AIOps

Market Guide for AI for IT Operations (AIOps) Platforms

AIOps platforms combine big data and machine learning functionality to support IT operations. I&O leaders should begin the

Published By - knowledgeNile

AIOps platforms combine big data and machine learning functionality to support IT operations. I&O leaders should begin the deployment of such platforms to enhance performance monitoring now, but plan extension to service desk and automation over the next five years.

AIOps platforms are software systems that combine big data and AI or machine learning functionality to enhance. And they partially replace a broad range of IT operations processes and tasks. This includes availability and performance monitoring, event correlation and analysis, IT service management, and automation.
Their central function is:

  • Ingesting data from a variety of resources
  • Storing that acquired data
  • Providing access to the data
  • Enabling data analytics at two points:
    • The point of ingestion
    • The point following the access of stored data

Key Findings

  • Over the past three years, IT operations have deployed big data and machine learning technologies separately to support IT operations in monitoring. Over the last six months, however, enterprises have begun to combine their IT-operations-oriented big data and machine learning projects and extend them to service desk and automation.
  • Enterprises use artificial intelligence for IT operations (AIOps) platforms to enhance and, occasionally, replace classical application performance monitoring (APM) and network performance monitoring and diagnostics (NPMD) tools.
  • While IT-operations-oriented vendors have, historically, tended to specialize in either big data or machine learning. Over the last 18 months, trends in acquisition and development strategies dynamically changing. As a result, they are leading to the emergence of a generation of platforms that combine both.
  • AIOps skills scarcity is improving as, on the one hand, universities graduate students with data science skills in rapidly growing numbers and, on the other hand, vendors simplify interfaces for delivering AIOps functionality.

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