  Energy consumption of Cloud data centers has been a major concern of many
researchers, and one of the reasons for huge energy consumption of Clouds lies
in the inefficient utilization of computing resources. Besides energy
consumption, another challenge of data centers is the unexpected loads, which
leads to the overloads and performance degradation. Compared with VM
consolidation and Dynamic Voltage Frequency Scaling that cannot function well
when the whole data center is overloaded, brownout has shown to be a promising
technique to handle both overloads and energy consumption through dynamically
deactivating application optional components, which are also identified as
containers/microservices. In this work, we propose an integrated approach to
manage energy consumption and brownout in container-based cloud data centers.
\color{black} We also evaluate our proposed scheduling policies with real
traces in a prototype system. The results show that our approach reduces about
40%, 20% and 10% energy than the approach without power-saving techniques,
brownout-overbooking approach and auto-scaling approach respectively while
ensuring Quality of Service.
