Deep dive into Artificial Intelligence for IT operations (AIOps)

1. Blog 2: Opsramp.com Deep dive into Artificial Intelligence for IT operations (AIOps) IT Infrastructure Monitoring is an age-old practice in the land of enterprise IT. But as anyone working in the field knows, doing this job well nowadays is like pushing a rock up the hill (and against the wind). A 2018 Everest Group survey found that 71% of CIOs reported the lack of a meaningfully scalable model for infrastructure growth. So, while the public cloud has been designed for massive, on-demand scalability, the reality of attaining this in the average hybrid IT environment is not easy without sacrificing performance, security, and uptime. Over the past few years, artificial intelligence for IT operations (AIOps) has emerged as a promising new way to do more with less. Many IT operations teams are static; small staffs simply cannot keep pace with the onslaught of new technologies and cloud services, while simultaneously having to add DevOps skills to the daily infrastructure monitoring workload. Something is got to give and AIOps could be the bridge between old and new ways of working. AIOps: It’s everything, it’s nothing, it’s definitely something AIOps is increasingly being defined by IT analysts as a software category, although it remains a little hard to nail down. AIOps leverages a broad set of technologies and methods including machine learning, network science, combinatorial optimization, and other computational approaches for solving everyday IT operational problems at scale. “AIOps is uniquely suited to anomalydetection, predictive analytics, and seasonal forecasting,” says IT and DevOps thought leader Donnie Berkholz, said in an interview. “The big value is in learning about unknown unknowns and to understand what normal looks like.” Elaborates Mike Kavis, chief cloud architect for Deloitte Consulting, “AIOps means 70 things to 30 different people. But it comes down to using intelligence to supplement or augment operations. It is using systems and machines and artificial intelligence capabilities to help supply information to help solve a problem. That problem could be operating the system or as simple as when you’re in Gmail andyou’re typing a search.” OpsRamp customer Epsilon, an email marketing services provider, has been using OpsRamp AIOps capabilities to progress from a semi-manual IT infrastructure monitoring environment to one that is fully automated and optimized. For example, OpsRamp has audited the process of sending alert notifications to the right team members at the right time. Another OpsRamp customer, Zebra Technologies, is finding that AIOps makes infrastructure monitoring far more efficient and accurate by reducing alert noise so that IT operators can focus on solving actual business problems instead of combing through massive, uncategorized data sets.

2. Blog 2: Opsramp.com But is there more? Some artificial intelligence observers believe that AI has an eventual role in the area of predictive operations. Over time, once the machine learning models have matured and moved toward self-learning capabilities, they will be able to see patterns at very early stages and predict when something will likely go wrong. Tools can even be configured to fix a routine problem safely, without human intervention. AIOps may even be used to help determine when changes – such as configurations, new types of services or workload migrations – could deliver quantifiable advantages. By looking at IT operations usage metrics for signals of customer intent, CIOs could perhaps answer questions such as: why are customers buying from us and how can we engage them better? Indeed, as with any emerging technology, the limits we have placed on its potential lie squarely in our past experiences with older, outdated tools. The eventual value of AIOps for infrastructure monitoring may go far beyond application performance and uptime, as writes this Medium author: “The competitive advantage in adopting and embracing AIOps is not purely from a resource unit/opex savings perspective, but has the potential to bring continuous innovation in the enterprise.”