Root Cause Analysis
using Deep Learning
In this tutorial we will use artificial neural network to solve one of the common problem that we call Root Cause Analysis. The use case to solve relates to root cause analysis of problems found in a data center.
We have a data center that runs a number of software services. Service failures happen sometimes, so the data center team have to quickly troubleshoot and identify the root cause. The team wants to create a model that can predict root causes reported by customers based on the telemetry generated and errors noticed. They already have a system monitoring tool that tracks CPU, memory, and application latency characteristics of their servers. In addition, they also track errors reported by their applications.
Can we use this information to predict root causes of the issues noticed?
Problem statement
Using features about CPU loads, memory load, network delays, and three types of errors observed, we want to build a deep learning model to predict the root cause of the error.
The available data set has available has one record for each incident to indicate if any of the load issues or errors were noticed when the problem happened.
