Routing Rule JSON structure

The exported rule is in JSON format that can be edited and imported if needed. A basic rule with two outbound mappings looks the following:

{
"version": 1,
"changeDescription": "test",
"createdTime": 1607344697357,
"createdBy": "user@oneio.cloud",
"enabled": true,
"current": false,
"activatedTime": 1607344697357,
"activatedBy": "user@oneio.cloud",
"action": "ROUTE",
"ruleId": "2d5b51cde6674907a49f90a7b218c5a4",
"name": "test rule",
"sourceSystemId": "sebastian_snc_jira_snc",
"sourceEntityType": "incident",
"targetSystemId": "sebastian_jira",
"targetEntityType": "Issue",
"targetMessageType": "",
"entityConditions": [],
"conversationConditions": [],
"delayConditions": [],
"virtualAttributeMappings": [],
"mappings": [
{
"type": "Single",
"template": "${short_description}",
"sourceFormatters": [],
"targetAttribute": "fields.summary"
},
{
"type": "Single",
"template": "${description}",
"sourceFormatters": [],
"targetAttribute": "fields.description"
}
],
"conversationAttributeMappings": [],
"attachmentMapping": {
"extensionBlacklist": [],
"filterFilesWithoutExtension": false,
"mapAttachmentsFromConversation": false,
"removeAttachmentsFromConversation": false,
"mapAttachmentsFromSourceMessage": false
},
"priority": 0,
"routeOneTargetPerAttachment": false,
"saveAttachmentsToConversation": false,
"linkedRules": []
}

The first section shows the inbound endpoint, entity and message type, routing information and the outbound endpoint, entity type and message type. 

This information is followed by the mappings in this order:

Lets have a look at a single mapping and which attributes are part of this mapping.

{
"type": "Single",
"template": "${short_description}",
"sourceFormatters": [],
"targetAttribute": "fields.summary"
}

This mapping consists of four attributes, with a fifth attribute fallbackValue only added when in use.

Type options

TableTranslate

TableTranslate is a very powerful way of mapping one or more related source attributes to one or more target attributes at the same time. It is probably the most commonly used mapping type after Copy and Template.

For a TableTranslate, you define one to several source to target attribute pairs. When the source matches, the target will be result of the mapping. 

The matching happens from first to last in the translation table. This means, that the first line that matches the source attribute value is used.

For source, you can use value, match and null as detailed below:

For target, you can use value, valueExpression and null as detailed below:

In the following example, we're mapping from multi-level category the another multi-level category:

{
   "type":"TableTranslate",
   "template":[
      "category1",
      "category2"
   ],
   "targetAttributes":[
      "cat_a",
      "cat_b"
   ],
   "translationTable":[
      {
         "source":[
            {
               "value":"ADVANCED ORDERS"
            },
            {
               "value":"DIFFERENT STUFF"
            }
         ],
         "target":[
            {
               "value":"Acme"
            },
            {
               "value":"CAT-000316"
            }
         ]
      },
      {
         "source":[
            {
               "match":"ANY"
            },
            {
               "value":"STUFF"
            }
         ],
         "target":[
            {
               "value":"Small Potatoes"
            },
            {
               "value":"CAT-000316"
            }
         ]
      },
      {
         "source":[
            {
               "match":"BLANK"
            },
            {
               "match":"BLANK"
            }
         ],
         "target":[
            {
               "value":"Small Potatoes"
            },
            {
               "valueExpression":"CAT-${category_id}"
            }
         ]
      }
   ]
}

MultiValueToSingle

Whenever you have a list of values from the same source which need to be aggregated to the same target field then this mapping is handy.

E.g. if ONEiO receives the following JSON containing an array:

{root: { array: ["first", "second"]}}

It would be mapped into two ONEiO attributes with the name "root.array" and the values: "first" and "second": 

root.array: first
root.array: second

These two attributes can be mapped into one single field with the "Multiple values to single value" mapping. A mapping with the delimiter ", " would map the "root.array" multi-value into the value "first, second". Here's an example of the resulting field: 

singleField: first, second

Here's an example of how the configuration looks like:

{
"type": "MultiValueToSingle",
"sourceAttribute": "root.array",
"targetAttribute": "singleField",
"delimiter": ", "
}

The delimiter is ", " by default, but can be configured to anything.

CounterIncrement

There are some cases when we want to decide what to do based on how many times something has happened. For these cases, there's a CounterIncrement mapping, which can increment integer-valued conversation attributes. The next example increments counter myCounter: 

{
"type": "CounterIncrement",
"counterName": "sf:conversation:counter:myCounter",
}

CounterReset

There are some cases when we want to reset a counter which was incremented with CounterIncrement mapping. This can be done with a Reset counter mapping. The next example resets counter myCounter to zero:

{
"type": "CounterReset",
"counterName": "sf:conversation:counter:myCounter",
}

Source Formatter options

{
"type": "Single",
"template": "${description}",
"sourceFormatters": [
{
"type": "RegExp",
"expression": "^.*\\(Work notes\\)\\s*([\\s\\S]*)"
}
],
"targetAttribute": "summary"
}

{
"type": "Single",
"template": "${description_truncate}",
"sourceFormatters": [
{
"type": "Truncate",
"length": 255
}
],
"targetAttribute": "description_truncate"
}

{
"type": "Single",
"template": "${description_lowercase}",
"sourceFormatters": [
{
"type": "Lowercase"
}
],
"targetAttribute": "description_lowercase"
}

{
"type": "Single",
"template": "${description_uppercase}",
"sourceFormatters": [
{
"type": "Uppercase"
}
],
"targetAttribute": "description_uppercase"
}

{
"type": "Single",
"template": "${description_capitalize}",
"sourceFormatters": [
{
"type": "Capitalize"
}
],
"targetAttribute": "description_capitalize"
}

{
"type": "Single",
"template": "${description_remove_html}",
"sourceFormatters": [
{
"type": "RemoveHtmlTags"
}
],
"targetAttribute": "description_remove_html"
}

{
"type": "Single",
"template": "${description_replace}",
"sourceFormatters": [
{
"type": "ReplaceAll",
"template": ":",
"replacement": "-",
"isRegex": false
}
],
"targetAttribute": "description_replace"
}

{
"type": "Single",
"template": "${description_date}",
"sourceFormatters": [
{
"type": "Date",
"fromFormat": "dd/mm/yyyy",
"fromTimeZone": "Europe/Helsinki",
"toFormat": "mm/dd/yyyy",
"toTimeZone": "America/Chicago"
}
],
"targetAttribute": "description_date"
}

{
"type": "Single",
"template": "${description_translate}",
"sourceFormatters": [
{
"type": "LanguageTranslate",
"target": "en",
"source": "fi"
}
],
"targetAttribute": "description_translate"
}

{
"type": "Single",
"template": "${description_trim}",
"sourceFormatters": [
{
"type": "Trim"
}
],
"targetAttribute": "description_trim"
}

Using multiple formatters in attribute mapping

There is also support for using multiple formatters for the same attribute mapping. The formatters are applied in the order they are in the sourceFormatters array. Here's an example on first selecting text with a regular expression and then truncating the result to 5 characters:

{
"type": "Single",
"template": "${description_truncate}",
"sourceFormatters": [
{
"type": "RegExp",
"expression": "(INC.*)"
},
{
"type": "Truncate",
"length": 5
}
],
"targetAttribute": "description_truncate"
}