Today's datacenter is shared among various applications with different QoS requirements, which poses a great challenge to deliver low delay transport with high throughput. Most of works address this challenge by reducing the in-network delay, but assumes a negligible local delay. However, we show that this assumption does not hold for a multi-tenant datacenter that a physical machine is shared by multiple tenants with virtual machines running different applications. As measured, we found that VMs in a PM competing for bandwidth resources introduce delays as high as 13 ms, resulted from the packet queueing at QDisc layer of that PM, because current VMs' rate control still operates in a distributed manner without exploiting knowledge of the QoS requirements of applications running in VMs. This work addresses this problem by proposing a centralized rate adaptation (CERA) that operates in the host PM, dynamically schedules the flows from all VMs in a centralized manner. We implemented a CERA prototype and evaluated CERA through testbed experiments. Our results show that CERA reduces the local delay significantly thus reduces the average request latency of delay sensitive applications, e.g., memcached, by a factor of 6.3, without sacrificing the throughput performance of throughput intensive applications, e.g., iperf.