Edge Delta Deotel Processor

The Edge Delta Deotel processor converts OpenTelemetry formatted data back to simplified formats for non-OTLP destinations.

6 minute read

Overview

The Deotel (De-OpenTelemetry) processor extracts the core content from OpenTelemetry formatted telemetry data, removing all OTLP wrapper metadata. It takes a specified field (typically body) from the OpenTelemetry structure and outputs only that field’s content, discarding resource attributes, trace context, and other metadata.

The Deotel processor is ideal for:

Sending logs to legacy systems that don’t support OTLP format
Forwarding data to custom applications in their original format
Reducing data size by removing OpenTelemetry metadata

Do not use the Deotel processor when:

Your destination supports OpenTelemetry/OTLP format
You need trace context for distributed tracing
You need resource metadata for infrastructure correlation
Your downstream system benefits from OpenTelemetry semantic conventions

Data Loss

The Deotel processor permanently removes OpenTelemetry metadata including:

Trace context (trace_id, span_id) for distributed tracing
Resource attributes (service name, host information, Kubernetes metadata)
Semantic conventions and standardized field names
Timestamp information from the OTLP wrapper

If you need to preserve some OpenTelemetry metadata in the output, use OTTL Transform before Deotel to merge important fields into the body or whichever field you configure the deotel processor to preserve:

processors:
- type: ottl_transform
  statements: |
    set(body_map, ParseJSON(body))
    set(body_map["service"], resource["service.name"]) 
    set(body_map["pod"], resource["k8s.pod.name"])
    set(body, String(body_map))

Configuration

You configure the Deotel processor by specifying which field to extract and preserve from the OpenTelemetry structure. The processor removes all other fields and outputs only the extracted content.

Example Input

Suppose the following OpenTelemetry formatted log is sent to the Deotel processor:

{
  "_type": "log",
  "timestamp": 1755065085076,
  "body": "{\"timestamp\":\"2025-08-13T06:04:44+00:00\",\"level\":\"INFO\",\"message\":\"Test log 4\",\"service\":\"test-service\",\"trace_id\":\"trace-4\"}",
  "resource": {
    "container.id": "123456789",
    "container.image.name": "docker.io/library/123456:latest",
    "ed.domain": "k8s",
    "ed.filepath": "/var/log/pods/busy_test-deotel_123456789/test-deotel/0.log",
    "ed.source.name": "kubernetes_input_50df",
    "ed.source.type": "kubernetes_input",
    "host.ip": "172.19.0.2",
    "host.name": "ed-api-testbench-control-plane",
    "k8s.container.name": "test-deotel",
    "k8s.namespace.name": "busy",
    "k8s.node.name": "ed-api-testbench-control-plane",
    "k8s.pod.name": "test-deotel",
    "k8s.pod.uid": "123456789",
    "service.name": "Unknown"
  },
  "attributes": {
    "level": "INFO",
    "message": "Test log 4",
    "service": "test-service",
    "timestamp": "2025-08-13T06:04:44+00:00",
    "trace_id": "trace-4"
  }
}

This configuration extracts only the body field:

- name: deotel_processor
  type: sequence
  processors:
  - type: deotel
    metadata: '{"id":"unique_id","type":"deotel","name":"Deotel"}'
    data_types:
    - log
    field_path: body

Example Output

The processor outputs only the content of the body field:

{"timestamp":"2025-08-13T06:04:44+00:00","level":"INFO","message":"Test log 4","service":"test-service","trace_id":"trace-4"}

Note how the Deotel processor:

Extracted only the body field content
Removed all resource attributes (container, Kubernetes, host information)
Removed the attributes object
Removed timestamp and _type fields
Output the original log format without any OpenTelemetry wrapper

Options

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

Operator	Name	Description	Example
`==`	Equal to	Returns `true` if both values are exactly the same	`attributes["status"] == "OK"`
`!=`	Not equal to	Returns `true` if the values are not the same	`attributes["level"] != "debug"`
`>`	Greater than	Returns `true` if the left value is greater than the right	`attributes["duration_ms"] > 1000`
`>=`	Greater than or equal	Returns `true` if the left value is greater than or equal to the right	`attributes["score"] >= 90`
`<`	Less than	Returns `true` if the left value is less than the right	`attributes["load"] < 0.75`
`<=`	Less than or equal	Returns `true` if the left value is less than or equal to the right	`attributes["retries"] <= 3`
`matches`	Regex match	Returns `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!

Operator	Description	Example
`and`	Both conditions must be true	`attributes["level"] == "ERROR" and attributes["status"] >= 500`
`or`	At least one condition must be true	`attributes["log_type"] == "TRAFFIC" or attributes["log_type"] == "THREAT"`
`not`	Negates the condition	`not regex_match(attributes["path"], "^/health")`

Functions

Function	Description	Example
`regex_match`	Returns `true` if string matches the pattern	`regex_match(attributes["message"], "ERROR\\|FATAL")`
`IsMatch`	Alternative regex function (UI generates this from “matches” operator)	`IsMatch(attributes["name"], ".*\\.log$")`

Field Existence Checks

Check	Description	Example
`!= nil`	Field exists (not null)	`attributes["user_id"] != nil`
`== nil`	Field doesn’t exist	`attributes["optional_field"] == nil`
`!= ""`	Field is not empty string	`attributes["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

field_path

The field to extract and preserve from the OpenTelemetry structure. Typically body or an enriched attribute.

Final

Determines whether successfully processed data items should continue through the remaining processors in the same processor stack. If final is set to true, data items output by this processor are not passed to subsequent processors within the node—they are instead emitted to downstream nodes in the pipeline (e.g., a destination). Failed items are always passed to the next processor, regardless of this setting.

The UI provides a slider to configure this setting. The default is false. It is defined in YAML as follows:

- name: multiprocessor
  type: sequence
  processors:
    - type: <processor type>
    final: true