With the incessant growth of data, network telemetry is becoming instrumental.
The world today is entirely taken by a crisis induced by the COVID-19 outbreak. It has impacted every walk of life and disrupted economic activities globally. In this way, the use of connected devices, particularly the internet of things (IoT) devices, is gaining momentum. From enabling contactless attendance to sanitization conformity and measuring body temperature, millions of IoT devices are being used at an unprecedented rate.
As the pandemic is continuously growing without any vaccine, the use of connected and IoT devices will continue to grow as they can be used to track corona-affected people, pre-screening or diagnosis, cleaning and disinfecting, and for other use cases. However, these devices produce a massive amount of data that needs to be processed, but various data streams and logs, and lack of consistency across devices make it very challenging to understand the data. This is where network telemetry can play an effective role. It defines how information from various data sources are gleaned and uses a set of automated communication processes for analysis tasks.
With the relentless growth of data, network telemetry is significantly becoming a vital technique for data analysis. It accumulates data from various sources, extracts information collectively and processes it for analysis.
Defining the Network Telemetry Architecture
Network telemetry architecture typically describes how distinct types of Network Telemetry data are transmitted from various network sources and received by different collection entities. An ideal network telemetry architecture enables the ability to amass data independently of any specific application and vendor limitations. The Network Telemetry architecture generally involves:
Data Source: This can be any type of network device that generates data.
Data Collector: It may be a part of a control or management system and a dedicated set of entities, collecting data from various data sources and acting processing tasks to feed both raw and processed data to the Data Analyzer.
Data Analyzer: It merely processes data from different data collectors to deliver meaningful insights, from creating simple statistical metrics to inferring problems and recommending solutions.
Network Telemetry Becoming the New Normal
In today’s dynamic networking ecosystem where data center networks have evolved in both scale and complexity, traditional network monitoring techniques like SNMP, which is based on fetching state from individual network elements through the control plane, are very restrictive and slow. In the same way, Netflow and synthetic probes are not perfect enough to spot issues caused by short-lived events or microbursts which can impact services and applications.
In the time of the COVID-19 crisis, where organizations have shifted to the work from home business model and are using local internet connectivity, security, reliability and ease of deployment are creating a new set of challenges for networking teams. This is enabling them to respond to the end-to-end network state across virtual and physical networks.
With network telemetry, organizations can gain real-time insight into the status of their devices that can help them perform more precise and faster root cause analysis to detect problem areas.