Proactive resource management for cloud of services environments

Abstract

Microservices offer advantages such as better fault isolation, smaller and faster deployments, scalability, and speeding up the development of new applications through the composition of services. However, its large-scale use and specific requirements increase the challenges of monitoring and management. To meet these challenges, we propose a monitoring and management system for microservices, containers and container clusters that autonomously predicts load variations and resource scarcity, which is capable of making new resources available in order to ensure the continuity of the process without interruptions. Our solution’s architecture allows for customizable service-specific metrics that are used by the load predictor to anticipate resource consumption peaks and proactively allocate them. In addition, our management system, by identifying/predicting low demand, frees up resources making the system more efficient. We evaluated our service management solution in the AWS environment, environment characterized by high mobility, dynamic topologies caused by disconnection, dropped packets and delay issues. Our results show that our solution improves the efficiency of escalation policies, and reduces response time by improving the QoS/QoE of the system.