One of the main causes of packet loss and performance degradation in today's datacenter operations, is represented by microsecond-scaled congestion events, known as microbursts. Microbursts are characterized by sudden spikes in network traffic, and are likely to lead to congestion, impacting the overall efficiency of the datacenter. Existing solutions, such as packet deflection techniques, have shown promise in mitigating microburst effects. However, further research is needed to explore alternative approaches that can enhance network performance and stability. In this study, we propose Robinhood, a solution aimed at mitigating microbursts in datacenter networks as well as improving the overall performance. We exploit the insights gained from existing solutions, taking inspiration from the job-scheduling domain, and implement novel algorithms based on work-stealing scheduling techniques to address the challenge of microburst mitigation.