Business event processing

You can create a processing rule that transforms incoming events.

You can also specify the retention time for your events by assigning them to buckets.

Example 1. Add a new calculated field to the pipeline.
As a user, you need to add a calculated dollar trading volume value to the pipeline.

{
 "action":"buy",
 "accountId":6,
 "amount":10,
 "instrumentId":1,
 "price":157.025
}

Example 2. Mask your data.
You need to hide the CVV field on your credit card in an incoming JSON payload.

{
 "action": "payment",
 "creditCardNumber":"5570001112223344",
 "valid":"12/27",
 "cvv":"001"
}

Example 3. Drop event attribute.
You need to drop the birthdate field in an incoming JSON payload.

{
 "action": "newUser",
 "firstName":"Frank",
 "lastName": "Underwud",
 "birthDate": "10.01.1967"
}

Example 4. Parse nested JSON.
You need to parse attributes from a nested JSON in order to have them as top-level attributes in Grail.

{
  "action":"sell",
  "details":{
     "accountId":6,
     "amount":10,
     "instrumentId":1,
     "price":157.025
   }
 }

Example 5. Parse error message.

In this example, you need to remove the voucher code from the error message field below to have the ability to count how often the same error message appears. The solution below leverages the Dynatrace Pattern language for parsing.

{
"timestamp":"2023-01-18T10:50:23.777000000Z",
"cartId":"58583939",
"error.message":"The voucher [XY-892940] is not valid!",
"error.messageKey":"error.voucher "
}