A wide variety of applications ranging from distributed storage to Forward Error Correction (FEC) benefit from Random Linear Network Coding (RLNC). Recent research activities exploited Network Coding as a Service (NCaaS) as FEC for Software-Defined Networking (SDN). Based on the aforementioned research, in this paper we propose a more efficient approach to use RLNC in a reliability-centric network. By leveraging both, the knowledge possessed by the SDN switches on channel conditions and the dynamic flexibility provided by the virtualized coding instances, we developed a novel method to adapt the code rate of the underlying FEC, to support two different transport protocols with varying reliability and throughput requirements. We have implemented our approach in a realistic SDN emulator to evaluate it in a communication network with time-variant links for TCP and UDP flows comparing against existing fixed-code rate approaches. The results show that our method adapts the flows respectively to the channel conditions and thus delivers a good trade-off between reliability, bandwidth, and overhead. Specifically, our loss estimation algorithm can precisely estimate future losses with a deviation of up to 3%. Our approach is also able to precisely determine the delivery probability with a maximum deviation of 1.5%. In addition, we show that our adaptive redundancy enables TCP to achieve a stable throughput despite losses.