  Network slicing is one of the major catalysts to turn future
telecommunication networks into versatile service platforms. Along with its
benefits, network slicing is introducing new challenges in the development of
sustainable network operations. In fact, guaranteeing slices requirements comes
at the cost of additional energy consumption, in comparison to non-sliced
networks. Yet, one of the main goals of operators is to offer the diverse 5G
and beyond services, while ensuring energy efficiency. To this end, we study
the problem of slice activation/deactivation, with the objective of minimizing
energy consumption and maximizing the users quality of service (QoS). To solve
the problem, we rely on two Multi-Armed Bandit (MAB) agents to derive decisions
at individual base stations. Our evaluations are conducted using a real-world
traffic dataset collected over an operational network in a medium size French
city. Numerical results reveal that our proposed solutions provide
approximately 11-14\% energy efficiency improvement compared to a configuration
where all the slice instances are active, while maintaining the same level of
QoS. Moreover, our work explicitly shows the impact of prioritizing the energy
over QoS, and vice versa.
