Emerging businesses are incorporating many new technologies that are enabling them with capabilities to respond quickly to meet customer expectations. While these technologies like containers, serverless environments, microservices architectures and orchestration tools deliver important functions, they also complicate the application environment and create new IT operational challenges. And since many of the infrastructure is legacy based, identifying the problems, and resolving them becomes and additional challenge.
Since legacy systems and tools cannot handle the volume load of operations data generated by modern environments, new approaches to IT operations and incident response are needed. By adopting AI and ML to automate operations, organizations can harness data and process it faster, smarter, and more efficiently as well as enhance security and enrich user experience.
Enabling automation using ML and AI technologies
It is impossible for people to effectively evaluate the large volumes of data that complex IT environments generate. AI/ML technologies determine relationships across complex IT environments and the exact problems. While improved efficiency is a key value derived by enabling automation using ML and AI technologies, it also solves problems enterprises face in terms of balancing the growing workloads without additional staff. Challenges faced by IT operations teams tasked with driving performance in complex environments have also seen reduction in the form of fewer tickets raised and faster remediation of issues after incorporating AI and ML in their IT operations.
Businesses which are modernizing must adopt AI/ML for help with surfacing intelligence from an ever increasing volume of IT operations data generated by complex, hybrid environments to ensure their software and services deliver premium performance that attract, serve and retain end users and customers.
It is clear that AI and ML are key enablers of automation in IT ops and can be used to accurately analyze increasingly complex IT operations data and enable automation across incident management functions like detection, investigation and remediation. By automating rote work, IT teams are enabled with more time to work on more important problems and projects. The best way to employ AI/ML applications is to purchase monitoring and incident response tools that employ AI and machine learning since most organizations do not have the wherewithal to develop their own AI/ML applications.
iOPEX enables you to stay competitive and serve your customers better by employing disciplined data aggregation combined with ML/AI training models to build an autonomous front & back office operation and analyse the wealth of data you collect and process.