AIOps Drives Exceptional Digital Experience Through Network Assurance

Part 5 of the six-part series – The 2023 Global Networking Trends Report series 

The distributed workforce―and the distributed applications and services they consume―have vastly changed the enterprise network paradigm. Many connections—such as private cloud, internet, public cloud, multicloud, and software-as-a-service (SaaS) networks—now begin and end outside of the traditional corporate infrastructure. The coexistence of these complex connections creates new layers of operational complexity for teams responsible for ensuring predictable performance and quality of service.

What is needed to combat this complexity is a network assurance platform that includes true end-to-end visibility capabilities. Insight is needed into users and their devices, locations, and connected things, as well as into access networks, network services, multiple clouds, and corporate enterprise data centers and applications (Figure 1). A solution that combines these different data sets and uses artificial intelligence and machine learning (AI/ML) to analyze the data, can help drive decisions that make network operations proactive and predictive, instead of reactive.

Span of end-to-end visibility required
Figure 1. Span of end-to-end visibility required (click to enlarge)

In our 2023 Global Networking Trends Report, nearly half (47%) of respondents said they are prioritizing the adoption of predictive network analytics over the next two years, primarily to help with managing the connectivity and digital experience of their remote workforce.

A predictive network analytics solution requires the ability to correlate massive amounts of network data in real time and at tremendous scale. By continuously analyzing performance data and applying predictive modeling to forecast conditions and recommend actions, predictive capabilities can become a reality. Predictive analytics empowers teams to avoid adverse application impacts to distributed workers and to ensure the best possible user experience.

Predictive analytics for SD-WAN and an internet-centric world

For the software-defined WAN (SD-WAN), a platform that uses artificial intelligence for IT operations (AIOps) can provide predictive analytics to forecast performance (Figure 2). AIOps refers to the strategic use of AI, ML, and machine reasoning (MR) technologies to simplify and streamline IT processes and optimize the use of IT resources. By correlating and analyzing real-time and historical SD-WAN performance data and applying predictive models, AIOps can use these forecasts to deliver per-site recommendations for optimal path selection by application type to deliver an optimal experience based on available paths.

By integrating predictive analytics into SD-WAN solutions, IT teams can improve dynamic enforcement of application service levels with intelligent routing across alternative paths before any degradation occurs.

Predictive analytics through a continual feedback loop

Figure 2. Predictive analytics through a continual feedback loop (click to enlarge)

Combining traffic data sets from an organization’s ecosystem of ISPs, cloud providers, SaaS applications, and other external services, further enriches predictive analytical systems. Operations teams can rapidly identify, escalate, and remediate issues with providers using internet telemetry data. When outage behavior is detected, a root cause can be identified and shared with providers to prioritize fixes or escalate to peers and transit providers.

Predictive analytics at work in the real world 

When Insight Global—one of the largest staffing agencies in the United States—allowed its employees to return to the office, they leveraged information from ThousandEyes’ WAN Insights to optimize its SD-WAN policies and improve application experiences proactively and continuously. Once the solution was in place, they gained greater visibility into critical network environments and routing, and Insight Global’s IT team was better able to detect and avoid potential issues before those issues could impact the business.

Predictive and proactive operations is the way forward  

It’s time to move from reactive to proactive operations management through end-to-end visibility and AI/ML-powered predictive analytics. It’s time for a consistent way of automating operations, analyzing and diagnosing issues, and assuring the user experience across all the different networking domains.

We believe strongly in this way forward. It’s the cornerstone of Cisco’s approach to network assurance and Cisco’s Networking Cloud vision—a unified management experience platform for on-premises and cloud operating models to simplify IT, everywhere, at scale.

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