Juniper Networks on the importance of AI in networking

In March 2019, Juniper Networks announced the acquisition of Mist Systems, one of the pioneers of cloud-managed WiFi. Although there are other WiFi cloud providers in the mix, what sets Mist apart is that its solution is powered by artificial intelligence (AI), underscoring the importance of AI in networks.

At the time of the acquisition, Mist was used to improve the performance of Juniper’s WiFi solution. Since then, Mist AI-based management has been applied to the company’s campus network products and will soon be available for the SD-WAN and data center.

Mist is the foundation of Juniper’s corporate strategy

To better understand how Juniper will extend The use of Mist and the value it brings to customers, I recently interviewed Mist co-founder and CTO Bob Friday in a ZKast video interview, conducted in collaboration with eWEEK. I encourage anyone interested in the impact of AI on network operations to watch the video, but I’ve provided the highlights here:

  • Under the leadership of Rami Rahim, the CEO, Juniper has doubled its corporate budget. He expects the company’s operations to soon be larger than Juniper’s for service providers, although he has not provided any timetable for the switchover.
  • Mist was a key acquisition for Juniper’s business as it became the basis of its networking services. Since then, Juniper has made two other key acquisitions: 128 technology in the SD-WAN space and Apstra in the data center. The three companies combined can bring fully automated operations to all aspects of the commercial network.
  • Mist was designed from the start to take advantage of the elasticity and scalability of the cloud to simplify networking through the use of AI.
  • The cloud is basically a better way to maintain software. That’s why virtually every other area of computing has migrated to a cloud-based model. The network is the latest area to take advantage of the power of the cloud, and AI will drive this transition.
  • Mist’s goal is to have the troubleshooting capabilities of a high-level network engineer.
  • Although many vendors claim that their systems are BASED on AI, a number of them are actually rules-based products. The best way to identify real AI systems is to see if the product improves over time. AI platforms are constantly learning and should improve with more data.
  • Marvis, Mist’s virtual network assistant, has increased over time and is now at 70% efficiency (see graph at 8:20 of the video). At 90%, he will be tied with a championship-level network engineer.
  • Marvis/Mist is not designed to replace network engineers. The system should be seen as a tool that can help network professionals do their jobs more efficiently. ZK Research shows that about a quarter of network engineers spend about one day a week doing nothing but WiFi troubleshooting. Mist can eliminate much of these heavy loads and allow engineers to solve problems instead of diagnosing them.
  • Marvis provides a fundamentally different and more efficient way to run a network compared to the traditionally manually intensive control line interface.

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