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AIOps Explained

Learn how AIOps streamlines IT operations and service delivery using artificial intelligence

AIOps helps find and fix business application problems with capabilities ranging from advanced probable cause analysis to intelligent automation. Read on to learn more about how AIOps works and why it's a critical topic for today's modern IT organization.

What is AIOps?

Short for artificial intelligence for IT operations, AIOps is an approach to managing complex IT operations that optimizes service availability and delivery. AIOps runs on multi-layered technology platforms that harness machine learning, predictive analytics, and AI to automate, enhance, and improve IT operations.

Central to the success of AIOps is big data. By collecting, ingesting, and analyzing data from the gamut of IT operations tools, AIOps solutions can:

  • Advance traditional analytics capabilities
  • Automatically spot and react to issues in real-time
  • Proactively alert on potential issues before they become a problem

AIOps is a full-scale solution to support complex enterprise IT operations. Other names for AIOps include AI operations and AI for ITOps. Gartner, a leading analyst firm, coined the concept of AIOps in 2017 with this definition:

"AIOps combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection and causality determination."


Drivers & goals

Traditional approaches to IT operations are being challenged by two key factors:

  • The increasing complexity and hybrid nature of IT environments.
    Doing business today means various infrastructures (cloud, private data center, mainframe), applications, and software communicating effectively, often across disparate geographies.
  • The rapid adoption of new deployment technologies.
    To keep pace with employee and end user expectations, businesses contend with the regular and timely integration of new technologies.

Massive volumes of data and rapid tech adoption results in several problems, including poor visibility, degraded performance and availability, and costly tool sprawl. With AIOps, businesses can reduce, quickly resolve, or even prevent these problems by moving from a reactive to a proactive stance.

Some of the goals that companies can achieve using AIOps include:

  1. Gathering and consolidating operational information (e.g., metrics, logs, alerts) into a big data platform with a variety of views.
  2. Using analytics, ML, and AI to identify, react to, and report on IT issues in real-time.

How AIOps works

Many AIOps solutions provide piecemeal intelligence and automation capabilities. But the pace of business today demands a comprehensive, enterprise-wide solution that can capitalize on valuable data and prevent problems before they occur.

Enterprise AIOps solutions should coordinate multiple functions to optimize operations, including:

  • Ingestion

    Ingesting, indexing, and normalizing events and data from all types of sources—networks, domains, infrastructure, applications, and more—across an increasingly hybrid infrastructure. Ingestion should support both real-time (streaming) and historical data analysis

  • Discovery and unified topology

    Discovering IT assets and assembling a unified topology, no matter the source. The topology indicates key information, such as proximity and logical dependencies, so the AIOps platform can understand how assets support the services a business delivers.

  • Correlation

    Compressing and correlating events—connecting topology and time to related events—in order to reduce human intervention.

  • Recognition

    Processing data from events and telemetry in order to detect or predict important incidents, events, or other anomalous behavior. Here, machine learning helps the AIOps solution to continually learn and improve its understanding of individual event patterns.

  • Remediation

    Building on all the previous functions to fix or otherwise handle anomalous events and behaviors. An effective AIOps solution can remediate in two ways—by observing and responding automatically and by taking explicit direction.

A Day in the life with AIOps.

See how AIOps improves the workday in this interactive experience

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Why AI Ops: Use cases for AIOps

What can AIOps offer a business? Here are the most common use cases:

Open, cross-domain engagement, observability, and actionability. With true enterprise-wide, platform-driven management, IT can better predict issues, resolve them faster, and provide always-on service.

Event noise reduction. Separate the high-impact problems from common spikes to get a clearer view of the real issues causing event storms.

Intelligent anomaly detection. By federating data from the entire IT environment, including third-party tools, AIOps can filter and correlate the data to trigger appropriate events and notifications.

Intelligent automation and event management. With continuous detection of the state of infrastructure and service desk activity, users can take or recommend automated actions to fix issues faster.

Cross-domain situational understanding and probable cause analysis. Apply advanced analytics to aggregated data across infrastructure and applications to isolate issues and respond, saving time and resources.

Capacity analytics. Understand when and how resources are being used, determine the resources needed to support the most in-demand apps and services, and identify idle and unused resources that are opportunities for efficiency improvements and cost reduction.

BMC approach to enterprise AIOps

At BMC, we believe that AI can augment human effort—and AIOps is a perfect example. Reducing manual work, AIOps helps employees focus on value-add activities that require human skills.

Our AIOps approach enables your organization to make better decisions, faster. Find and fix problems before you’re aware of them. Focus on doing what’s important for your business, whether it’s building cars, running communications networks, maintaining client financial security, or delivering healthcare.

As a leader in enterprise IT solutions for more than four decades, we’re uniquely prepared to help our customers implement enterprise-wide AIOps—from cloud to data center to mainframe, and everywhere in between. With solutions like BMC Helix and BMC AMI, you can reduce problems, find fixes faster, and deliver service at the speed and quality that your users expect.

BMC is a trusted leader in AIOps