Modeling Autonomic Systems in the time of ML, DevOps and Microservices
Nelly Bencomo · 2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C) · 2021
Concurrently, continuous integration and continuous delivery practices changed the way software production chains are conceived. The permanent access to new data, and therefore the need for ML, bring up unique aspects to be considered. The uncertain and dynamic context of the new ecosystems calls for adaptation support similar to that provided by autonomic (a.k.a. self-*) systems to be added into the architecture. An autonomic solution aims to facilitate the update of the architecture at runtime towards a new desired behaviour.During this talk, I will discuss possible trade-offs, challenges, modelling techniques for software architects, and research directions involved in building autonomic systems in the era of ML, DevOps and Microservices [5], [7]. I will also talk about the role of runtime models [2] –[4], [8] and the MAPE-K architecture [1], [6], [9] when modeling autonomic systems.