Predictive analytics for IT operations management

The client is one of the world's largest data center & colocation provider offering the fastest application performance, lowest latency routes worldwide and a digital ecosystem for financial, content or rich-media, enterprise and cloud networks.

Business Challenge

  • The client had no visibility into problematic infrastructure components and hence was unable to get any insight from its current monitoring solution for infrastructure capacity planning. This was leading to a high number of incidents, negatively impacting business services availability. The client was also unable to forecast incident and event trends.

Technology Component

  • R System and Kaggle for building statistical modelling

  • Power BI for visualization layer

  • IT Operations data from various monitoring tools

Approach

  • Conducted workshops with business and IT stakeholders to understand the challenges

  • Collected the sample data from various monitoring tools

  • Performed data preparations and cleansing activities in PoC environment

  • Developed three statistical models (ARIMA, Negative Binomial, Zero Inflation) for predicting incidents

  • Establish correlation based on Pearson Correlation

  • Integrated Kaggle with Power BI for Dashboards and Reports

  • Demonstrated the solution approach to client senior leadership team

Transformational Effects

  • Ability to forecast incidents and report trends

  • Ability to forecast disk, network, memory usage metrics and proactively plan capacity

  • Visibility into event and incident occurrence patterns

  • Incident and event correlation

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