Nyansa brings a new approach to end-user management

Nyansa's Voyance+ provides significantly more accurate insight into real-time and historical behavior of applications

Nyansa brings a new approach to end-user management
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Legacy network and application management tools are significantly underpowered for today’s digital organizations. These old-school tools operate with a “bottoms-up” view of the IT environment, with each element having its own management tool.

Gathering insights from these discrete platforms is very difficult, as it requires a tremendous amount of manual data collection, aggregation and analytics. If Spock happened to be the lead engineer, this might be fine, but assuming no one in the IT department went to the Vulcan Science Academy, it’s likely that most organizations struggle with this model.

The big weakness of bottoms-up management is that it gives no real view of the end-user experience. It might be helpful in understanding if a certain element is down, but there’s no way to correlate that to the actual performance of an application, which is what the user is seeing.

Voyance+ provides complete picture of end-user application experience

Nyansa, a network management startup, has taken a different approach to enabling companies to get an accurate view of the actual user experience. It’s new product, Voyance+, an extension to its Voyance solution, adds user application analytics (UAA) to provide a complete picture of the end-user application experience by gathering client network transaction data across the wired and wireless network and then doing a bit of big data voodoo. UAA includes the in­frastructure that is monitored by legacy management tools but also components such as the client devices, cloud, WAN and Wi-Fi access points.

Voyance+ provides significantly more accurate insight into real-time and historical behavior of applications by measuring the end-user experience on every IT component that is used to deliver an application. The granular insights from Voyance+ enables businesses to understand how to optimize application performance and what the implications are for productivity. The product can also be used to study adoption trends and justify future investments.

Below are the steps that the Voyance+ solution utilizes:

1. Nyansa’s software inspection engine, “crawler,” inspects and analyzes all packets, correlating this data across multiple dimensions. An application ID engine within the crawler automatically characterizes SaaS, UC and custom applications. Voyance+ has a database of application signatures to discover well-known SaaS-based applications, unified communications as a service (UCaaS) providers and premises-based UC vendors. Businesses can also use the solution to define their own custom applications.

2. Traffic is analyzed and correlated on a per-user basis. Within its Voyance cloud engine, Nyansa uses machine-learning algorithms to understand the current environment without the IT staff having to manually interpret massive amounts of data.

3. Only metadata trends, baselines and analytics data are securely sent to the Voyance cloud engine. No packets are captured, and no user information or other sensitive data such as credentials are stored by the on-premises Voyance crawler.

4. Incidents, baselines, trends and analytics information can be viewed through a portal into the Voyance service. Support for user application analytics provides the following for every application:

  • Traffic, client and operating system usage
  • Automatic baselining of applications
  • All unique users who access the applications
  • Per-user or per-group incident identification to access root cause information, such as location data, device, RF band, operating systems, SSID and other relevant data
  • Rich dashboard view
  • Custom reporting

The Voyance+ service answers many of the who, how, where and what questions that have eluded IT for so long, including the following: 

Who

  • Which users are accessing specific applications over a selected period of time?

How

  • How is the quality of application experience for a given client device?
  • How many total “client hours” of poor user application experience did the company endure?
  • How does the user application experience vary with RF-band, SSID, location, device type, etc.?
  • How does my UC performance compare to UC in other similar environments?

Where

  • Where exactly is the problem located? Is it related to Wi-Fi, device/OS, infrastructure or the application itself?

What

  • What type of remediation can I apply to my network to alleviate user application issues?
  • What difference does upgrading my Wi-Fi network make in terms of application performance?

Businesses are using big data analytics and machine learning to understand customer behavior. Nyansa is taking this approach to help IT understand user and application behavior.

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