Today's data centers host wide variety of applications which generate diverse mix of internal data center traffic. In a data center environment 90% of the traffic flows, though they constitute only 10% of the data carried around, are short flows with sizes up to a maximum of 1MB. The rest 10% constitute long flows with sizes in the range of 1MB to 1GB. Throughput matters for the long flows whereas short flows are latency sensitive. Research studies point out that data center internal traffic often exhibit predefined patterns with respect to the traffic flow mix. We show that we could leverage insights into the internal data center traffic composition to achieve better throughput for long flows. We propose a smart ECN adaptation scheme based on Software Defined Networking paradigm, which offers the ability to dynamically adapt the network configuration parameters based on network observations. Prototype based test results demonstrate up to 22% improvement in long flow throughput in comparison to plain vanilla ECN scheme.