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Demystifying network analytics

Demystifying network analyticsNetwork analytics is key to helping IT proactively deliver great user experiences, but analytics for the enterprise access network is complicated.

Besides the array of connectivity options, the heterogeneous mix of client devices and the different application models to accommodate, there are volumes of relevant input data that can be used, such as:


    Actual data packets generated by real clients

    Synthetic data packets generated by simulated clients

    Real-time metrics and traps from infrastructure

    Logs/configuration from infrastructure and servers

    Flow data from infrastructure

    APIs from application servers

Real analytics tools should be able to analyze this network data and compare it to or correlate it with other data from the network to reveal or pinpoint a specific problem or trend that can be actively addressed. After all, for analytics to be useful, the tools must show what action to take to fix a problem or enhance an experience.

The vast majority of today's IT monitoring solutions don’t do this. These solutions tend to be siloed, revealing only one aspect of the user experience like wireless connectivity, DHCP response times or application performance.  What you’re left with is lots of graphs of raw data that you must study and correlate with other things going on in the network to get any kind of actionable answer.

Some new systems go a few steps further and interpret the data and visualize it to generate topology maps, heatmaps and scatterplots, but still fall short of the real role and value of analytics.

Another class of solutions are simply log processing/indexing engines that enable you to efficiently query log data from network elements and look for specific keywords. You can take this data and visualize it as well, but you’re still responsible for the correlation and analysis to come to some useful conclusion

The ideal network analytics tool should be able to answer complex questions, automatically surface insights and recommend actions, and provide a feedback mechanism.  Let’s dig deeper on these critical capabilities:

Analytics needs to answer complex questions

Most user experience issues involve complex questions that cut across different dimensions or parts of the infrastructure.  For example, if users on the 9th floor of building 5 are having poor Skype for Business performance, is it because of the wireless, or is it because of the application?  Or, if users simply can’t connect to the network, is it an issue with RADIUS? DHCP? ARP? DNS? 

Modern analytics must be able to answer these types of questions to help you resolve incidents more quickly and before users even see them.  To answer these questions, true network analytics needs to start with the relevant time-series data from disparate data sources. Next, the solution needs to correlate that data in real time. 



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