Synergistically Rebalancing the EDP of Container-Based Parallel Applications

The use of containers has become standard in cloud environments. However, many parallel applications in containers will not present gains proportional to the extra available hardware. This inefficient use of hardware naturally leads to energy consumption waste. With that in mind, we propose TT-Autoscaling. It works at two different levels: a) in the container, by automatically and transparently tuning the number of threads at runtime of the application, in a way to optimize the trade-off between energy and performance; b) in the cloud infrastructure, by smartly transferring the released resources to other containers that may run in parallel, making better use of the available resources. We compare TT-Autoscaling to the default execution of containers (serial execution with the maximum number of threads), showing 55.8% of performance improvements, 53.6% of energy reductions, and 79.5% of EDP improvements. We also show that TT-Autoscaling outperforms strategies that apply vertical autoscalers proposed by orchestrator tools.