DEEP-mon: Dynamic and energy efficient power monitoring for container-based infrastructures

In the last few years energy efficiency of large scale infrastructures gained a lot of attention, as power consumption became one of the most impacting factors of the operative costs of a data-center and of its Total Cost of Ownership (TCO). Power consumption can be observed at different layers of the data-center, from the overall power grid, moving to each rack and arriving to each machine and system. Given the rise of application containers both in the cloud computing and High Performance Computing (HPC) scenarios, it becomes more and more important to measure power consumption also at the application level, where power-aware schedulers and orchestrators can optimize the execution of the workloads not only from a performance perspective, but also considering performance/power trade-offs. In this paper we propose DEEP-mon, a novel monitoring tool able to measure power consumption and attribute it for each thread and application container running in the system. Moreover, we show how the proposed approach has a negligible impact on the monitored system and on the running workloads, overcoming the limitations of the previous works in the field.