Increased IT complexity drives the need for AIOps
As the AIOps market matures, many in the industry believe that companies will turn to AIOps platforms as their sole monitoring tool, as these platforms are able to natively acquire data and analyze.
Modern digital businesses need AIOps tools to enable continuous insights across an IT stack. Such insights are increasingly important as systems that require monitoring and management become more complex, more distributed, and further removed from the tight control offered when everything was on-premises.
In particular, the use of cloud-based resources makes network management more difficult. Visibility gaps in network monitoring and alerting tools arise, with networks now extending into third-party managed infrastructure-as-a-service (IaaS) clouds and applications/data moving to platform as a service (PaaS) and SaaS.
While more monitoring and alerting capabilities are great, they can add to the workload of already busy IT staff. That’s why the industry is moving away from separate network, application, and device monitoring tools towards so-called Artificial Intelligence (AI) for IT Operations, or AIOps for short.
AIOps platforms combine traditional monitoring tools with streaming telemetry and analyze it all using AI. AI analyzes each data source and correlates multiple anomalies to automate problem identification while providing detailed insights on how to fix the problem. So, if an AIOps platform is properly implemented, it not only provides more visibility into potential issues, but also eliminates many manual troubleshooting and remediation tasks.
An AIOps solution should automatically discover the relationships between state data and business outcome. (In a rules-based system, the same amount of configuration work is required as in many manual systems.)
There is also a difference between monitoring and management. A tool should provide information rather than the human user looking at the data and then sorting out what’s going on. The tool should tell an IT manager that there is something that needs attention. The Goal: AIOps provides automation to reduce time spent manually intervening and enable more time with applications.
See also: AIOps takes center stage in the IT management arsenal
Gartner’s point of view
Such systems provide insights that tell the full story of what’s going on behind the systems, enabling IT teams to achieve operational efficiency and high availability that lead to customer satisfaction.
This was the theme of a recent strategic advisory session, “Gartner’s Vision for AIOps in 2022 and Beyond,” presented by Gartner Principal Analyst Pankaj Prasad. According to a recent blog by Richard Whitehead, Chief Evangelist at Moogsoft, Prasad discussed the importance of AIOps as businesses continue to adopt new technologies.
“It’s by connecting the dots to convey a story that we see many organizations turning to the AIOps platform,” according to Prasad. At this point, the two noted that AIOps cuts across all three areas of IT operations:
- Observe (Monitoring): Do we know what is going on? AIOps offers real-time and historical data by analyzing event metrics, traces, and topology and administers data analysis, anomaly detection, performance analysis and correlation, and contextualization.
- Engage (IT Service Management): What happens within IT and how does it relate to the end user? AIOps provides incident, dependency, and change notifications and covers task automation, change risk analysis, SD agency performance analysis, and knowledge management.
- Act (Automation): What are we doing in the IT operations space? AIOps supports scripts, runbooks, and application publishing automations (ARA).
See also: AIOps is an essential component of the DevOps toolchain
As the market matures, many in the industry believe that companies will turn to AIOps platforms as their sole monitoring tool, as these platforms are able to natively acquire data and analyze it. . This makes it ideal for many aspects of business operations and useful to many groups including IT, operations, site reliability engineers and even SecOps.
As such, the market is poised for strong growth. Last year, Gartner said AIOps in the IT operations management market will grow at a compound annual growth rate of 15% per year through 2025, from over $1 billion in 2020.
Part of the appeal of AIOps is that it helps solve problems as complexity increases. Businesses routinely use multiple clouds and a combination of multiple cloud services and legacy systems. It gives an overview of the status of these systems.
Additionally, most businesses now need to support many more devices and applications. IT staff often cannot keep up with the large number of alerts, logs, telemetry data, etc. As such, they are turning to AIOps to help manage IT operations and security, relying on AI and machine learning to help sort through data.
The promise of AIOps is not just to help IT teams respond to outages and performance issues. Perhaps the greatest value lies in using predictive analytics to identify and prevent future failures. And increasingly, AIOps is being embraced by developers. Specifically, DevOps teams are beginning to move its use earlier in the pipeline to analyze development and pre-production environments and reduce risk.