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What is AIOps?

The simple answer is that AIOps stands for Artificial Intelligence for IT Operations. It’s the next generation of IT operations analytics, or ITOA. And its value is in helping organizations address IT challenges on a number of fronts.

These challenges include:

  • The increasing complexity and dynamic nature of IT architectures
  • Digital business transformation
  • Siloed IT operations
  • Exponential growth of uncorrelated data

All of the above render traditional, domain-centric monitoring and IT operations management inadequate. Such systems can’t correlate the onslaught of data various IT domains create. What’s more, they’re unable to provide the insights IT operations teams need to proactively manage their environments. And that just doesn’t work.

IT organizations need a new class of technology to modernize the IT operations process. This technology needs to be able to correlate millions of data points across all IT domains. It should have the smarts to apply machine learning to detect patterns. And it should present that information so organizations can easily see what’s happening and gain insights.

This technology is AIOps

What is AIOps

Figure 1: Gartner’s visualization of the AIOPS platform

“Artificial intelligence for IT operations (AIOps) platforms are software systems that combine big data and AI or machine learning functionality to enhance and partially replace a broad range of IT operations processes and tasks, including availability and performance monitoring, event correlation and analysis, IT service management, and automation.”

(Gartner – “Market Guide for AIOps Platforms” – Will Cappelli, Colin Fletcher, Pankaj Prasad. Published: 3 August 2017)

What the AIOps Architecture Looks Like

An AIOps solution includes the following functional blocks:
AIOP-graphic

Open Data Ingestion

An AIOps platform collects data of all types from various sources. That may include data on faults, logs, performance alerts, and tickets. The ability to ingest data from the most diverse data sources is critical. It allows for an accurate, real-time view of all the moving parts across hybrid IT environments.

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Auto-Discovery

Given the very dynamic nature of modern IT environments, businesses need an auto-discovery process. That automatically collects data across all infrastructure and application domains – including on-premises, virtualized, and cloud deployments. And it identifies all infrastructure devices, the running applications, and the resulting business transactions.

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Correlation

Then it’s time for the AIOps platform to correlate this data in a contextual form. So it needs to determine the relationships between infrastructure elements (such as the physical and virtual connections at the networking layer), between an application and its infrastructure (for instance, by mapping application flows to the supporting infrastructure), and between the business transactions and the applications.

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Visualization

Once the end-to-end correlation process is completed, they need to be presented in an easy-to-use format. And that’s what visualization is all about. Data is typically visualized in topology maps, application maps, business and operations dashboards, and other formats. Visualization is important because allows IT operations to quickly pinpoint issues and take corrective actions.

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Machine Learning

Finding the root cause of a problem is key. But it’s even more critical to determine recurring patterns and predict likely future events. AIOps solutions use supervised and unsupervised machine learning to determine patterns of events in a time-series. They also detect anomalies from expected behaviors and thresholds and predict outages and performance issues.

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Automation

Then it’s time for the AIOps platform to correlate this data in a contextual form. So it needs to determine the relationships between infrastructure elements (such as the physical and virtual connections at the networking layer), between an application and its infrastructure (for instance, by mapping application flows to the supporting infrastructure), and between the business transactions and the applications.

AIOps Use Cases

Enterprise IT Operations teams deploy AIOps solutions to:

INCREASE

Increase
end-to-end
business
application assurance
and uptime

OPTIMIZE

Optimize IT & 
reduce costs by automating 
root cause analysis 
& accelerating technology 
migration

ENABLE

Free up resources 
to enable IT operations to become a proactive source of 
innovation

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