What does AIOps mean to your IT team?

What does AIOps mean for your IT team
Published By - Kelsey Taylor

AIOps now known as the AI of IT Operations was first introduced to us as “Algorithmic IT Operations”.

Let us briefly it allin this article.

The AIOps platform, to its core, has two main elements to it:

  1. Machine Learning
  2. Big Data

The first to coin the term AIOps; Gartner, Inc., refers to it as the integration of IT and Artificial Intelligence in Operation Management.

Further, the AIOps platform utilizes modern machine learning, visualization, and advanced analytics technologies with Big Data. Hence, this all, to enhance IT Operations functions like monitoring, automation, and service desk.

In 2016, the trend of introducing artificial intelligence operating systems (AIOS) and Machine learning in everything possible led to the birth of AIOps in the first place to the Gartner Research analyst Colin Fletcher.

AIOps typically have these key functional layers:

  • Automation
  • Storage
  • Visualization
  • Machine Learning
  • Analytics offering Correlation
  • Prediction
  • Anomaly Detection

…working on data layer with Data sources, Monitoring, and IT service, and configuration management database (ITSM and CMDB).

Why does your IT team need to care about AIOps?

The software and applications are getting increasingly complex with the surfacing of every new solution.

Eventually, every enterprise needs to use multiple cloud providers and applications to affiliate to its various services necessary – the increasing variety and amount of data generation.

Moreover, human monitoring alerts tend to be slow and errorful. Without any supervision, machine learning algorithms analyze what alerts regarding Big data are real.

Further, the infrastructure and operations (I&O) leaders need to deploy such platforms to enhance performance monitoring. Here, market research done by Gartner explains how Artificial Intelligence in IT Operations:

  • Improves collaboration to integrate Data,
  • Monitor Stakeholders and provides more practical insights into it
  • Set Realistic Expectations for Data Accumulation Technologies

IT needs to act quickly with always increasing digital business and tech.

Moreover, the artificial intelligence operating system in IT is used to monitor IT infrastructure, application behavior, and digital experience.

Meanwhile, we are dealing with the costly adoption of various cloud-native or other ephemeral architectures.

Also, followed by the integration of monitoring tools, facing high volume, variety, and velocity of data.

 

Who and What’s next in AIOps?

Firstly, IT Leaders often need to keep an eagle eye on the AIOps platform. Following are some of the significant AIOps players include:

  • IBM
  • CA Technologies
  • HPE
  • MicroFocus
  • VMware
  • Moogsoft
  • HCL
  • BMC

Artificial Intelligence in the IT Operations concept still, is relatively new. But, it has impressive potential locked within.

Together with IT operations management (ITOM) and information technology service management (ITSM), it may result in better solutions to problems in:

  • Acquiring data and streaming various Data Types,
  • alerting,
  • aggregation, analysis, and action

Moreover, Gartner predicts that among large enterprises the adoption will go up to 40% by 2022 which is currently on a 5% level.

The Artificial Intelligence for IT Operations adoption came out considerably late but is showing some very promising growth now.


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