UDP Connector

Configure the UDP connector to receive logs, metrics, and telemetry data sent via UDP datagrams from applications, systems, and network devices for AI-powered analysis.

  7 minute read  

Overview

The UDP connector receives logs, metrics, and telemetry data sent via UDP (User Datagram Protocol) datagrams from applications, systems, and network devices. UDP is a connectionless protocol providing fire-and-forget message delivery with minimal overhead, ideal for high-volume, low-latency data ingestion where occasional packet loss is acceptable. Content streams into Edge Delta Pipelines for analysis by AI teammates through the Edge Delta MCP connector.

The connector acts as a UDP server, receiving and processing datagrams from monitoring agents, applications, network infrastructure, and IoT devices. It supports high-volume metrics (StatsD), application logs, network telemetry (NetFlow, sFlow), and sensor data with automatic format detection for JSON, plain text, and StatsD metrics.

When you add this streaming connector, it appears as a UDP source in your selected pipeline. AI teammates access this data by querying the Edge Delta backend with the Edge Delta MCP connector.

For comprehensive UDP source configuration details, see the UDP Source documentation.

Add the UDP Connector

To add the UDP connector, you configure Edge Delta to listen on a specified UDP port for incoming datagrams.

Prerequisites

Before configuring the connector, ensure you have:

  • Edge Delta agent with network access to receive UDP traffic
  • Firewall rules allowing inbound UDP traffic on chosen port
  • Applications or systems ready to send data via UDP
  • For ports below 1024, root/admin privileges (or use ports 1024+)

Configuration Steps

  1. Navigate to AI Team > Connectors in the Edge Delta application
  2. Find the UDP connector in Streaming Connectors
  3. Click the connector card
  4. Configure Port (3421 default or custom)
  5. Configure Listen address (default 0.0.0.0)
  6. Configure Read Timeout (how long to wait for data)
  7. Optionally configure Advanced Settings for rate limiting
  8. Select a target environment
  9. Click Save

The connector deploys and begins listening for UDP datagrams.

UDP connector configuration showing port, listen address, and read timeout settings

Configuration Options

Connector Name

Name to identify this UDP connector instance.

Port

UDP port to listen on for incoming datagrams.

Format: Integer between 1 and 65535

Default: 3421

Examples:

  • 514 - Standard syslog port (requires root/admin)
  • 8125 - StatsD metrics port
  • 9090 - Custom metrics port (non-privileged)
  • 3421 - Edge Delta default

Note: Ports below 1024 require root/admin privileges on Linux/Unix systems

Listen

IP address to bind to for listening.

Format: IPv4 address

Default: 0.0.0.0 (all interfaces)

Examples:

  • 0.0.0.0 - Listen on all network interfaces
  • 192.168.1.100 - Listen only on specific interface
  • 127.0.0.1 - Localhost only (testing)

Read Timeout

How long to wait for incoming data before timing out.

Format: Duration (seconds, minutes)

Default: 1m

Examples:

  • 30s - 30 seconds for responsive sources
  • 1m - 1 minute typical timeout
  • 5m - 5 minutes for sparse streams

Purpose: Controls how long UDP socket waits for datagrams

Note: UDP is connectionless; timeout affects waiting period, not connection state

Advanced Settings

Metadata Level (Resource Attributes)

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.

UDP-specific metadata included:

  • Host name - Edge Delta agent hostname
  • Host IP - Edge Delta agent IP address
  • Server port - Port connector is listening on
  • Service name - Service identifier
  • Source name - Connector instance name
  • Source type - UDP connector type

Network metadata (when enabled):

  • Source IP address - Sender’s IP address
  • Source port - Sender’s port number

Metadata Level (Attributes)

Additional attribute-level metadata fields to include.

Default: ed.env.id

Rate Limit

Rate limit configuration to control volume of UDP data accepted.

