42% of IT Professionals Say They Use More than 10 Monitoring Systems

In a recent survey on demand and use of AIOps, about 27 percent of information technology professionals surveyed said they had “never heard of the term” according to Big Panda. 

Some 42 percent of respondents reported using more than 10 monitoring tools, while 19 percent of respondents said their organizations used more than 25 separate monitoring tools. Most observers say the time it takes to isolate and fix alarm conditions is complex because so many different monitoring systems and alarms are routinely generated. 

source: Big Panda

source: Big Panda

AIOps Wrings Value from Full Packet Capture

Cheap computation and storage mean many impossible operations have become practical. Use of millimeter wave frequencies for commercial end user communications is among the salient examples, but enterprise ability to capture and process nearly all data generated by the enterprise, for the purpose of wringing insights out of that data provides another example. 

According to Cisco, companies can expect to see their network traffic triple by 2022. “This will require organizations to make a proportional increase in data storage and maintain a brute force, record-everything approach for network forensics that will cost companies significantly more in terms of time and money,” says Randy Caldejon, CounterFlow CEO. 

AIOps plays a key role here, he argues. “Full packet capture is finally entering the age of practicality because of the introduction of AIOps,” he argues. 

“Thanks to AIOps, security analysts now have an opportunity to utilize more open source technologies and experiment with ML and AI to make packet capture work better for them and their organization,” he says. “Before, it was unrealistic to expect a group of analysts in a security operations center to proactively ferret through petabytes of data in search of an anomaly.”

Gartner defines AIOps as the application of machine learning (ML) and data science to IT operations problems. The firm also predicts that large enterprises use of AIOps tools will reach 30 percent by 2023.

Why AIOps Might Help IT Operations Improve

A new Digital Enterprise Journal (DEJ) study, The Roadmap to Becoming a Top Performing Organization in Managing IT Operations, finds that top-performing information technology organizations outperform others in large part because they are able to detect performance issues faster, resolve issues faster and create new products faster, at lower cost. 

Top-performing organizations can proactively detect 79 percent of performance issues ahead of time while all other organizations are only able to detect 39 percent of performance problems. 

The average mean time to incident resolution for TPOs is 38 minutes while it takes five times more time (224 minutes) for all other organizations.

Top performers also can deliver innovative products and services at a faster pace (5.1 times faster release velocity as compared to all other organizations) and do so at a lower cost (4.2 times more end-users supported per IT full-time employees.

source: OpsRamp

And that is where AIOps plays a role, improving pattern recognition and anomaly detection, therefore reducing the amount of time before performance issues are identified and remedied. 

source: OpsRamp

AIOps Market Growth Looks a Lot Like IT Ops Growth

This 2026 forecast for the information technology operations market looks suspiciously like projections for AIOps. Probably because most of the market is repurposed IT ops revenue, with AI features added. 

source: Zion Research

So here's one forecast for AIOps. 

source: Maximize Market Research

And here's another. 

source: Garner Insights

And another. 

source: Coherent Market Insights

AIOps Platform Market Forecasts are Plentiful, but Are They Accurate?

There is no shortage of AIOps market studies, forecasts and estimates. The question some of us might have is whether AIOps revenue is actually incremental new revenue or simply some of that and a rebranding of legacy IT ops solutions. Personally, I'd lean towards the latter interpretation.

The AIOps platform market will see a 26 percent on a compound annual growth rate to 2026, according to Coherent Market Insights. How much of that growth is shifted from existing enterprise information technology or analytics spending budgets is not so clear. 

source: Coherent Market Insights

Other researchers see sales growth on the order of 25 percent CAGR until 2025, or as much as 34 percent, to reach $18.51 billion, by 2026, according to Data Bridge Market Research. 

Platform revenue is expected to be about $1.76 billion at the moment, according to Data Bridge.

AIOps is about Analytics Driving Insight

You still can get an argument about whether the primary purpose of AIOps is insight or action, but all agree inferences and insight are essential to the value proposition. 

source: OpsRamp

Gartner predicts larger enterprises’ use of AIOps and digital experience monitoring tools for monitoring applications and infrastructure will rise from five percent in 2018 to 30 percent in 2023. 

The AIOps analytics market represented sales of about $2 billion in 2016, according to IDC. 

source: IDC

Automation, which is critical to running AIOps smoothly and efficiently, helps drive AIOps to perform, according to CIO:

• Automated monitoring: discover the full environment and identify when new endpoints, such as a virtual server or machine, a new mobile device, or even a new cloud platform, are brought up
• Automated AIOps: run AIOps while adhering to established policies and dependency mapping and requiring no advance configuration
• Automated remediation: quickly and efficiently execute the necessary steps to resolve any fault or performance events

AIOps helps enterprises consolidate and analyze infrastructure operational data coming at them at a rapidly increasing pace from myriad sources, says Micro Focus. 

It can reduce the overall volume of potentially damaging events, provide alerts to conditions that could cause an outage, isolate the cause of those events, and apply process automation to remediate events, Micro Focus argues. 

Insight Arguably is Primary for AIOps

Insights are the objective of AIOps processes. Many would agree that automated or expedited response runs a close second. Knowing what to fix, then doing so, in other words. 


source: Tech Target