IntelliNet
Root-Cause Analysis
US Bank
Alert Correlation
Barclay's Bank
End-to-End Monitoring
The Future of AIOps
As you increase the volume, velocity and variety of data, it gets more difficult for your IT operations team to manually correlate it, analyze it, and solve any problems that arise before they impact user experience. This is especially true for companies with tools dispersed across different data siloes.
In response, AI and machine learning have emerged as a means of relieving some of the manual intervention required to maintain effective IT operations and protect the user experience. This shift is key going forward, because some of the main threats to user experience call for automated actions and decision-making processes that are just beginning to gain adoption. The challenges include:
In the pages to come, you’ll learn about how industry-leading companies are using machine learning and AI to tackle some of the biggest challenges in IT Ops today, including:
At a time when you place such a high premium on user experience, rapid root-cause analysis has never been more important. But it’s made difficult by the proliferation of disparate tools and data siloes, which can make it hard for you to efficiently understand the source of an issue. With AI and machine learning, IT teams can:
• Understand the root cause of a problem affecting one or more services
• Contextualize the information relevant to the issue at hand
• Execute appropriate remediation to minimize impact on user experience
As data increases in volume and complexity, so does the challenge of manually correlating alerts and resolving them before user experience suffers. No wonder that correlation takes up such a large part of the triage process with many IT Ops teams. Which of these top monitoring challenges have you struggled with?
New distributed and microservice-style architectures bring more complexity and new monitoring challenges with them. The use of disparate monitoring tools makes it difficult to get end-to-end visibility across an entire IT estate. And that means it’s even harder to identify and negate issues before they impact up time and user experience.
That’s because if you want to not only survive but thrive in today’s digital economy, you must consider the use of AI in IT operations. Now is the time to start assessing and implementing AIOps-powered solutions to drive the superior user experiences your customers have not only come to expect, but will increasingly demand.
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1-3 TechValidate, AIOps IT industry survey, May 2018
4 Randy Bean, MIT Sloane Management Review, “How Big Data and AI Are Driving Business Innovation in 2018,” February 2018