Stop Reacting to Issues. Start Preventing Them.
In today's connected world, delivering superior digital experiences is critical for every business. And cloud and Internet networks play a core role in this connected ecosystem. However, relying on these external environments can create blind spots that impact the digital experience of customers and employees alike. It also results in a reactive-based networking model, where user experience is always at risk.
ThousandEyes WAN Insights enables enterprises to move from reactive to preventative by continuously analyzing performance data and applying statistical models to forecast conditions and recommend actions. With WAN Insights, network operations and IT teams can proactively avoid experience degradation or outages, confidently delivering the best possible user experience in the hybrid work era.
Experience WAN Insights in Action
Using ThousandEyes WAN Insights, Cisco SD-WAN customers can take a proactive approach to improving application experiences for their users. By leveraging historical network performance data from SD-WAN telemetry, ThousandEyes WAN Insights uses statistical models to forecast conditions allowing network teams to proactively optimize their IT infrastructure in order to improve users’ quality of experience on their Cisco SD-WAN. Improving long-term end-user experience for critical business applications, such as Microsoft 365 and collaborative services like voice and Webex by Cisco.
Forecast Network Conditions Impacting Sites
ThousandEyes WAN Insights applies statistical models to Cisco SD-WAN telemetry to produce routing recommendations that forecast potential performance gains for application groups. It follows the SD-WAN configuration for sites, edge routers, and interfaces across IT infrastructure—continuously measuring and assessing the quality at a path level.
Implement SD-WAN Policy Optimizations, Proactively
ThousandEyes WAN Insights uses constant real-time analysis of the underlay and overlay network data to guide the preferred policy recommendations to avoid application experience issues for an application at a given site. These long-term recommendations are specific to each site and application category, and quality estimates reflect the forecasted quality improvement on the recommended path compared to the current path.
“WAN Insights opened many different avenues for visibility into our traffic to different applications within our environment, like Microsoft 365, Webex, and voice. We could really see and execute on some of the recommendations being made.”
Improve Workforce Experience and IT Operations Efficiency
ThousandEyes WAN Insights empowers network operations and IT teams to seamlessly make policy optimizations through Cisco vManage. WAN Insights organizes data around long-term recommendations based on network quality of service (QoS) levels for loss, latency, and jitter. These quality of service estimates are defined separately for each application class. Network teams can quickly review network issues at problematic sites in order to take proactive measures. With less time spent troubleshooting, IT operations can spend more time advancing strategic business priorities.
Boost Application Experience and Network Performance Like Insight Global
Learn how Insight Global, a national staffing and services company dedicated to empowering people, is able to deliver exceptional application experience and a resilient enterprise network using WAN Insights. Watch as Michael Kutka, Network Architect at Insight Global, shares their story.
Award-winning Innovation. Exceptional Experiences.
ThousandEyes WAN Insights received the 2023 Cloud Computing Product of the Year Award by TMC's Cloud Computing Magazine for its standout innovation.
Learn About Predictive Networks
A predictive network is a network that leverages a predictive analytics process using historical data to forecast future behavior to determine the probability of an issue occurring or reoccurring on that network. Then, the forecast is capable of generating recommendations that, if applied manually or through automation, reduce the probability of the issue ever happening and, therefore, reduce the impact on the user's digital experience.
Predictive analytics is the application of algorithms applied to a model in an effort to identify the potential of future outcomes based on historical data.
Creating a predictive analytics model involves running different algorithms to identify recurring patterns in sizeable transactional data sets.
While machine learning is not technically a form of predictive analytics, it can be leveraged to enhance a predictive analytics model's ability to detect patterns, forecast outcomes, and recommend actions over time.
Predictive analytics is forward-looking data analysis that identifies the likelihood of future outcomes based on historical data. Diagnostic analytics is reactive and designed to determine changes that occur in a specified period and is typically used retrospectively to understand why an event or trend occurred.
Enterprises are increasingly adopting cloud-based services, such as SaaS applications, which in turn increases reliance on the Internet to deliver WAN traffic. The use of traditional multi-protocol label switching (MPLS) services makes sub-optimal use of costly backhaul WAN bandwidth, given that many critical applications and services are no longer internal in data centers. As a result, enterprises are migrating to hybrid WAN architectures and SD-WAN technology that combines direct Internet access (DIA), IP VPN tunnels, and traditional MPLS circuits.
Over the last several years, a robust market of SD-WAN vendors and managed SD-WAN providers has arisen to meet this need. SD-WAN has been architected to provide a certain amount of resilience, leveraging automated actions. A number of these automated functions are able to track network and path characteristics of the data plane tunnels between SD-WAN devices and use the collected information to compute optimal paths for data traffic, automatically redirecting data traffic to the best available path in the event of an issue occurring. This function, while automatic, remains reactive, only able to initiate the change when conditions deteriorate to the point at which the user's performance is impacted.
Predictive analytics builds on this reactive functionality by taking those characteristics, including packet loss, latency, and jitter, and applying a broad range of statistical time-series methods to predict probabilities of traffic disruption for different applications and use these forecasts to provide recommended path selections to the network, in order to avoid the probable issue occurring and impacting user performance.
The goal of the ITOps team for any existing and new site within an SD-WAN network is to provide the best application performance while keeping the circuit cost low. However, the volume of data points across thousands of sites, networks, paths, applications, and users is impossible to assess manually and analyze. As a result, most organizations have a reactive approach to delivering user experience, only focusing on issues as they occur, and are unable to move away from a firefighting mode of operations.
A reduction in the number of incidents and, subsequently, the number of times ITOps has to react to an issue allows them to move beyond a complaint-driven, fire-fighting engagement to a data-driven decision-making process. This facilitates a proactive engagement model that allows network conditions that may otherwise have gone unnoticed to be addressed before they reach a noticeable user-impacting level.
This becomes applicable throughout multiple levels of ITOps, enabling cross-skilling throughout the organization, providing less experienced engineers with enough information to make informed decisions, and ultimately freeing up time for more experienced engineers that can be utilized for strategic actions.
By continuously observing the behavior of selected applications across every network path over a rolling period, a predictive analytic system is able to analyze historical performance across all SD-WAN network sites and identify quality issues for each application category (for example, Office 365 or Voice).
When the system identifies that a quality issue could be avoided by a change to the current network configuration, it generates a recommendation, typically an alternate path to route that site’s outgoing traffic, for a given application category.
Five Emerging WAN Trends That Will Shape NetOps's Strategy
The future of enterprise networking is filled with Internet-dependent services and applications operating in complex, multi-component environments. Learn more about these WAN trends in our latest eBook, and see how you can unlock their full potential for the modern workplace.
Cisco SD-WAN customers can now optimize SD-WAN policies proactively for seamless application experiences, confidently delivering the best possible user experience in the hybrid work era. Learn more about WAN Insights in this product overview.
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Stop reacting to issues and start preventing them.