Edge Delta OTLP Source

The OTLP source node consumes telemetry data from configured sources using gRPC or HTTP protocols.

8 minute read

Overview

The OTLP source node consumes data items directly from OTLP configured data sources. The node is configured with the port that the agent should listen on.

AI Team: Configure this source using the OTLP connector for streamlined setup in AI Team.

outgoing_data_types: log, metric, trace

The OTLP source supports standard and exponential histogram metrics, ingesting full bucket-level data from OpenTelemetry sources.

Configure OTLP

See Prepare to Ingest from an OTLP Source for information on configuring your data sources for OTLP and obtaining the port number.

Example Configuration

Create an OTLP source node for the port to ingest logs, metrics and traces.

nodes:
- name: OTLP logs
  port: 4324
  protocol: grpc
  read_timeout: 1m0s

Required Parameters

name

A descriptive name for the node. This is the name that will appear in pipeline builder and you can reference this node in the YAML using the name. It must be unique across all nodes. It is a YAML list element so it begins with a - and a space followed by the string. It is a required parameter for all nodes.

nodes:
  - name: <node name>
    type: <node type>

type: otlp_input

The type parameter specifies the type of node being configured. It is specified as a string from a closed list of node types. It is a required parameter.

nodes:
  - name: <node name>
    type: <node type>

port

The port parameter specifies the port number to listen on. It is specified as an integer and is required.

nodes:
- name: <node name>
  type: otlp_input
  port: <port number>

protocol

The protocol parameter defines which protocol is being used to send items to the OTLP source. You can specify either grpc or http. If you select HTTP you can also specify a read timeout. The default is gRPC and a protocol is required.

nodes:
- name: <node name>
  type: otlp_input
  port: <port number>
  protocol: http|grpc

Optional Parameters

read_timeout

The read_timeout parameter defines a wait time timeout for HTTP connections. You specify it a duration. The default is 1m and it is optional.

nodes:
- name: <node name>
  type: otlp_input
  port: <port number>
  protocol: http
  read_timeout: 2m

rate_limit

The rate_limit parameter enables you to control data ingestion based on system resource usage. This advanced setting helps prevent source nodes from overwhelming the agent by automatically throttling or stopping data collection when CPU or memory thresholds are exceeded.

Use rate limiting to prevent runaway log collection from overwhelming the agent in high-volume sources, protect agent stability in resource-constrained environments with limited CPU/memory, automatically throttle during bursty traffic patterns, and ensure fair resource allocation across source nodes in multi-tenant deployments.

When rate limiting triggers, pull-based sources (File, S3, HTTP Pull) stop fetching new data, push-based sources (HTTP, TCP, UDP, OTLP) reject incoming data, and stream-based sources (Kafka, Pub/Sub) pause consumption. Rate limiting operates at the source node level, where each source with rate limiting enabled independently monitors and enforces its own thresholds.

Configuration Steps:

Click Add New in the Rate Limit section
Click Add New for Evaluation Policy
Select Policy Type:

CPU Usage: Monitors CPU consumption and rate limits when usage exceeds defined thresholds. Use for CPU-intensive sources like file parsing or complex transformations.
Memory Usage: Monitors memory consumption and rate limits when usage exceeds defined thresholds. Use for memory-intensive sources like large message buffers or caching.
AND (composite): Combines multiple sub-policies with AND logic. All sub-policies must be true simultaneously to trigger rate limiting. Use when you want conservative rate limiting (both CPU and memory must be high).
OR (composite): Combines multiple sub-policies with OR logic. Any sub-policy can trigger rate limiting. Use when you want aggressive rate limiting (either CPU or memory being high triggers).

Select Evaluation Mode. Choose how the policy behaves when thresholds are exceeded:

Enforce (default): Actively applies rate limiting when thresholds are met. Pull-based sources (File, S3, HTTP Pull) stop fetching new data, push-based sources (HTTP, TCP, UDP, OTLP) reject incoming data, and stream-based sources (Kafka, Pub/Sub) pause consumption. Use in production to protect agent resources.
Monitor: Logs when rate limiting would occur without actually limiting data flow. Use for testing thresholds before enforcing them in production.
Passthrough: Disables rate limiting entirely while keeping the configuration in place. Use to temporarily disable rate limiting without removing configuration.

Set Absolute Limits and Relative Limits (for CPU Usage and Memory Usage policies)

Note: If you specify both absolute and relative limits, the system evaluates both conditions and rate limiting triggers when either condition is met (OR logic). For example, if you set absolute limit to 1.0 CPU cores and relative limit to 50%, rate limiting triggers when the source uses either 1 full core OR 50% of available CPU, whichever happens first.

