anchor.diff:  <2> Define the Nelson Rules to activate (Rule1, Rule2, ..., Rule8) for metric-data-id (all rules are activated by default)
   <3> Define the sampleSize (by default this value is set to 50)
   
  -Each rule is focus on specific patterns as it is described below
  +Each rule represents a specific pattern as described below:
   
   === Rule 1
   
  
positive.code: 
  Applying Nelson Rules in our scenario can help to detect potential "out of control" situations.
  
  But as discussed, modelling scenarios is highly dependent of the nature of the Domain, and applying Nelson Rules do not fully guarantee avoiding false alerts nor substitute the assistance of the Domain's Analyst to evaluate the quality of the model.
negative.code: :jbake-status: published
  :jbake-tags: blog, alerts, alerting, advanced, nelson
  
  == Modeling Conditions
  
  Hawkular Alerting offers several types of link:http://www.hawkular.org/community/docs/developer-guide/alerts.html#_conditions[Conditions] for defining Triggers. Most of the Conditions deal with numeric data but String, Availability and Event data are also supported.
  
  Modeling scenarios for detecting behaviours is highly dependent on the nature of the Domain being represented.  The Domain may only require simple numeric threshold conditions to efficiently detect unexpected situations.
  
  In other domains, it can be non-trivial to identify unusual metric variations that may lead to a problem.
  Simple thresholds are not expressive enough to detect metric patterns or trends that can identify potential problems.
  
  == Nelson Rules
  
  Hawkular Alerting supports Conditions based on link:https://en.wikipedia.org/wiki/Nelson_rules[Nelson Rules] to enable advanced detection on Numeric metrics.
  
  These rules are based on the mean and the standard deviation of the samples and offer additional techniques for modeling complex scenarios.
  
  For example,
  
  