The SENTINL anomaly detection mechanism is based on the three-sigma rule of thumb. In short, anomalies are the values which lie outside a band around the mean in a normal distribution with a width of two, four and six standard deviations (68.27%, 95.45% and 99.73%).

Let's do an example. We will take a credit card dataset.

  1. Create a new watcher.
  2. In watcher editor, inside Input tab insert Elasticsearch query to get the credit card transactions dataset.
  "search": {
    "request": {
      "index": [
      "body": {
        "size": 10000,
        "query": {
          "bool": {
            "must": [
                "exists": {
                  "field": "Amount"
  1. In the Condition tab specify a minimum number of results to look for > 0 and a field name in which to look for anomalies, Amount in our example.
  "script": {
    "script": " > 0"
  "anomaly": {
    "field_to_check": "Amount"
  1. In Action tab create email html action. In Body HTML field render all the anomalies you have in the payload.anomaly using mustache syntax.
<h1 style="background-color:DodgerBlue;color:white;padding:5px">Anomalies</h1>
<div style="background-color:Tomato;color:white;padding:5px">
<li><b>id:</b> {{_id}} <b>Amount</b>: {{_source.Amount}}</li>

As a result, we have an email with a list of anomaly transactions.

Also, the list of anomalies was indexed in today's alert index watcher_alarms-{year-month-date}.