For CPU Absolute Limits: Enter value in full core units:
- 0.1 = one-tenth of a CPU core
- 0.5 = half a CPU core
- 1.0 = one full CPU core
- 2.0 = two full CPU cores
For CPU Relative Limits: Enter percentage of total available CPU (0-100):
- 50 = 50% of available CPU
- 75 = 75% of available CPU
- 85 = 85% of available CPU
For Memory Absolute Limits: Enter value in bytes
- 104857600 = 100Mi (100 × 1024 × 1024)
- 536870912 = 512Mi (512 × 1024 × 1024)
- 1073741824 = 1Gi (1 × 1024 × 1024 × 1024)
For Memory Relative Limits: Enter percentage of total available memory (0-100)
- 60 = 60% of available memory
- 75 = 75% of available memory
- 80 = 80% of available memory

Set Refresh Interval (for CPU Usage and Memory Usage policies). Specify how frequently the system checks resource usage:

Recommended Values:
- 10s to 30s for most use cases
- 5s to 10s for high-volume sources requiring quick response
- 1m or higher for stable, low-volume sources

The system fetches current CPU/memory usage at the specified refresh interval and uses that value for evaluation until the next refresh. Shorter intervals provide more responsive rate limiting but incur slightly higher overhead, while longer intervals are more efficient but slower to react to sudden resource spikes.

The GUI generates YAML as follows:

# Simple CPU-based rate limiting
nodes:
  - name: <node name>
    type: <node type>
    rate_limit:
      evaluation_policy:
        policy_type: cpu_usage
        evaluation_mode: enforce
        absolute_limit: 0.5  # Limit to half a CPU core
        refresh_interval: 10s

# Simple memory-based rate limiting
nodes:
  - name: <node name>
    type: <node type>
    rate_limit:
      evaluation_policy:
        policy_type: memory_usage
        evaluation_mode: enforce
        absolute_limit: 536870912  # 512Mi in bytes
        refresh_interval: 30s

Composite Policies (AND / OR)

When using AND or OR policy types, you define sub-policies instead of limits. Sub-policies must be siblings (at the same level)—do not nest sub-policies within other sub-policies. Each sub-policy is independently evaluated, and the parent policy’s evaluation mode applies to the composite result.

AND Logic: All sub-policies must evaluate to true at the same time to trigger rate limiting. Use when you want conservative rate limiting (limit only when CPU AND memory are both high).
OR Logic: Any sub-policy evaluating to true triggers rate limiting. Use when you want aggressive protection (limit when either CPU OR memory is high).

Configuration Steps:

Select AND (composite) or OR (composite) as the Policy Type
Choose the Evaluation Mode (typically Enforce)
Click Add New under Sub-Policies to add the first condition
Configure the first sub-policy by selecting policy type (CPU Usage or Memory Usage), selecting evaluation mode, setting absolute and/or relative limits, and setting refresh interval
In the parent policy (not within the child), click Add New again to add a sibling sub-policy
Configure additional sub-policies following the same pattern

The GUI generates YAML as follows:

# AND composite policy - both CPU AND memory must exceed limits
nodes:
  - name: <node name>
    type: <node type>
    rate_limit:
      evaluation_policy:
        policy_type: and
        evaluation_mode: enforce
        sub_policies:
          # First sub-policy (sibling)
          - policy_type: cpu_usage
            evaluation_mode: enforce
            absolute_limit: 0.75  # Limit to 75% of one core
            refresh_interval: 15s
          # Second sub-policy (sibling)
          - policy_type: memory_usage
            evaluation_mode: enforce
            absolute_limit: 1073741824  # 1Gi in bytes
            refresh_interval: 15s

# OR composite policy - either CPU OR memory can trigger
nodes:
  - name: <node name>
    type: <node type>
    rate_limit:
      evaluation_policy:
        policy_type: or
        evaluation_mode: enforce
        sub_policies:
          - policy_type: cpu_usage
            evaluation_mode: enforce
            relative_limit: 85  # 85% of available CPU
            refresh_interval: 20s
          - policy_type: memory_usage
            evaluation_mode: enforce
            relative_limit: 80  # 80% of available memory
            refresh_interval: 20s

# Monitor mode for testing thresholds
nodes:
  - name: <node name>
    type: <node type>
    rate_limit:
      evaluation_policy:
        policy_type: memory_usage
        evaluation_mode: monitor  # Only logs, doesn't limit
        relative_limit: 70  # Test at 70% before enforcing
        refresh_interval: 30s

source_metadata

This option is used to define which detected resources and attributes to add to each data item as it is ingested by Edge Delta. You can select:

Required Only: This option includes the minimum required resources and attributes for Edge Delta to operate.
Default: This option includes the required resources and attributes plus those selected by Edge Delta
High: This option includes the required resources and attributes along with a larger selection of common optional fields.
Custom: With this option selected, you can choose which attributes and resources to include. The required fields are selected by default and can’t be unchecked.

Based on your selection in the GUI, the source_metadata YAML is populated as two dictionaries (resource_attributes and attributes) with Boolean values.

See Choose Data Item Metadata for more information on selecting metadata.