Prometheus and AIOps for the orchestration of Cloud-native applications in Ananke

DevOps methodologies reduce the gap between Developers and Operations teams, enabling automation, integration, monitoring, and team collaboration by exploiting continuous integration and deployment and providing high-scale performance for the cloud software delivery life-cycle. AIOps seems to represent the future of IT automation by leveraging DevOps methodologies, Big Data, and AI-enabled strategies for the smart orchestration of Cloud-native applications. Based on the Ananke monitoring model, this paper investigates design issues and strategies required to enable integration between clusters and applications managed by Ananke, and their metrics stored in the Prometheus Monitoring system. Some classic algorithms for anomaly detection and forecasting of time series have been introduced in the proposed AIOps Prometheus Framework for the system analysis and orchestration of applications. Finally, we propose, as a case study, an auto-scaling strategy based on the prediction of traffic peeks for a web application using the Facebook Prophet model.