Under the hood of Cisco’s Tetration Analytics platform

#Cisco ’s entrance into the data center analytics market with the introduction of #Tetration is the culmination of two years worth of wrangling various open source projects and developing proprietary algorithms in the areas of big data, streaming analytics and machine learning. #Apache

Tetration is an analytics platform that provides deep visibility into data center and cloud infrastructure operational information. Here’s a description fromNetwork World’s story on Tetration:

The platform, Cisco Tetration Analytics gathers information from hardware and software sensors and analyzes the information using big data analytics and machine learning to offer IT managers a deeper understanding of their data center resources. The system will dramatically simplify operational reliability, application migrations to #SDN and the cloud as well as security monitoring.

But what’s under the hood of Tetration? Below are some of the components used to build the product (by the way, the word Tetration is a mathematical term used to indicate very large numbers):

Apache Spark

Apache Spark is an engine for large-scale data processing. To understand what Spark is, it’s helpful to understand the basics of Hadoop. Hadoop has two main components: the Hadoop Distributed File System (HDFS), which is the storage layer and MapReduce, which is the analytics and compute layer. Spark was developed as an alternative to MapReduce as an in-memory cluster processing platform that can deliver up to 100x faster response times compared to MapReduce for some applications. A key feature for Spark is that programs can load data into Spark’s cluster memory system and be queried repeatedly, making it an ideal platform for machine learning and artificial intelligence applications.

http://www.networkworld.com/article/3086250/cisco-subnet/under-the-hood-of-cisco-s-tetration-analytics-platform.html