The Intelligent Next Step for Intent-Based Networking


June 10, 2019 - 3 Comments

We, and our customers, have long understood that networks are most valuable when they do more than support their own weight. They become assets only when they enable the growth of business strategies. To get networks to work at this level, we have to get a higher level of performance and agility from them.

That’s why we launched a series of products and services based on intent-based networking two years ago. Our goal was to reinvent access networking to serve business needs. Intent-based networking turns intent into network policy, and it lets businesses innovate faster than ever.

Since we started working on intent-based networking, we’ve been focused on making it simple. As the technicalities of networking are complex, this focus is not something we’ll ever be fully done with. Simplifying advanced IT requires continuous refinement.

One big leap we’re making now is using the power of artificial intelligence (AI). It lets us simplify the experience that IT teams have with networking tools, and provides personalized and targeted insights into their operational environments.

We are also simplifying what it takes to manage multiple networking domains – by linking them together to provide key outcomes that network managers care about, like end to end segmentation with application SLAs (service-level agreements).

Artificial Intelligence Powers the Next Level of Intent-Based Networking

We can use the artificial intelligence  to make IT more efficient and proactive. With AI, we can deliver a network that operates at its peak performance. At the same time, we make it easier to manage.

For example, we address the fact that the number of devices attaching to networks is increasing quickly. From end-user devices to IoT equipment, many networks are seeing exponential growth. This increase in network complexity is leading to an increase in alerts from management consoles. But IT teams, with their limited resources, are only able to pay attention to the highest-priority incidents. They end up ignoring the less urgent, but still important, indicators of network under-performance.

Having networks send their operators only the right alerts, though, isn’t something that can be done just by setting coarse threshold bands. Every network is different.  Every building in campus network is different. Each floor within a building is different. And these networks are constantly changing. We need to apply AI to optimize network management, to surface the alerts that are truly important for each unique environment.  With AI, we can customize alerts for every building, every floor and every room – with actionable insights that allow teams to quickly and proactively mitigate problems.

In early field trials of Cisco AI Network Analytics, we have seen the number of flagged incidents reduced by up to 75%. One of our customers, with a three-person network management team, tells us they call Cisco AI technology the “fourth member of the team.”

Having an AI tool to prioritize — and increasingly, remediate — network alerts means IT staff can spend more of their time and resources on strategic projects that make their business better, more efficient, and more competitive.

AI Network Analytics Reduces Noise for Greater IT Efficiency

AI can effectively filter and prioritize alerts.

The quality of the AI-driven improvement depends, of course, on the quality of the data. The more devices you collect data from – end user smartphones, switches, WAN routers, cloud servers, and everything connecting them – the better. That’s why we build telemetry into all the products we make. And we have 35 years of experience across all the domains of networking – experience that goes beyond raw data. We are combining that pattern-matching human knowledge of how networks work, with real-time telemetry, to move into a new field of AI, machine reasoning, to create even more intelligent network management.

Network teams can also use the network telemetry as a raw business resource. Networks are sensors, not just wires. A network can know how employees and customers use resources – increasingly, physical resources like buildings and equipment – and that data can be an invaluable resource in creating competitive advantage.

Integrating Network Policies

It’s also time to start unifying network management across domains. No network is an island, and yet they have been traditionally managed as if they were. Even inside a single enterprise, there are multiple networking domains, each supporting a unique role — from the campus and IoT networks that identify and onboard devices and authorize access, to the WAN network responsible for securely connecting to a hybrid cloud environment with a great application experience, to the data center and cloud networks where workloads are distributed and where protecting against data breaches is utterly critical.

Operating policies that govern network actions are defined in each of the domains. But the needs of a business are not fulfilled by one domain alone. All need to work together so that, for example, a doctor in a clinic can securely run a diagnostic application in the data center with adequate quality of experience over the WAN that connects them to it – a task that touches at least three traditionally separately-controlled networks.

To meet this business intent, domains must exchange relevant policies, so that the entire network works in concert.

In our example, the access network that onboards and authorizes the doctor must let the data center network know of their privileges to run the medical diagnostic application. Similarly, the data center network must tell the WAN of the critical nature of the application and how its traffic must be prioritized. When the doctor moves to a different clinic, the policies that govern their usage should follow.

Applying policies across domains can also be simplified.

Without such integrations, IT teams for each domain need to coordinate and then manually implement different policies. With the rapid pace of change, that may not even be possible.

Multidomain integration means that policy applied in one place (like the access network) will get applied to the other networks (like SD-WAN and data center) that are involved in delivering the desired result. Each domain continues to support its primary role, but as changes occur, it will dynamically update across other domains.

Improving the Human Element

AI tools and automation for multiple domains will get us closer to the IBN vision and will dramatically free up IT teams so skilled network operators can work on strategic projects – projects that may appear out of reach today due to the fire-fighting nature of network management. Based on talks I have with customers, I know that there is no end to the number of interesting and lucrative projects our users could be working on. And we want to help.

We recognize that network engineers and IT teams will need new skills and practices to take advantage of these tools. Our own Cisco DevNet can help lead the way: Resources are available now to help build network automation across domains with the new DevNet Automation Exchange. New DevNet certifications will help engineers build critical software skills and infrastructure expertise to keep on top of the latest IT developments.

Smart software will soon be able to do more for our networks than ever. But to keep a business ahead of the game, IT teams need to know how to use it to its best advantage. There’s so much still to do when it comes to leveraging the power of interconnected systems. We want to help networks get smarter, and we want to be sure they all have the best-informed people available to manage them.

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3 Comments

  1. Excellent insight to the continued evolution of our Intent Based Networking solution!

  2. Amazing solution meant to improve the modern business environment.

  3. You said, " We recognize that network engineers and IT teams will need new skills and practices to take advantage of these tools."

    Based on market research findings, CIOs report that IT 'talent development' is more challenging than network management tools deployment. Finding people with the skills and experience to fill the apparent void where AI can't deliver meaningful results (on its own) is the key to progress.