Building AIOps Now for the Future

AIOps, a term coined by Gartner, refers to the application of artificial intelligence techniques to IT operations data to provide enhanced insights and scalability for managing complex software systems. Despite criticisms regarding the absence of AI in many solutions labeled as AIOps, these technologies do offer tangible benefits, such as automating problem isolation in application performance management and accelerating ticket remediation in IT service management. There are two types of AIOps platforms: domain-agnostic, which are general tools like observability platforms, and domain-centric, which target specific applications or infrastructure. The market for AIOps is still developing, with diverse use cases and a focus on pragmatic outcomes. Current challenges include reliance on unsupervised machine learning, which often leads to ineffective anomaly detection. Nonetheless, advancements in supervised learning and integration with cloud services are promising. AIOps aims to evolve from traditional monitoring to more advanced automated analytics, although it still requires further maturation to fully realize its potential.