Wednesday 20 December 2017

Juniper Brings AI Bots To Intent-Based Networks


The concept of intention-based networks has received a lot of attention from media and network professionals since Cisco launched its "Network Intuitive" earlier this year.

Certainly, Cisco has turned the term "intention-based" into a familiar term, but that was not the first time I heard a provider talk about this vision. Years ago, I was at an event held by Juniper Networks, where its founder and CTO at that time, Pradeep Sindhu, spoke about the death of Moore's Law and how that would lead us to what we call intention-based networks.

Since then, Juniper has been somewhat silent about its role in the evolution of the market, although it has been quite aggressive in the area of ​​software defined networks (SDN) through the evolution of its Contrail platform. Last week at its NXTWORK 2017 client event, Juniper linked its innovation with Contrail to the vision of a stand-alone network with the launch of Juniper Bots designed to translate the intent into automated workflows.

It is fair to say that all the great advances that the industry has seen in the creation of networks in recent years, which include the change to software, a greater adoption of white boxes, new operating systems and the switch to software models, have allowed to do much more with our networks But they have also increased the complexity of running a network.

The change to the cloud has also increased the importance of the network, as we are now literally connecting everything to the network. Companies have had to hire more people with new skill sets just to maintain the status quo.

Automation is something that network professionals seem more open today than a few years ago, but what to automate and how it remains something of a mystery. At the event, Juniper provided a data point from his research that found that 43 percent of respondents said that lack of education and internal skills are preventing the use of network automation.

Juniper Bots help automate network tasks

The Juniper Bots were designed to address that lack of skills. The solution consists of Contrail Intent Bots and AppFormix Analytics Bots, which facilitate automation by making it easier for people to interact with your network. The details of the Juniper Bots are the following:

  •     Contrail PeerBot automates the network peering process. This makes it easier to manage multiple Border Gateway Protocol (BGP) domains, simplifies policy compliance and allows scaling on demand.
  •     Contrail TestBot allows network professionals to switch to a DevOps approach for the continuous integration / continuous deployment of network resources. Bots can be used to automate network auditing and provisioning modifications. Humans simply can not do these tasks fast enough to apply DevOps principles to the network.
  •     AppFormix HealthBot is like a Fitbit for the network. It uses machine learning to track the physical state and health of the network by taking advantage of AppFormix to collect real-time network data that can be used to discover new knowledge. The HealthBot translates the data into actionable information that can be used to solve problems and maintain the network.



Juniper Extension Toolkit Updates

In addition to the Bots, Juniper also announced several updates to its Juniper Extension Toolkit (JET). The enhancements extend the API framework of management and control to the data plane, allowing developers to create applications that interact directly with the data plane in the Juniper vMX and MX Series 3D Edge universal routers.

Juniper's plans for AI and machine learning

I had the opportunity to speak with Juniper's current CTO, Bikash Koley, who came from Google and has been in the CTO post since July when Sindhu resigned. I asked about Juniper's plans for artificial intelligence (AI) and machine learning. He said that most of the AI ​​that is in use today is what is known as broad AI, such as Amazon's Alexa. This can tell people the weather, what time a meeting is and who is playing a certain song. This requires a broad knowledge base, but does not require much depth.

However, those types of tools do not have the information or intelligence necessary to run a network. That requires a narrow AI where the data behind it is extremely deep, but the functionality of the tool, like a Bot, is well defined and narrowly focused. Koley said that over time we should expect Juniper to implement smaller artificial intelligence bots that solve the big problems that affect network operations today. In the long term, Juniper can venture to be a broad artificial intelligence provider, but the immediate focus is on simplifying network operations.

Another good point that Koley made was that doing something simple actually requires a huge amount of engineering and innovation. Juniper will apply its R & D efforts to mask the complexity of the network so that its customers can do more, faster.

It is likely that compliance with the vision of a stand-alone network will be years away, and providers should help their customers crawl, walk and then run in a fully automated environment. The Juniper Bots are a great starting point, since they allow engineers to take advantage of AI without putting the business at risk.