AIOps (Artificial Intelligence for IT Operations) is the new kid on the block. Businesses have only just begun to get their heads around the likes of DevOps - so why should they take note of yet another ‘buzz’ and seemingly complex new acronym?
In essence, AIOps is all about improving IT operations - but how? AIOps platforms utilise data, Machine Learning (ML) and Artificial Intelligence (AI) to automatically spot and react to operational issues in real-time. It’s about making businesses more efficient. Freeing up IT’s time to focus on further innovation in order to optimise customer and employee experience, through the digital services (applications and associated infrastructure) used.
The past decade has been marked by exceptional advances in technology innovation, which have resulted in increasingly more complex environments for IT to manage, but conversely more data and potentially more insight than ever before. Application performance monitoring (APM) solutions have proven essential in helping IT leaders manoeuvre by providing real-time insights that are needed in order to take the right action specifically in regards to detecting performance or availability issues. But as the volume of data in IT ecosystems increases, technologists are finding it challenging to manage. And while automation has helped teams reduce the time spent on repetitive, manual tasks, it does not entirely answer the challenge of today’s increasingly complex environments.
What’s needed is a robust strategy, underpinned by AI and ML, to improve agility, minimise time-consuming routine tasks, and surface the insights that matter most.
From ‘Oops’ to AIOps
Grappling the potential of AIOps to deal with application environment complexity is a necessity for any modern enterprise. It helps technologists get ahead and ensures companies decrease revenue-impacting outages, where customer experience and brand reputation are at stake.
According to AppDynamics’ research, only 15 per cent of IT teams identify an AIOps strategy as a top priority for their business in the next 12 months. Companies that truly want to drive innovation and digitally transform the way they do business should adopt AIOps as part of their monitoring strategy as this can be a real gamechanger.
So, what should enterprises do if they want to get ahead of the curve?
Create a holistic view of performance monitoring
Today, midsize to large companies use an average of eight different cloud providers for their enterprise applications and services according to IHS Markit. This means managing an increasing set of tasks that might become disconnected if not managed properly. AppDynamics discovered that almost half (48 per cent) of enterprises release new features or code at least monthly, with 91 per cent of IT leaders saying that the current monitoring approach only provides a siloed view on the quality and impact of each release.
There is a clear demand for businesses to move away from siloed ways of working to create a unified view of how all elements interact. And that’s where leveraging data through ML and AI can help IT operations in a new enterprise environment.
Put proactive APM on the agenda
IT teams are no longer hidden away. Instead, they are at the centre of driving the business forward, with the new breed of technologist - Agents of Transformation - possessing the vision and tools to effect positive change and a more proactive approach to APM. Currently, it takes an average of one business day, or seven hours, to resolve a system-wide issue, with 42 per cent of IT leaders still using monitoring and analytics tools reactively to find and resolve technical issues.
The longer it takes to resolve an issue, the greater the potential for it to turn into a wider-business problem, particularly in the fast-paced digital world. And when it comes to monetary loss, AppDynamics discovered that a single service outage can cost a business in the UK an average of £168,496.54.
With almost all IT leaders surveyed reporting performance issues related to business-critical applications in the last six months alone, the need for a proactive approach and the implementation of an AIOPs strategy becomes critical.
The future of IT operations
The need for a dynamic technology to support business operations is evident. One of the most fundamental capabilities AIOps can provide to monitoring is not simply automating existing IT tasks, but identifying opportunities for improvement, and managing new optimised tasks, constantly learning as application environments change. To ensure that IT teams meet the demands of the complex application environments, AppDynamics provides real-time visibility and AI and ML-based insight and automation that drive improved customer experiences and business performance.
Solving problems quickly and understanding their impact on the business will play a crucial part in performance management in the years ahead. AIOps can assist in providing more agility in the face of potential service disruptions or threats, without the additional drain on resources.
The increasingly complex application environment requires businesses to revamp their current operation processes. Implementing AI and ML into systems’ monitoring will ensure IT leaders can be more productive, spending time on higher-value work, and helping to proactively identify issues before they arise.
There is, however, still plenty of room for improvement. Businesses must first prioritise and invest resources into an AIOps strategy to build a stronger connection between IT and the wider business.
John Rakowski, Senior Director of Technology Strategy, AppDynamics