AIOps

What is AIOps?

On the one hand, AIOps stands for Artificial Intelligence for IT Operations. - Artificial intelligence for IT operations". This is a subcategory of the Artificial intelligencewhich was created by the US research and consulting company Gartner in 2016.

On the other hand, the Acronym supplemented by the meaning "Algorithmic IT Operation" - which means the use of Machine learning for analysis purposes.

The need for this particular field is explained by the modern IT landscape. Static and predictable systems must give way to software environments that change and reconfigure during operation. In addition, data will in future be less often stored in data centres or Clouds generated, but by billions of networked IoT-devices. Against this background, the installation of AIOps within companies with a broad digital infrastructure is inevitable in order to remain competitive.

How is AIOps different from DevOps?

DevOps describes the working culture that is necessary to develop software systems efficiently and effectively. This includes methods such as automated development processes, agile teamwork or decoupled processes that communicate with each other via programming interfaces.

AIOps also refers to the culture as a prerequisite for the targeted development of software. Topics such as Scrum, development pipelines or automation (they are otherwise associated with DevOps) also play a major role here. However, the Focus on the use of Big Data and machine learning - i.e. working with artificial intelligence - in order to, among other things, achieve the following Analyse and optimise IT operational processes:

  • In event correlation, so-called events are monitored. These are logins and events that are carried out during a computer session. The aim is to identify operational errors and uncover causes.
  • Anomaly detection is used as a further measure of danger prevention within the framework of AIOps. While event correlation concentrates on the detection of already known dangers, anomaly detection detects a communication pattern that deviates from the usual behaviour of the system. Cyberattacks, for example, can be unmasked with this.
  • As the name suggests, causality identification strives to show and explain connections. Depending on the technical approach, this idea is implemented individually by the well-known AIOps platforms.

What platforms and tools are there?

AIOps platforms:

  • The computer programme IBM Watson Understands natural language and Responds to questions. With the Cloud Pak platform, it also has an efficient AIOps solution to collect data from various sources and centralise the information derived from it in one point - a solid and proven way to automate an IT operation.
  • The provider Splunk originally focused on logging, monitoring and reporting with the platform of the same name.. With the additional AIOps division, customers are supported in centralising and simplifying analysis.
  • Also the provider Aruba combines Big Data and machine learning to automate IT operations processes.

AIOps tools:

  • The Market research company Gartner predicted the direction in which the IT sector was heading early on. From this, one can deduce the expertise they have in this area. Based on research findings, Gartner helps clients make informed decisions and develops tools for a wide range of business areas and market analyses. One tool in particular is relevant for the AIOps sector: the Gartner Hype Cycle.

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