Purpose: Protects Edge Delta from being overwhelmed by excessive datagram rates

Configuration:

  • Evaluation Policy: Policy to decide whether source will be rate limited

When to Use: Prevent high-volume senders from overwhelming the pipeline or enforce data volume quotas

Note: UDP has no backpressure mechanism; rate limiting drops excess packets

How to Use the UDP Connector

The UDP connector integrates seamlessly with AI Team, enabling data ingestion from UDP-capable sources. AI teammates automatically leverage UDP-ingested data to analyze StatsD metrics, investigate application logs, monitor network telemetry, and track IoT sensor data.

Use Case: StatsD Metrics Collection

Collect StatsD metrics from distributed microservices for performance monitoring. Applications send counters, gauges, and timers via UDP to Edge Delta. AI teammates analyze performance trends, identify anomalies, and correlate metrics with application events without manual dashboard monitoring.

Configuration:

  • Port: 8125
  • Listen: 0.0.0.0
  • Read Timeout: 30s

Application Configuration (Node.js):

const StatsD = require('node-statsd');
const client = new StatsD({
  host: 'edge-delta-host',
  port: 8125
});

client.increment('api.requests');
client.gauge('api.response_time', 245);

Use Case: High-Volume Application Logging

Ingest application logs in JSON format via UDP for low-latency centralized analysis. Applications send logs as UDP datagrams, avoiding TCP connection overhead. AI teammates provide real-time error detection and pattern analysis across distributed services.

Configuration:

  • Port: 9090
  • Listen: 0.0.0.0
  • Read Timeout: 1m

Application Configuration (Python):

import socket
import json

sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
log_entry = json.dumps({
    "level": "error",
    "message": "Payment processing failed",
    "timestamp": "2025-10-08T12:00:00Z"
})
sock.sendto(log_entry.encode(), ('edge-delta-host', 9090))

Use Case: Network Device Telemetry

Receive network telemetry (NetFlow, sFlow) from switches and routers for infrastructure monitoring. Network devices send flow records via UDP. AI teammates analyze traffic patterns, detect bandwidth anomalies, and identify security threats from network behavior.

Configuration:

  • Port: 6343
  • Listen: 0.0.0.0
  • Read Timeout: 2m

Device Configuration (sFlow):

# Cisco switch sFlow configuration
sflow destination 10.0.0.100 6343
sflow sampling-rate 1024
sflow counter-interval 20

Troubleshooting

No data received: Verify Edge Delta listening on port with netstat -uln | grep 3421. Test connectivity with echo "test" | nc -u edge-delta-host 3421. Check firewall rules allow inbound UDP traffic. Verify sender configured with correct destination IP and port. Remember UDP is connectionless; no connection establishment.

Packet loss or missing data: UDP doesn’t guarantee delivery. Check network congestion between sender and Edge Delta. Monitor packet loss with netstat -su (UDP statistics). Increase Edge Delta agent resources if CPU/memory saturated. Reduce send rate from applications. Deploy multiple Edge Delta agents and distribute load across them.

High latency in data processing: Monitor Edge Delta CPU and memory usage for resource bottlenecks. Check datagram size; very large packets may cause processing delays. Review pipeline processors for performance issues. Increase agent resources or deploy additional agents.

Datagrams truncated: UDP datagram size limited to 65KB maximum. Check sender not exceeding size limits. Monitor for fragmentation issues. Use TCP connector instead for large messages. Split large payloads into multiple datagrams on sender side.

Rate limiting dropping data: Adjust rate limit configuration based on actual traffic volume. Monitor dropped packet counts in Edge Delta metrics. Increase rate limit threshold if legitimate traffic being dropped. Deploy multiple agents to distribute load.

Format detection issues: Verify data sent in recognizable format (JSON, plain text, StatsD). Check for encoding issues or malformed data. Review Edge Delta logs for parsing errors. Test with known good data format. Ensure newline delimiters for multi-line messages.

Port binding errors: Check no other process using the port with netstat -uln | grep 3421. For ports below 1024, verify Edge Delta running with sufficient privileges. Try higher port numbers (1024+) for non-privileged operation. Ensure listen address valid and exists on system.

Next Steps

For additional help, visit AI Team Support.