Networking - Network Telemetry and Streaming Telemetry

Introduction

Network telemetry is the process of collecting detailed information from network devices such as routers, switches, firewalls, and wireless controllers and sending that information to a central monitoring or analytics system. The collected information can include interface statistics, packet counts, bandwidth utilization, CPU and memory usage, errors, latency, routing information, and other operational data.

Traditional network monitoring often depends on periodically asking devices for information. Network telemetry provides a more efficient approach by allowing network devices to continuously generate and transmit operational data. This makes it possible for administrators to observe what is happening across a network in near real time.

Streaming telemetry is an advanced form of network telemetry in which data is continuously streamed from network devices to a monitoring or analytics platform. Instead of waiting for a monitoring system to repeatedly request information, the device can automatically send updates whenever new data becomes available or at predefined intervals.

How Network Telemetry Works

A typical telemetry system consists of three main components: the network device, the telemetry collector, and the analytics or visualization platform.

First, a network device collects operational information from its internal systems. For example, a router may record the number of packets transmitted through an interface, the amount of bandwidth being consumed, packet errors, CPU utilization, and memory usage.

The collected information is then formatted into a structured data model. Common technologies used for structured network data include YANG models and formats such as JSON, XML, or Protocol Buffers.

The information is transmitted to a telemetry collector. The collector receives data from multiple network devices and stores or forwards it to an analytics system.

Finally, the analytics platform processes the information and presents it through dashboards, graphs, alerts, or reports. Network administrators can use this information to identify performance problems, unusual traffic patterns, device failures, and other network conditions.

Traditional Monitoring vs Streaming Telemetry

Traditional monitoring commonly follows a pull-based approach. In this model, a monitoring server periodically asks a network device for specific information. Simple Network Management Protocol, or SNMP, is a well-known example of this approach.

For example, a monitoring system might ask a router every five minutes about its interface traffic. The router responds with the requested information.

Streaming telemetry generally follows a push-based approach. The network device continuously sends selected information to the telemetry collector without requiring the monitoring system to repeatedly request it.

This difference can become important in large networks. If thousands of devices are monitored at short intervals, repeatedly polling each device can generate significant overhead. Streaming telemetry can provide more frequent and detailed information while making data collection more efficient.

Types of Telemetry

Network telemetry can be implemented in different ways depending on the requirements of an organization.

Periodic Telemetry

In periodic telemetry, network devices send information at regular intervals. For example, a router could send interface statistics every 30 seconds.

This approach is useful when administrators need continuous information but do not require an update every time a particular value changes.

Event-Based Telemetry

Event-based telemetry sends information when a specific event occurs. For example, a device could report when an interface goes down, when a routing neighbor is lost, or when a particular threshold is exceeded.

This approach can reduce unnecessary data because information is transmitted when something important happens.

On-Change Telemetry

In on-change telemetry, information is transmitted when the value of a monitored parameter changes.

For example, if a routing configuration changes, the device can immediately send the updated information to the collector instead of waiting for the next scheduled polling interval.

Important Technologies

Several technologies are commonly associated with modern network telemetry.

YANG

YANG is a data modeling language used to describe the structure and characteristics of network configuration and operational data.

It provides a standardized way of representing information that network management systems can understand.

gNMI

gNMI, or gRPC Network Management Interface, is commonly used for configuration management and telemetry. It can allow a network device to stream operational data to a collector.

gRPC

gRPC is a high-performance communication framework that can be used as a transport mechanism for streaming telemetry. It supports efficient communication between network devices and applications.

NETCONF

NETCONF is a network management protocol commonly used for retrieving and modifying configuration information. When combined with YANG models, it provides a structured approach to network management.

Although NETCONF and telemetry can work within the same modern network-management ecosystem, they serve different purposes. NETCONF is primarily associated with configuration management, while streaming telemetry focuses on continuously delivering operational information.

What Information Can Telemetry Collect?

Telemetry can collect a wide range of network information.

Examples include:

  • Interface bandwidth utilization

  • Packets transmitted and received

  • Packet drops

  • Interface errors

  • CPU utilization

  • Memory utilization

  • Temperature and hardware health

  • Routing-table information

  • Routing protocol status

  • Network latency

  • Queue statistics

  • Optical signal information

  • Link status

  • Traffic flows

  • Application-related network metrics

The exact information available depends on the capabilities of the network device and the telemetry model being used.

