Edge Delta Datadog Source

The Datadog Agent Source node allows ingestion of logs, metrics, and traces from the Datadog agent with TLS security configurations.

11 minute read

Overview

The Datadog Agent Source node enables the agent to ingest data types such as logs, metrics, and traces from the Datadog agent.

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

Example Configuration

In this example, the port parameter indicates the network port on which the node will listen for incoming data. This port needs to be open and available for the node to accept incoming connections from Datadog agents. The read_timeout specifies the maximum duration the node will wait for incoming data before timing out. This helps manage timeouts and ensures that the node doesn’t hang indefinitely if no data arrives. The tls block contains configurations related to Transport Layer Security (TLS), which is used for securing connections: the ignore_certificate_check parameter indicates whether SSL/TLS certificate verification should be disabled. It is set to false, which means that the node will verify certificates as part of securing the connection. This is important for ensuring a secure data transfer channel.

nodes:
  - name: my_datadog_source
    type: datadog_agent_input
    port: 3421
    read_timeout: 1m
    tls:
      ignore_certificate_check: false

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: datadog_agent_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: datadog_agent_input
    port: <port number>

Optional Parameters

listen

The listen parameter specifies the address to listen on for incoming traffic. The default value is 0.0.0.0, and it is optional.

nodes:
  - name: <node name>
    type: datadog_agent_input
    port: <port number>
    listen: <host>

read_timeout

The read_timeout parameter indicates how long to wait for incoming data before timing out. It is specified as a duration and is optional.

nodes:
  - name: <node name>
    type: datadog_agent_input
    port: <port number>
    read_timeout: <duration>

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.

tls

The tls parameter is a dictionary type that enables a number of TLS options to be set using sub-parameters.

nodes:
  - name: <node name>
    type: datadog_agent_input
    port: <port number>
    tls:
      <tls options>:

ca_file The ca_file parameter is a child of the tls parameter. It specifies the CA certificate file. It is specified as a string and is optional.

nodes:
  - name: <node name>
    type: datadog_agent_input
    port: <port number>
    tls:
      ca_file: /certs/ca.pem

ca_path The ca_path parameter is a child of the tls parameter. It specifies the location of the CA certificate files. It is specified as a string and is optional.

nodes:
  - name: <node name>
    type: datadog_agent_input
    port: <port number>
    tls:
      ca_path: <path>

client_auth_type The client_auth_type parameter is a child of the tls parameter. It specifies the authentication type to use for the connection. It is specified as a string from a closed list and is optional.

The following authentication methods are available:

noclientcert indicates that no client certificate should be requested during the handshake, and if any certificates are sent they will not be verified.
requestclientcert indicates that a client certificate should be requested during the handshake, but does not require that the client send any certificates.
requireanyclientcert indicates that a client certificate should be requested during the handshake, and that at least one certificate is required from the client, but that certificate is not required to be valid.
verifyclientcertifgiven indicates that a client certificate should be requested during the handshake, but does not require that the client sends a certificate. If the client does send a certificate it is required to be valid.
requireandverifyclientcert indicates that a client certificate should be requested during the handshake, and that at least one valid certificate is required to be sent by the client

nodes:
  - name: <node name>
    type: datadog_agent_input
    port: <port number>
    tls:
      client_auth_type: <auth type>

crt_file The crt_file parameter is a child of the tls parameter. It specifies the certificate file. It is specified as a string and is optional.

nodes:
  - name: <node name>
    type: datadog_agent_input
    port: <port number>
    tls:
      crt_file: /certs/server-cert.pem

ignore_certificate_check The ignore_certificate_check parameter is a child of the tls parameter. When set to true, it ignores certificate checks for the remote endpoint. It is specified as a Boolean value and the default is false, indicating that TLS verification will be performed. This is an optional parameter.

nodes:
  - name: <node name>
    type: datadog_agent_input
    port: <port number>
    tls:
      ignore_certificate_check: true

key_file The key_file parameter is a child of the tls parameter. It specifies the private key file. It is specified as a string and is optional.

nodes:
  - name: <node name>
    type: datadog_agent_input
    port: <port number>
    tls:
      key_file: /certs/server-key.pem

key_password The key_password parameter is a child of the tls parameter. It specifies the key password. When the private key_file location is provided, this file can also be provided to get the password of the private key. It is specified as a string and is optional.

nodes:
  - name: <node name>
    type: datadog_agent_input
    port: <port number>
    tls:
      key_password: <password>

max_version The max_version parameter is a child of the tls parameter. It specifies the maximum version of TLS to accept. It is specified as a string and is optional.

You can select one of the following options:

TLSv1_0
TLSv1_1
TLSv1_2
TLSv1_3

nodes:
  - name: <node name>
    type: datadog_agent_input
    port: <port number>
    tls:
      max_version: <TLS version>

min_version The min_version parameter is a child of the tls parameter. It specifies the minimum version of TLS to accept. It is specified as a string and is optional. The default is TLSv1_2.