Edge Delta Telemetry Generator Source

The Telemetry Generator Source node generates sample logs, metrics, and traces for testing pipeline configurations.

Overview

The TelemetryGen Source node generates sample logs, metrics or traces at a specified rate. Use this node to quickly configure and test a pipeline using data similar to your use case.

See Effective Pipeline Design for details on using templates to test and validate pipeline configurations.

Key Features

  • Multi-line log support: Paste multi-line logs and generate multiple outputs. A new breaker splits logs by newline, JSON objects, or a custom regex. Previously, each line required a separate format.
  • Multi-metric templates: Create multiple metrics in a single template for comprehensive metric testing.
  • Import/Export templates: Move templates between organizations or import them into the shared template library for reuse.
  • Attribute and Resource support: Add attributes to enrich your logs, metrics, and traces for more realistic test data.

Example Configuration

This configuration will emit an Apache Error every 1 second.

nodes:
- name: telemetrygen_input_41ae
  type: telemetrygen_input
  user_description: Telemetry Generator Source
  events_per_sec: 1
  template_type: log
  templates:
  - Apache Error

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: telemetrygen_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>

events_per_sec

The events_per_second parameter specifies the number of data items that will be generated per second. It is specified as an integer and is a required parameter.

nodes:
- name: <node name>
  type: telemetrygen_input
  events_per_sec: 2
  template_type: <type>
  templates:
  - <template name>

templates

The templates parameter specifies the data item schema the node should emit. It is specified with the template_type. It is specified as a string and a template is required. You can now specify multiple templates in a single configuration.

nodes:
- name: <node name>
  type: telemetrygen_input
  events_per_sec: <rate>
  template_type: <type>
  templates:
  - <template name>

For metrics, you can create multi-metric templates that generate multiple metrics in a single template:

nodes:
- name: metric_generator
  type: telemetrygen_input
  events_per_sec: 1
  template_type: metric
  templates:
  - <multi-metric template name>

Optional Parameters

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:

  1. Click Add New in the Rate Limit section
  2. Click Add New for Evaluation Policy
  3. 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).
  1. 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.
  1. 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
  1. 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:

  1. Select AND (composite) or OR (composite) as the Policy Type
  2. Choose the Evaluation Mode (typically Enforce)
  3. Click Add New under Sub-Policies to add the first condition
  4. 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
  5. In the parent policy (not within the child), click Add New again to add a sibling sub-policy
  6. 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