Network Telemetry Architecture

A basic streaming telemetry architecture can be represented as:

Network Devices → Telemetry Collection → Data Processing → Storage → Analytics and Visualization

Network devices are responsible for generating the data.

Telemetry collectors receive information from multiple devices. In a large organization, collectors may be distributed across different locations to handle the volume of incoming data.

The processing layer can normalize, filter, aggregate, or enrich the information.

The storage system maintains historical telemetry data so that administrators can analyze network behavior over time.

The visualization and analytics layer provides dashboards, graphs, reports, and alerts.

Advantages of Network Telemetry

One of the major advantages of telemetry is improved visibility. Administrators can obtain detailed information about the current state of network infrastructure.

Another advantage is faster problem detection. Because streaming telemetry can provide frequent updates, administrators and automated systems can identify changes much sooner than with long polling intervals.

Telemetry can also support predictive analysis. Historical data can be analyzed to identify trends. For example, if bandwidth usage on a particular link increases consistently every month, administrators can identify the need for additional capacity before the link becomes congested.

It can also help with troubleshooting. Instead of examining individual devices manually, administrators can analyze centralized information from multiple devices to determine where a problem originated.

Network Telemetry and Automation

Telemetry becomes particularly powerful when combined with network automation.

For example, suppose telemetry detects that an interface has consistently exceeded a predefined utilization threshold. An automation system can analyze the information and potentially trigger a predefined response, such as adjusting traffic paths, generating an alert, or requesting additional capacity.

This creates a feedback cycle:

Monitor → Analyze → Decide → Act → Monitor Again

Such an approach is an important part of modern intent-based and software-driven network management.

Challenges of Network Telemetry

Despite its advantages, telemetry also introduces challenges.

The first challenge is data volume. Large networks can contain thousands of devices producing information every second. Collecting and storing all of this information requires appropriate infrastructure.

The second challenge is data management. Not every metric is equally useful. Organizations need to determine which information should be collected, how frequently it should be collected, and how long it should be retained.

Another challenge is compatibility. Different network vendors and device models may support different telemetry technologies and data models.

Security is also important. Telemetry data can contain detailed information about network infrastructure. Communication between network devices and collectors should therefore be appropriately protected.

Finally, telemetry systems require skilled administration. Organizations need people who understand networking, data collection, analytics, and automation to obtain maximum value from the collected information.

Example

Consider a company operating a data center with hundreds of switches.

Without streaming telemetry, a monitoring system might periodically poll each switch for interface utilization, packet errors, CPU usage, and memory usage.

With streaming telemetry, the switches can continuously send selected metrics to centralized collectors.

Suppose one switch suddenly experiences a large increase in packet drops. The telemetry system can receive this information quickly and display it on a monitoring dashboard. If an alert threshold is configured, the system can notify the network administrator.

The administrator can then examine related metrics, such as interface errors, bandwidth utilization, CPU usage, and neighboring-device status, to identify the cause.

Applications of Network Telemetry

Network telemetry is particularly useful in large and complex environments.

Common applications include:

  1. Network Performance Monitoring
    Administrators can monitor bandwidth, latency, packet loss, errors, and device performance.

  2. Fault Detection
    Telemetry can help identify failed interfaces, overloaded devices, and routing problems.

  3. Capacity Planning
    Historical telemetry data can reveal long-term traffic trends and help organizations plan future network expansion.

  4. Data Center Monitoring
    Large data centers can use telemetry to monitor thousands of network interfaces and devices.

  5. Network Automation
    Telemetry data can provide the information required for automated network-management decisions.

  6. Security Analysis
    Abnormal traffic patterns and unusual network behavior can be identified using telemetry data alongside security systems.

  7. Performance Optimization
    Network engineers can analyze telemetry information to optimize routing, bandwidth allocation, and resource utilization.

Conclusion

Network telemetry provides a modern method for obtaining detailed information about network infrastructure. Instead of relying entirely on periodic manual checks or polling, organizations can collect structured operational data continuously from network devices.

Streaming telemetry takes this approach further by allowing devices to stream information to centralized systems in near real time. When combined with analytics, visualization, and automation, it enables organizations to detect problems faster, understand network behavior more accurately, plan capacity, and operate large networks more efficiently.

For modern enterprise networks, cloud environments, and data centers, network telemetry is becoming an important foundation for real-time network visibility and automated network management.