you can create a rule like Anomaly is to be detected when the current Last Hour Average Value is greater than twice the Six Hours Moving Average Value. Critical and Warning alarms can be set accordingly.

 

The system variables that can be used for forming custom expressions are

 

Expressions Meaning
$10D_MVA Ten Days Moving Average
$LastHourValue Last Hour Average
$6H_MVA Six Hours Moving Average
$30D_MVA Thirty Days Moving Average
$10H_MVA Ten Hours Moving Average
$7D_MVA Seven Days Moving Average

 

Creating Anomaly Profile based on Custom Expressions

 

 

 

Associating Anomaly profile



Note: A particular monitor's health will be made critical and EMail notification will be sent only if the user had associated EMail action to the health of the dependant attribute

 


Anomaly Dashboard

 

This dashboard facilitates viewing through all the performance metrics. It helps the user to intuitively scan through the hundreds of performance metrics with ease.

 



<< Prev

Home

Next >>

Error Handling

Icon Representation