  The scope of the Sixth-Generation Self-Organized Networks (6G-SON) advances
its predecessor's capability towards agility, flexibility, and adaptability.
On-demand overlay networking technologies have shown a prominent maturity while
coping with the rising complexity and scale of enterprise, service provider,
and data centre networks. The Software-Defined Networking paradigm has recently
offered Model Driven Programmability, minimizing network management complexity
through automation and orchestration. However, leveraging Machine
Learning-driven network optimization, a.k.a. Knowledge-Defined Networking
(KDN), has still been a domain of interest for the Network Softwarization
research community. In this article, we propose Intelligent Routing as a
Service (iRaaS) architecture as an application layer cognitive routing
framework for KDNs. iRaaS offers routing logic customization (i.e., customizing
metric function and path-finding algorithm) and provides an option to include
heuristic parameters from trained models as a part of the metric calculation.
iRaaS sits on the application plane above the knowledge plane in a KDN stack,
thus providing platform- and vendor-agnostic coupling with existing network
infrastructures. This article covers the scope of iRaaS by using reliability as
a heuristic for standard path-discovery algorithms, e.g., Shortest Path First
(SPF) and Diffusion Update algorithm (DUAL), along with the architectural
specification. We validate our approach through a Proof-of-Concept deployment.
