This vendor-written piece has been edited to eliminate product promotion, but readers should note it will likely favour the submitter's approach.
Understanding how end-users access and experience network applications requires a new approach. Ten years ago, enterprises could count on Ethernet-connected, Intel-based Windows devices accessing on-premise applications. This made it possible to improve end-user experience within established use cases. But that scenario is the exception today rather than the norm.
Most applications today are supported by a dynamic infrastructure distributed across on-premise and the public cloud. And client devices are copiously diverse in terms of hardware, operating systems, drivers, and more. To add to the overall complexity, these devices are accessing networks via Wi-Fi over dynamic RF environments and potentially unreliable Internet connections.
What insight can traditional application performance monitoring (APM) and related technology provide in this new landscape? APM tools answer the question of how long a client transaction takes to get satisfied once it hits the web server. This takes into account the transaction times between the web server, app servers, database servers, etc. APM homes in on the inner workings of a multi-tier application within the data center. Even a brief consideration of contemporary applications, however, reveals that this portion now constitutes just a tiny segment of the overall user application experience.
First, IT is increasingly working with business critical applications beyond its control. When third-party applications are in use, IT cannot instrument a third party’s data center and the use of APM technology becomes moot. Second, using APM presupposes that clients are able to efficiently connect to the access network and subsequently reach the application webserver. When this connection fails, APM tools are not equipped to collect or analyze data from the wireless LAN infrastructure, the campus network services, nor the health of the WAN/Internet link.
Limited by its scope, APM is simply not the right tool to address the complexity of issues users are facing before their transactions even hit the application webserver.
To gain maximum visibility into the user application experience, network operations staff need insight into the client device’s ability to associate in a timely manner to a wireless access point, authenticate via RADIUS, obtain an IP address via DHCP, resolve domain names via DNS and finally transmit/receive data from the internet. If any of these steps fail, it would be pointless to consider the “application performance” since users have failed to even access the application. Maintaining complete awareness of all of these user network transactions is daunting for network managers who must sift through volumes of network, application and user data from a variety of domain silos.
Evolving interdependences between networks, devices and applications are driving the need for a more holistic approach to IT analytics. Performance metrics about the application, wireless/RF, network services, Internet link, as well as device type and operating system information must be collected simultaneously across the stack. Next, these metrics need to be analyzed and correlated across time and other dimensions (e.g. locations, SSIDs, VLANs, etc.). Finally, advanced machine learning algorithms need to be applied on top of these metrics in order to surface insights and remediation advice proactively.
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