Cisco to Scoop Up Perspica, Gain More App Smarts
This acquisition adds real-time streaming view to application intelligence Cisco gained with AppDynamics buy.
October 20, 2017
![Smart Apps Smart Apps](https://eu-images.contentstack.com/v3/assets/bltde8121fc52c5c8f3/blt8cfe6686a8b28d2c/6653f888159aa1b0af48e22d/app-68002_640.jpg?width=1280&auto=webp&quality=95&format=jpg&disable=upscale)
Cisco this week announced its intent to acquire Perspica, a machine learning vendor -- the second of this sort of acquisition this year (not to mention its 200th overall).
Earlier this year Cisco dropped a hefty $3.7 billion to purchase AppDynamics, paying a significant premium over the application performance vendor's pending IPO price. AppD, as it's better known as, gave Cisco a view of user experience through the lens of applications. Prior to the acquisition, Cisco had to infer how apps were performing through data generated by its security, networking, and data center products. AppD gave Cisco badly needed application intelligence, arguably enabling it to deliver the first true end-to-end monitoring and analytics platform.
Modeled for scale and speed
To provide enterprises a view of how applications are performing, AppD analyzes and applies machine learning to the data it collects from users, applications, databases, servers, and, soon, networks and Internet of Things endpoints. It aggregates collected data and works on data at rest. That's not to say that AppD doesn't provide a real-time view, because it certainly does. However, it does need to combine and sort the data.
Conversely, Perspica uses machine learning to analyze real-time streaming data, or data in motion. This could be the telemetry generated from many of Cisco's newer network products, its ACI controller, or Tetration analytics system, as well as any competitive products that stream data. Perspica can process enormous volumes of data on the fly. Together with AppD's product, the Perspica machine learning tools will enable Cisco to measure business transactions at greater scale and speed than it is able to do now.
This article first appeared on NoJitter.
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