Adaptation Models for Cloud-native Applications

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Cloud is a self-serving and on-demand computing model, in which traditionally user-performed tasks are automated and provided by cloud software. It has become critical infrastructure where private and public sectors deploy mission- critical applications that are expected to be robust, secure, and performant. These qualities are many times achieved through automation services that monitor the applications and their environment and keep them within the desired requirements. However, there is an increasing gap between the application's requirements and the capability of automation software. Basically, only a small fraction of cloud operations can be automated due to a lack of models that can replace human expertise. This gap has led the industry to start a new field of practice, AIOps (Artificial Intelligence for IT Operations), which entails "the use of artificial intelligence to simplify IT operations management and accelerate and automate problem resolution in complex modern IT environments." In this partnership, we explore automation software, that is the applications, platforms, and services that manage other software across the cloud infrastructure, platforms, and/or the end-user applications and services. The long-term goal of this partnership is to investigate application-agnostic techniques to design, develop, verify, and manage flexible and resilient AI-based automated cloud-native software systems. The expected benefits to both partners are: new scientific and technological advancements materialized in patents, prototypes, products and publications; exchange of knowledge through meetings, workshops and presentations; and a new generation of talent, capable of addressing the challenges of nascent economies. This partnership will be of direct benefit to all Canadians by: 1) advancing our knowledge and informing society on cloud automation and AI; 2) providing a competitive product/service differentiator to and opportunities for industry to commercialize key cloud- and AI-related technologies; and 3) creating a new generation of highly qualified personnel.