AIOps platforms take your business to the future
Working in today’s dynamic business environment with traditional IT tools is quickly becoming an impossible task because they are not suited to deal with the challenges of a modern digital business. As the IT landscape continues to see fast-paced and fundamental changes, every aspect of the business success becomes dependent upon the optimized performance and continued innovation of IT-powered services.
What are the AIOps platforms?
Positioned at the intersection of three different IT disciplines — service management, performance management, and automation — AIOps (artificial intelligence for IT operations) brings a new approach that leverages advances in big data and machine learning to overcome legacy tools and human limitations.
Simply put, Gartner defines AIOps as “the application of machine learning and data science to IT operations problems”. In one of their reports, Gartner predicted that large enterprise exclusive use of AIOps and digital experience monitoring tools to monitor applications and infrastructure will rise from 5% in 2018 to 30% in 2023.
How do AIOps platforms work in practice?
Using analytics, machine learning (ML) and artificial intelligence (AI), AIOps platforms analyze the big data collected from various IT operations tools and devices and provide full visibility into real-time issues that might affect the availability or performance of the IT systems that businesses rely on.
They represent the future of ITOps because with network infrastructures evolving, the successful digital transformation will rely on AIOps to automate and enhance IT operations enabling them to function at the speed that modern business requires.
There is a common misconception that AI will replace human operators, a statement that could not be farther from the truth. Actually, AIOps combine the automation of tactical activities with strategic oversight by expert users, preserving valuable human intelligence for less frequent, unpredictable, and high-value activities. In other words, humans and machines operate together, with algorithms augmenting human capabilities and enabling them to focus on what is meaningful.
What drives the emergence of AIOps platforms?
Let’s explore the main challenges of digital transformation that AIOps are addressing:
- Legacy systems cannot keep up with the velocity, variety, and volume of digital data;
- Traditional IT systems are not equipped to manage the modern infrastructure that combines cloud, third party services, SaaS integrations, mobile, and more;
- It takes too long to resolve issues, putting service-level agreement compliance at risk;
- Infrastructure problems must be responded to at ever-increasing speeds;
- Event noise drowns out real issues, reducing efficiency and driving up mean time to repair.
In a constantly changing IT landscape, AI promises to do what humans do but better, faster and at scale. AIOps platforms take this promise one step further, improving IT Operations in the process.
Benefits and applications of AIOps platforms
A recent report published by IDC shows that by 2021, 70% of CIOs will aggressively apply AIOps to cut costs, improve IT agility, and accelerate innovation. Although impressive, this is only a summary of the many benefits entailed by the AIOps platform.
- Eliminating the skills gaps as the experts get easier access to data with built-in intelligence and can focus on key decisions;
- Increasing business responsiveness by making data-driven decisions to ensure that the business stays up-to-date with emerging trends;
- Processing data more efficiently with smart algorithms powered by ML and big data, reducing the mean time to detect and mean time to repair by about half;
- Removing noise and distractions to enable the IT specialists to focus on what’s important and not be distracted by irrelevant alerts;
- Providing a holistic vision across the entire IT environment, by correlating information across multiple data sources.
Among the main real-life applications for AIOps are the following:
- Analytics – provide interactive dashboards and dynamic visuals for data analytics;
- Anomaly detection – detect abnormal behavior in system metrics, services, user activity;
- Predictive analytics – determine future trends for metrics based on past values;
- Events clustering – cluster events using various techniques including neural feedback;
- Automated RCA (root cause analysis) – automatically detect with increasing accuracy the root cause of incidents.
There is still untapped potential in the use of AIOps platforms which makes it an interesting topic for business leaders on the market.
Promise of AIOps
The market for AIOps platforms is still in its infancy stage but with more companies becoming interested in starting their digital transformation journey, their interest in AIOps continues to increase. These companies understand that by applying AIOps, in addition to enhanced efficiencies and cost savings, they will be able to find and fix issues faster and even gain the predictive insights they need to prevent issues from occurring in the first place.
What is your experience with using AIOps for your business? Share your thoughts in the comments section below!