Edge Delta Filter Processor

The Edge Delta Filter Processor allows filtering of data items from the pipeline based on specific conditions.

  4 minute read  

Overview

You can drop data items based on a specific condition in each data item. For example, you can drop activity performed by a test user.

See Pipeline Quickstart: Filter Data Items for a walkthrough.

Configuration

In this example, all logs with user email jane.smith@exampleemail.com are dropped.

- name: Multi Processor
  type: sequence
  processors:
  - type: ottl_filter
    metadata: '{"id":"C583fhTKWFgbhdWCZOXEz","type":"filter","name":"Filter out test
      user Jane"}'
    condition: attributes["user"]["email"] == "jane.smith@exampleemail.com"
    data_types:
    - log
    filter_mode: exclude

Options

Select a telemetry type

You can specify, log, metric, trace or all. It is specified using the interface, which generates a YAML list item for you under the data_types parameter. This defines the data item types against which the processor must operate. If data_types is not specified, the default value is all. It is optional.

It is defined in YAML as follows:

- name: multiprocessor
  type: sequence
  processors:
  - type: <processor type>
    data_types:
    - log

Action

This option determines what the processor does with matching vs non-matching data items. Include means matching data items are passed and all others are dropped. Exclude means matching data items are dropped and all others are passed. The default is exclude. It is populated for you in YAML using the filter_mode parameter.

It is defined in YAML as follows:

- name: Multi Processor
  type: sequence
  processors:
  - type: ottl_filter
    filter_mode: exclude

In this example, the action is set to Include so only logs containing the jane.smith@exampleemail.com attribute are dropped.

condition

The condition parameter contains a conditional phrase of an OTTL statement. It restricts operation of the processor to only data items where the condition is met. Those data items that do not match the condition are passed without processing. You configure it in the interface and an OTTL condition is generated. It is optional.

Important: All conditions must be written on a single line in YAML. Multi-line conditions are not supported.

Comparison Operators

OperatorNameDescriptionExample
==Equal toReturns true if both values are exactly the sameattributes["status"] == "OK"
!=Not equal toReturns true if the values are not the sameattributes["level"] != "debug"
>Greater thanReturns true if the left value is greater than the rightattributes["duration_ms"] > 1000
>=Greater than or equalReturns true if the left value is greater than or equal to the rightattributes["score"] >= 90
<Less thanReturns true if the left value is less than the rightattributes["load"] < 0.75
<=Less than or equalReturns true if the left value is less than or equal to the rightattributes["retries"] <= 3
matchesRegex matchReturns true if the string matches a regular expression (generates IsMatch function)IsMatch(attributes["name"], ".*\\.log$")

Logical Operators

Important: Use lowercase and, or, not - uppercase operators will cause errors!

OperatorDescriptionExample
andBoth conditions must be trueattributes["level"] == "ERROR" and attributes["status"] >= 500
orAt least one condition must be trueattributes["log_type"] == "TRAFFIC" or attributes["log_type"] == "THREAT"
notNegates the conditionnot regex_match(attributes["path"], "^/health")

Functions

FunctionDescriptionExample
regex_matchReturns true if string matches the patternregex_match(attributes["message"], "ERROR\|FATAL")
IsMatchAlternative regex function (UI generates this from “matches” operator)IsMatch(attributes["name"], ".*\\.log$")

Field Existence Checks

CheckDescriptionExample
!= nilField exists (not null)attributes["user_id"] != nil
== nilField doesn’t existattributes["optional_field"] == nil
!= ""Field is not empty stringattributes["message"] != ""

Common Examples

- name: _multiprocessor
  type: sequence
  processors:
  - type: <processor type>
    # Simple equality check
    condition: attributes["request"]["path"] == "/json/view"
    
  - type: <processor type>
    # Multiple values with OR
    condition: attributes["log_type"] == "TRAFFIC" or attributes["log_type"] == "THREAT"
    
  - type: <processor type>
    # Excluding multiple values (NOT equal to multiple values)
    condition: attributes["log_type"] != "TRAFFIC" and attributes["log_type"] != "THREAT"
    
  - type: <processor type>
    # Complex condition with AND/OR/NOT
    condition: (attributes["level"] == "ERROR" or attributes["level"] == "FATAL") and attributes["env"] != "test"
    
  - type: <processor type>
    # Field existence and value check
    condition: attributes["user_id"] != nil and attributes["user_id"] != ""
    
  - type: <processor type>
    # Regex matching using regex_match
    condition: regex_match(attributes["path"], "^/api/") and not regex_match(attributes["path"], "^/api/health")
    
  - type: <processor type>
    # Regex matching using IsMatch
    condition: IsMatch(attributes["message"], "ERROR|WARNING") and attributes["env"] == "production"

Common Mistakes to Avoid

# WRONG - Cannot use OR/AND with values directly
condition: attributes["log_type"] != "TRAFFIC" OR "THREAT"

# CORRECT - Must repeat the full comparison
condition: attributes["log_type"] != "TRAFFIC" and attributes["log_type"] != "THREAT"

# WRONG - Uppercase operators
condition: attributes["status"] == "error" AND attributes["level"] == "critical"

# CORRECT - Lowercase operators
condition: attributes["status"] == "error" and attributes["level"] == "critical"

# WRONG - Multi-line conditions
condition: |
  attributes["level"] == "ERROR" and 
  attributes["status"] >= 500  

# CORRECT - Single line (even if long)
condition: attributes["level"] == "ERROR" and attributes["status"] >= 500

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See Also