How does Network Automation work?

Network automation works via a layer of software implemented across all networking devices such as routers, switches, and more. The network automation software leverages a set of application programming interfaces (APIs) to establish communication with hardware and network devices. Through the APIs, the network can then be configured as needed.

But artificial intelligence (AI) and machine learning (ML) techniques can take automation even further, essentially allowing an AI-enhanced automation engine to evaluate network and application performance then respond by making adjustments to the network configurations automatically.

Here’s how this AI-powered network optimization works.

Using AI and ML techniques, the network automation software evaluates historic patterns of bandwidth consumption and performance, then configuring all physical and virtual network assets using a set of known-good parameters.

Think of it this way: If a corporate network is a complex puzzle with 10,000 interlocking pieces, then networking automation is like a robot that can understand in an instant how every puzzle piece fits. It can then place the next piece accordingly—and do so at a speed and scale beyond what is humanly possible. Because the robot learns using past experience data, it will get better and faster at solving every future puzzle.

 

Why is Network Automation important?

Network automation is important because it solves business problems:

Productivity: Managing the network and application performance is difficult and time consuming for IT teams. Networks are rigid, complex, and fragmented systems prone to error. They are typically operated manually with a small team of people focused on identifying the root cause of service degradations while handling all fault management, configuration management, bandwidth allocation, and security. But this work is time consuming with the average network manager spending 20 hours a week troubleshooting the network.

Because the human brain is not good at quickly evaluating complexity using mountains of data, it’s often difficult for people to understand what’s happening inside the network. It can be even harder in multi-cloud environments where there are too many vendors, systems, dashboards, policies to evaluate. This is why network automation powered by AI is critically important today.

At a tactical level, network automation reduces the complexity of a corporate network which affects the amount of labor required to deploy everything from a new single user up to a whole office full of users. Network automation is important for IT departments because, at a strategic level, it helps them to maintain consistency of the corporate network’s configuration while also constantly optimizing its performance. An automated network uses AI to drastically reduce the time needed for a network manager to troubleshoot and resolve issues.

Network Costs: When these deployments leverage virtualized network hardware, the cloud, and converged devices (e.g. a single piece of hardware that serves as a router, firewall, and SD-WAN endpoint), network automation also reduces a company’s overall costs. Whether the network uses equipment that is physical, virtual, or a hybrid of both, the combination of AI, automation, and software at every network endpoint provides real-time analytics on the condition of the network. By performing constant “health checks” on the network at a global scale, network automation empowers IT managers with the business agility needed to run the network more efficiently.

 

What is required for an Automated Network?

The base level requirements for an automated network are :

  1. A software-powered network control plane and management system – Commonly used in software defined wide area networks (SD-WAN), this software “abstracts” the network signaling, configuration, and administration functions of a networking equipment (e.g. routers, switches, etc.). A software-defined and centralized control plane also enables the end-to-end network visibility required for network automation
  2. Built-in artificial intelligence and machine learning capabilities – An automated network uses AI/ML to analyze and configure network devices automatically to provide users the best experience
  3. Detailed network analytics – A crucial component to all automated networks, real-time network analytics are required for the AI/ML components to not only set up but also optimize the WAN/LAN

On a typical corporate WAN or LAN today, setting up routing tables for IP traffic is often a time-consuming and labor-intensive process managed by an experienced IT manager or network architect. However, an automated network can use real-time analytics data fed into the machine learning-engine to determine optimal network packet routes on a LAN or WAN faster than humanly possible. Artificial intelligence can then push out that optimal configuration to all network routers on a global scale via the network control plane software in minutes.

 

Is an Automated Network the same as a Self-Healing Network?

While they share some similarities, the fact is that an automated network and a self-healing network are two different things. The key difference being AI-powered insights versus the ability to act alone.

Generally speaking, a self-healing network is when a LAN or WAN is designed to resist failure using various transmission paths. But a fully automated network uses AI-powered intelligence to both understand what’s happening inside the network and also automatically make changes to the network in order to optimize the performance.

An automated network has an AI engine or AIOps tool that is connected to the controls, so it can make broad configuration changes all by itself–without any human interaction. Thus, a fully automated network has advanced through distinct stages of maturation, as shown here.

 

When will we see truly autonomous networks?

Industry analysts predict that enterprises could see fully-automated networks as soon as 2022. Much like a fully-automated vehicle that can pick up a human passenger and deliver them safely to a destination, a fully-automated network is difficult with current technology.

Does Masergy offer an Automated Network?

Yes! Masergy embedded a layer of real-time network analytics into its global network to feed a proprietary AI/ML engine with usage data. This real-world data powers Masergy AIOps, a virtual network engineer built into every customer deployment that helps to optimize network performance. With rapid advancements to AIOps made by Masergy engineers since 2019, the goal is for Masergy to offer autonomous networking for customers by 2022.

Masergy owns a global, software-defined private network that was built from the ground up and is currently in use by over 1,400 enterprises around the world. A software-defined networking pioneer with two decades of engineering experience, Masergy provides our customers with secure and scalable managed SD-WAN solutions. All Masergy networking solutions include our proprietary AIOps tool, which is built into our award-winning customer portal, empowering IT managers with real-time visibility and control over every aspect of their on-prem, cloud-based, and hybrid corporate network.

To learn more about the Masergy customer portal with AIOps, download the product sheet and watch this short demo video to see exactly how Masergy AIOps can help your overworked and understaffed IT teams manage and optimize your corporate WAN.