Network monitoring has existed since the inception of the Internet. SNMP, a protocol that works by connecting to a device at periodic intervals to pull, or ‘fetch’ information, has long been the conventional method of gathering network data. Getting data from the command-line is a similar method that – like SNMP – becomes less efficient as a network’s size and complexity increase.
SNMP tends to draw heavily on CPU resources, causing usage to spike when network data is polled; which is usually at five- to thirty-minute intervals. Configuring SNMP polling, which includes the polling intervals, the devices to be polled, the information to be collected, and more – demands significant time and manual effort. The intermittent nature of the SNMP approach that is created by the polling intervals, means that the data it yields invariably paints an incomplete picture of the network being monitored.
The command-line approach, one the other hand, comes with its own set of pitfalls; Updates to vendors’ operating systems often include changed or deprecated command-line syntax, which could cause stored procedures for pulling device data to stop working. Thankfully, newer, smarter methods of polling network data are coming to the fore. Iris Network Systems is purposefully gearing their NMS tools towards a new approach; subscription-based data analytics.
Where methods like SNMP and CLI use the pull method to collect network data, the opposite is true of this approach. Using model-driven telemetry, the subscription-based approach empowers network operators by allowing them to tailor the data that is collected according to their needs – i.e. to model what data the NMS subscribes to. Not only is this approach less resource intensive, but it also provides the ability to get data from real-time sources.
In the context of network monitoring, ‘telemetry’ refers to an automated process whereby the devices within a network push information to the NMS, without the NMS needing to actively request (pull) it. Foregoing the overhead that manual polling requires, model-driven telemetry augments the automation power of telemetry with flexible modelling capabilities, to make for a modern approach that is faster than its predecessors and yields only meaningful, usable information.
With all of the devices in a network being able to stream data back to a central server or servers – cloud or embedded – Iris can leverage off only subscribing to data it wants to see from these devices. Using TLS technology to encrypt telemetry data means that it can safely be transported to our cloud for analysis. Network operators can rest easy in the knowledge that their confidential data is safe from prying eyes, even while off-network.
Iris Network Systems has always embraced new technologies. Adopting newer, more efficient methodologies like model-driven telemetry empowers us to continuously improve our systems and services.