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.
This reference outlines the advantages of adopting telemetry push models over traditional pull-based network monitoring approaches.
Telemetry push models provide real-time data that is useful in the following areas:
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Managing network remotely: Telemetry enables you to monitor the state of a network element from a remote location. After deployment, you can analyze, leverage, and act on network insights without being physically present at the site.
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Optimizing traffic: Monitoring link utilization and packet drops at frequent intervals makes it easier to add or remove links, redirect traffic, and modify policing. Technologies like fast reroute allow the network to switch to a new path and reroute faster than traditional SNMP poll intervals. Streaming telemetry data provides quick response times for faster traffic transport.
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Preventive troubleshooting: Network state indicators, statistics, and critical infrastructure information are exposed to the application layer to enhance operational performance and reduce troubleshooting time. The finer granularity and higher frequency of telemetry data enable better performance monitoring and troubleshooting.
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Visualizing data: Telemetry data serves as a data lake for analytics toolchains and applications to visualize valuable insights into network deployments.
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Monitoring and controlling distributed devices: The monitoring function is decoupled from storage and analysis, reducing device dependency and providing flexibility to transform data using pipelines. These pipelines consume telemetry data, transform it, and forward the content to downstream consumers such as Apache Kafka, Influxdata, Prometheus, and Grafana.
Streaming telemetry converts the monitoring process into a big data proposition, enabling rapid extraction and analysis of large data sets to improve decision-making.
| Benefit Area |
Description |
Key Features |
Downstream Consumers |
|---|---|---|---|
| Remote management |
Monitor network elements from remote locations and act on insights without physical presence. |
Real-time monitoring, remote access |
|
| Traffic optimization |
Monitor link utilization and packet drops to optimize traffic and reroute quickly. |
Fast reroute, frequent updates |
|
| Preventive troubleshooting |
Expose network state and statistics for enhanced performance and reduced troubleshooting time. |
High-frequency data, granular metrics |
|
| Data visualization |
Serve as a data lake for analytics and visualization tools. |
Analytics integration |
Grafana, Prometheus |
| Distributed device monitoring |
Decouple monitoring from storage and analysis, enabling flexible data transformation and distribution. |
Pipeline processing |
Apache Kafka, Influxdata |