Artificial intelligence for IT operation (AIOps) is an AI application that helps to enhance IT services. It sifts signals out of the noise to identify significant patterns and events related to system performance and availability issues. It collects and aggregates increasing volumes of operations data.

These data are generated by multiple IT infrastructure applications, components, and monitoring tools. AIOps diagnoses the root causes of problems. Sometimes it resolves the issues by itself; sometimes, it reports the problem to the IT team.

AIOps uses a single, intelligent, automated IT operation platform instead of multiple separate, manual IT tools teams. Thus it helps the operation team to respond more proactively and quickly with less effort to outages and slowdowns. It creates a bridge between a challenging, dynamic, and diverse IT landscape and the user’s expectations to reduce the gap.

Three steps framework of AIOps:

The structure or frame of AIOPs can vary from company to company, from team to team, but in general, it consists of 3 steps:

1. Identify: Detect essential events from the noise.

2. Understand: Understand root causes and propose solutions.

3. Resolve: Solve problems, automate responses with real-time proactive resolution.

AIOps uses a large data platform to complete overall IT operations data in one place. It includes- system metrics and logs, network and packet data, streaming real-time operation events, event data, and historical performance, related document-based data, etc. 

Step#1: Identify significant events

The first step is detecting new issues when it occurs or even before it occurs. In DevOps, it needs a long hour to identify topics, teams with specific knowledge about production infrastructure and applications. AIOps provide an improved detection capability. 

  1. AIOps can automatically detect anomalies.
  2. It provides a streamline integration process to connect all data sources for events and incidents.
  3. It correlates related events to reduce noise so that no critical signals go unnoticed.

Step#2: Understand the root causes and solutions

AIOps helps to understand and diagnose events more accurately. 

  1. To prevent problems from increasing, it surfaces key details and streamlines information.
  2. It tries to go to the deep of the issues to know about affected components, impact, and related questions. 
  3. It analyzes the broader context to understand the full impact of an issue.

Step#3: Resolve problems and automate responses

The last step is to solve the problem using automated responses. AIOps enables faster detection and diagnosis to speedier incident response. AIOps does this in 4 possible ways: 

  1. Deliver insights into the tools that have already been used without changing existing workflows.
  2. Direct to the people who are best experienced to resolve them.
  3. Provide feedback and smarter recommendations for continuous improvement.
  4. Automatically trigger remediation actions to detect and fix problems with little help from humans.

AIOps provides visibility of the performance data across the environment, analyzes them, and automatically alerts IT, staff, about the problems with solutions.