Top Aiops Tools & How to Choose

AIOps tools consume different data sources, collect the application logs, and measure the heath of your systems through automated capabilities like:

• Pattern discovery
• Anomaly detection
• Root cause determination

Today’s AIOps tools have moved beyond their infancy and seem to be growing rapidly. Still, each vendor tends to specialize in one area, so there are certain features to look for, given your enterprise requirements.

In this article, we’ll take a look at AIOps products, including what makes it AIOps (and what doesn’t). Then, we’ll sum up some leading AIOps tools and vendors.

AIOps debrief

AIOps is short for Artificial Intelligence for IT Operations.

AIOps tools are multi-layered technology platforms that automate and enhance IT operations by using analytics and machine learning to analyze big data collected from various IT operations tools and devices. AIOps platforms help IT Ops departments automatically spot, react to, and report on IT Ops issues in real time.

The heart of any AIOps platform combines big data with machine learning to support and partially replace processes and tasks in IT domains like:

• Monitoring
• Service desk & technical support
• Automation

(Learn more in our AIOps explainer.)

What makes an AIOps product?

AIOps is already transforming the IT Operations methodology and overall spending, so it benefits everyone to understand what vendors, products, and services make up the AIOps marketplace.

The goal of AIOps isn’t simply to implement new tooling. A successful AIOps implementation:

• Gathers and consolidates operational information into a big data platform.
• Uses analytics and machine learning to identify, react to, and report on IT issues in real time.

The goal here, says Gartner, is to curate and enhance quality data so infrastructure and operations (I&O) leaders can tie use cases to relevant practices and business persona.

When looking for products in the AIOps marketplace, it helps to remember AIOps is a multi-layered platform with many elements. According to Gartner’s 2021 report, the main functions of any AIOps platform must include these five functions:

Let’s take a look at each characteristic.

Ingestion

An AIOps platform must be able to ingest, index, and normalize events and/or telemetry from a range of domains, vendors, and sources, including but certainly not limited to:

• Networks
• Infrastructure
• Apps
• Existing monitoring tools
• The cloud

The platform must also use machine learning to support both historic and real-time (streaming) data analysis.

Topology

The AIOps platform must discover and assemble a unified topology of IT assets. That means the platform must understand how proximity, logical dependencies, and other dimensions can apply to the relationships between IT assets and the services you’re delivering.

Correlation

An AIOps tool must correlate and compress events in order to reduce unnecessary human intervention. Here, it is combining time and topology to group-related events.

Recognition

Any AIOps tool must be able to process event and telemetry data to detect or predict important events, incidents, or other issues. Because it uses ML, the platform should continually learn and improve the individual patterns of events that are important.

Remediation

The AIOps platform must continuously learn and improve on the associations between each important event and the operations team response to it. The platform can do this in two ways:

• Explicitly being told by the operator
• By observation