Introduces model-driven telemetry concepts, benefits, components, transport options, and session modes.
Scale up your network monitoring strategy using telemetry is a network feature that addresses the limitations of traditional polling methods by providing real-time, automated data streaming for improved visibility and control.
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Traditional polling methods such as SNMP, Syslog, and CLI may not provide sufficient data for effective network monitoring as network complexity and scale increase.
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These methods use a pull model, where the data collector requests information at regular intervals, which can result in information gaps, resource-intensive operations, and limited automation.
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Telemetry uses a push model to stream data automatically, supporting scale, speed, and automation for network monitoring.
Telemetry versus traditional polling models for network monitoring
Explains the differences between traditional polling methods and telemetry, focusing on scalability, automation, and real-time data collection for network monitoring.
Common questions and challenges in network monitoring include:
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What percentage of the network bandwidth does the network traffic currently consume?
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Do all the links in the network run at a hundred percent utilization rate?
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If an unmanned router fails, is the network operator notified in real time about the issue and its related consequences?
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Is the CPU over- or under-utilized?
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Can the efficiency of the network be calculated based on traffic and data loss?
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What are the possible performance issues that cause traffic loss or network latency?
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How do you proactively prevent issues that may arise? Does the data support the study of network patterns in real time?
Traditional polling methods require continual manual intervention and limit scalability and automation, inhibiting network visibility and control. As networks grow, a monitoring strategy that adds resiliency and stability is needed.
Telemetry uses a push model that automatically streams data from network devices in real time, eliminating the need for periodic requests from collectors. This model supports scale, speed, and automation, allowing selection of relevant data and transmission in a structured format to remote management stations.
Telemetry provides finer granularity and higher frequency of data, enabling DevOps engineers to quickly locate and investigate issues as they occur and collaborate for improved network control.
The following image compares the benefits of streaming telemetry data using the push model with traditional pull models. Pull models can create resource bottlenecks, while the push model removes these bottlenecks and delivers data efficiently.
Starting from Cisco IOS XR, Release 7.0.1, telemetry is part of the base image (<platform>-mini-x.iso). In earlier releases, telemetry was part of the Manageability package (<platform>-mgbl-3.0.0.0-<release>.x86_64.rpm).
This article describes the benefits of using telemetry data and the methods to stream meaningful data from your network device.
Benefits of shifting network monitoring from pull models to telemetry push model
Lists the benefits of using telemetry push models for network monitoring, including real-time data, remote management, traffic optimization, troubleshooting, data visualization, and distributed device monitoring.
Telemetry data streaming mechanisms
Explains how routers stream telemetry data using cadence-driven or event-driven mechanisms to support network monitoring and analysis.
Elements that enable streaming telemetry data
Lists the essential elements that enable telemetry in a network and outlines their roles in building a telemetry solution.
Telemetry session establishment methods
Lists the available methods for establishing a telemetry session, including dial-out and dial-in modes.