I’ve been posting recently about how transformational technologies such as artificial intelligence (AI), machine learning, and blockchain have begun reshaping the business and creating new customer-focused services.
One of the key trends that’s materializing from the continuing maturation of AI and machine learning is how these technologies are disrupting Cloud/IT operations (ITOPs) and IT Service Management (ITSM). AI and machine learning are making these activities more intelligent and automated, driving higher levels of productivity and continuous improvement.
As my friend Muddu Sudhakar recently shared with me, the emergence of ‘AIOps’ – or artificial intelligence for Cloud & IT operations – is a new approach for automating and enhancing IT operations through the use of machine learning and analytics to identify and respond to IT operational issues in real-time.
Just as AI and machine learning have had a tremendous impact on cyber security solutions, a similar trend will also play out for ITOps, DevOps, and CloudOps. “In 2018, CIOs will see disruptive solutions for Cloud and DevOps, AI/ML-driven IT Ops (AI Ops), and AI/ML-driven IT Service Management (AISM),” says Muddu.
Muddu is a serial innovator and tech entrepreneur whose distinguished background includes executive leadership roles at companies such as Splunk, ServiceNow, VMware, Pivotal and EMC. Muddu is a true visionary who is adept at forecasting where the market is heading. I appreciate his insights as the predictions we provide to CIOs and technology leaders is a unique service that HMG Strategy delivers to the forward-looking executives in our network.
As Muddu sees it, there are “3 P’s” that contribute to the success of AIOps: Proactive, predictive, and prescriptive multi-cloud operations.
In the new world of Serverless architectures and Microservices-based applications with dynamic and elastic resources, the old IT methods and processes are not just suboptimal – they actually fail. This is where AIOps become necessary not just for IT optimization but rather to ensure the integrity, stability and transparency of Cloud and IT operations. For instance, AIOps will enable companies to proactively gauge the health of enterprise IT operations, including dynamic cloud activities.
“Customers want AI-driven multi-cloud operations for monitoring, detection, and prevention of disruptions,” said Muddu. “Disruptions can cause revenue loss, unhappy users, impact brand reputation, etc. Enterprise CIOs need to leverage multi-cloud and DevOps trends with AI/ML to automate operations and provide real-time visibility to take actions.”
Meanwhile, AIOps can also enable IT teams to anticipate or “predict” Cloud/IT Ops issues before they occur, such as server capacity constraints that need to be immediately addressed without the need for human intervention. In addition, the “prescriptive” use of AIOps can help IT organizations to identify and implement the most effective solutions to Cloud/IT Ops challenges when they arise.
“Intelligent IT operational management is vastly more efficient and productive than what IT teams currently have in place,” said Muddu.
AIOps can be extended to service management, performance management, and automation to revolutionize Cloud & IT operations across a plethora of infrastructure systems, storage, networks, and services/applications.
For the past several years, I’ve been advocating how it’s critical for CIOs to identify ways to use technologies to help disrupt the business and create new business models that can deliver increased value to the enterprise. But technology executives must also continually disrupt the IT organization to identify new ways to achieve improved performance. AIOps represents such an opportunity.