AIOps – Bringing AI into IT Operations

by Sherwin Jaleel
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Digital is disrupting the world of ITOA

Traditionally IT Operations and Analytics (ITOA) functions made sure the lights stayed on by providing stability to an organisation’s IT systems. However, the emerging forces of digital transformations are disrupting traditional ITOA functions and are driving it to a tipping point, demanding a course change for how IT operations are managed.

Why AIOps?

The staggering rate at which Digital adoption is advancing using emerging architectural patterns such as microservices is introducing far more moving parts into an application stack. Moreover, the elasticity of cloud-native applications and their containerization is resulting in dynamic operational environments. Traditional IT operations are struggling to keep up with such complex digital ecosystems which are driving the need for a paradigm shift in the world of IT Operations. AIOps is emerging as a means to address this paradigm shift and assist IT Operations functions enabling them to keep up with the accelerating pace of digital transformations.

Digital is driving the need for a paradigm shift in the world of IT Operations.

What is AIOps?

AIOps is a term coined by Gartner and stands for Artificial Intelligent Operations. There is nothing artificial about AIOps, though. At its core lies analytics and machine learning which AIOps brings into service management and performance management. Unlike traditional algorithmic and rule-based approaches to automating IT Operation tasks, AIOps harnesses Big Data, Analytics, Artificial Intelligence (AI) and Machine Learning (ML) to drive truly intelligent automation within the discipline of IT Operations. AIOps sits slap bang in the middle of the DevOps Practises of Continuous Feedback and Continuous Monitoring.

There is nothing artificial about the AI in AIOps.

What does AIOps do?

AIOps brings to the world of ITOA four core benefits:

  1. Reduce MTTR: Outages impact the bottom line of every business. IT operation teams are measured on MTTR, i.e. Mean Time to Resolution AIOps helps reduce MTTR.
  2.  Proactive, not Reactive Approach: AIOps technology, helps ITOA teams to recognize outage patterns and detect potential issues and take action before the issue manifests into a more significant problem. AIOps helps IT teams to shift from an operational paradigm of reactive to proactive.
  3.  Automated Remediation: AIOps can prescribe correction action and automate remediation by harnessing technologies such as ML, AI and Analytics. Metadata, metrics, logs and operational data generated by production systems are digested by AIOps solutions, and the insights obtained used to automatically map dependencies, build models to determine the root cause of an issue and also apply fixes automatically.
  4. Business Insights: Not only does AIOps enable preventive maintenance though the insights obtained from operational data this data from live IT ecosystems can also be harnessed to drive insights at a more strategic and business level.

How does AIOps do it?

AIOps consists of a multi-layered technology stack comprising of components from Analytics, ML and Automation. In the world of AIOps, data is king. IT operational data streams is central to the success of AIOps. Big Data and ML are critical components in the AIOps solution stack. Data streams from a production system such as events, logs, traces, tickets, incidents, system monitoring metrics are tapped into and fed into a Big Data engine. AIOps then combs the data using analytics and ML techniques to build models and draw insights that can spot and flag anomalies. Not only can system anomalies be identified, but they can also be recognised (such as specific problem type) and acted upon using Automation. This kind of deep-dive analysis of live streams of data and the speed in which it can be done makes AIOps a game-changer for IT operations. Traditional ITOA approaches cannot deliver such speed, insights, and surgical resolutions.

In the world of AIOps data is king

AIOps leverages advances in ML and brings AI into the world of IT Operations to proactively seek, identify and solve problems that arise in the application environment. The ability of AIOps to tap into, analyse and act upon the tons of operational data at speed and scale is powerful. AIOps helps IT Operational teams take back control in the fast-moving and increasingly complex digital and multi-cloud environments.

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