Traditional application performance management no longer sufficient

Understanding how applications perform has been somewhat of a mystery for IT departments since the advent of networked applications.

The reason why it’s been so hard is that traditional management tools operate in a bottoms-up manner. That is, each infrastructure component is monitored, usually with its own management tool, and then the data is rolled up to some kind of manager of managers. Application performance management is inferred by trying to correlate the information manually. The problem is today there is far too much data to be analyzed using manual processes.

Nyansa takes a different approach. It provides a top-down view of the infrastructure, so application performance can be determined through the lens of the user instead of the infrastructure. Its Voyance product can be thought of as actual user performance management instead of traditional application performance management. Voyance uses machine language to interpret the massive amounts of data collected at the access edge, including wireless infrastructure.

With the explosion in mobile devices and cloud-based applications, Wi-Fi data can give an accurate view of what the users experience, given it’s the infrastructure component that is closest to the user.

Nyansa’s growth illustrates interest in user performance management

Recently Nyansa announced a few items that highlight their momentum and illustrate the demand for user performance management tools:

• Nyansa closed its series B funding round. Startups typically go through several rounds of funding to raise money for innovation, marketing, expansion or other use cases. The most recent round was for $15 million, led by Intel Capital with participation from Formation 8, one of the original investors. That brings the total funding for the company to $27 million. The additional money combined with the backing of a firm like Intel Captial should give customers confidence in doing business with a startup. Nyansa said it would use the additional money to drive more innovation into its flagship product, Voyance.
• New big-name customers. Nyansa announced wins with a number of big-name customers, including Mulesoft, the Atlanta Braves baseball club, International Red Cross, Uber, NVIDIA, Tesla and others. This gives the company several credible case studies to help prospects understand how the product works and to quantify the return on investment (ROI).
• Voyance integrated with ServiceNow and Slack. Nyansa is now integrated into the ServiceNow ticketing system, as well as the Slack collaboration tool. Integration into those products enables IT organizations to leverage the platform but continue to use the tools with which they are familiar. ServiceNow and Slack are great examples of how the IT management industry is changing, as they both seemingly came out of nowhere and are now widely deployed. They are the right types of technology partners for a next-generation platform like Voyance versus the many legacy management tools.
• Key milestones. Nothing legitimizes a startup like having the product used in large-scale environments. The company launched in April 2016, and in just under two years, Nyansa has achieved the following:
  • 200-plus production deployments
  • 3 million client devices under observation
  • 4 million client events analyzed weekly  

Voyance is a cloud-based solution so the more events and clients it analyzes, the more data it has to work with and the smarter it becomes.

Infrastructure management industry due for a change

I’ve long felt the infrastructure management industry was long overdue for a change.  For years, IT professionals have had to try and understand how applications are performing through manual correlation of data. This was sufficient about a decade ago when IT controlled everything from the network to application.

Today, the environment is completely different, and it’s impossible to understand user experience using old-school tools. Nyansa takes a user-centric view of the infrastructure and uses machine learning to quickly identify the source of application problems.