AIOps: From vision to reality
With an ever-increasing reliance on technology, IT operations is emerging as a strategic role in the enterprise. However, before IT operations leaders can fulfill the business’ expectations, they need to overcome significant challenges. From security to resiliency, the IT leader’s day-to-day responsibilities are increasing, leaving them little time to focus on the digital innovations that drive the business forward.
The challenges of this increase in scope are compounded by the lack of available tools to assist. To be sure, there are tools that address specific aspects of IT operations, such as security or performance management, but no one tool effectively addresses the holistic view required by IT leaders, from the director level to the CIO or CTO.
Even at the day-to-day management level, many of these tools fall short of the promised benefits of AI and machine learning. Without an AI-driven analysis of IT operations and self-healing systems, managing IT operations remains a labor-intensive, reactive discipline – one hardly worthy of being called strategic.
What is AIOps?
Increasingly, enterprises are creating titles like Chief Digital Officer (CDO) and giving the individuals who fill these roles a seat at the boardroom table. But with an average tenure of only two and a half years, no doubt, many of these CDOs are struggling to live up to expectations.
Thankfully, we’re reaching a tipping point with the evolution of an approach called AIOps. As you’ve probably already guessed, AIOps is shorthand for AI Operations. And at a high level, the name is pretty self-explanatory: the application of AI to IT operations. But to realize the benefits of AI, we need to unpack that a bit.
AIOps platforms address I&O leaders’ need for operations support by combining big data and machine learning functionality to analyze the ever-increasing volume, variety and velocity of data generated by IT in response to digital transformation.
- Gartner Market Guide for AIOps Platforms
Many of the tools designed for IT operations include AI functionality to some extent. (Though what passes for AI/Machine Learning varies.) These tools can be included as part of your AIOps platform, but they are not AIOps in themselves even if they include some AI functionality. The functionality that characterizes an AIOps solution include:
Holistic – IT leaders don’t have time to hop between tools to get a complete picture of your IT operations. A true AIOps platform serves up these insights in a highly consumable manner, such as a dashboard tailored to the leader’s role and responsibilities.
Integrated – An AIOps platform should aggregate data from multiple sources – security systems, performance management, devops, or other tools used to manage IT operations – even if these tools are from different vendors.
Analytical – It’s not enough to collect the data. An AI Ops solution needs to be able to analyze the data and draw out new insights based on what matters to you.
Predictive – Your AIOps solution should show you more than just what is happening right now. It should also be able to predict what might happen if current trends continue.
Self-healing – Your AIOps platform should help you automate your response to potential issues, including self-healing where appropriate, to ward off some issues and lower the MTTR (Mean Time To Remediation) for others.
4 core functional components of AIOps
Now, let’s dive deeper into some of the core functional components of AIOps. There are lots of tools that can be integrated into an AIOps platform, but here are four core components:
Enterprise Monitoring creates the foundation for your AIOps solution. Some enterprise monitoring solutions include point monitoring functionality, but Enterprise Monitoring provides an enterprise-wide view of IT operations. At a minimum, an Enterprise Monitoring solution must meet the first four characteristics of AIOps: holistic, integrated, analytical, and predictive.
Network Performance Management monitors and analyzes aspects of network performance, such as response times, and can help pinpoint where the problem lies to decrease remediation time. There are many products available on the market today, but to be considered AIOps-ready, the solution should include predictive capabilities so you can spot issues before they happen as well as self-healing functionality to reduce MTTR even further.
Application Performance Monitoring is rapidly gaining traction as more organizations recognize that how their application performs in a production environment can make or break their reputation. An application performance management solution like AppDynamics provides a holistic view of application performance (even across a hybrid environment), can detect bottlenecks and anomalies, and perform a root-cause analysis.
Security Monitoring & Management is often a component of Enterprise Monitoring, Network Performance Management and Application Performance Management, but it is also a component of AIOps in its own right. And, there are plenty of tools available on the market today! Integrating Security Monitoring & Management into the AIOps platform helps align security to the needs of the business and day-to-day IT operations.
If you’d like to learn more about AIOps and how it can help you, we invite you Request a Demo of AIOps. This demo starts the discussions around your reference architectures and products to help build your AIOps strategy.