According to Gartner, the data volumes generated by IT infrastructure are increasing two-to-three-fold every year. Owing to the rapid digitization of organizations in recent times, it has become more difficult than ever for ITOps teams to analyze data, predict issues before they occur and locate anomalies quickly.

In a nutshell, there is too much data noise.

AIOps solutions combine big data and machine learning and help IT leaders to automate key ITOps processes like event correlation, anomaly detection, causality determination and more.

In this guide, we’ll explore:

  1. Understanding AIOps and its evolution
  2. Key elements of AIOps
  3. AIOps: use cases and benefits
  4. AIOps tools
  5. How to get started with AIOps
  6. The Future of AIOps
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