Automatic Adaptation of Reliability and Performance Trade-Offs in Service- and Cloud-Based Dynamic Routing Architectures

Many different dynamic routing architectures are available, including sidecar-based routing, routing through a central entity such as an event store or gateway, or architectures with multiple routers. These architectures are currently based on vastly different implementation concepts, such as API Gateways, Message Brokers, or Service Proxies. We propose a new approach that abstracts all these architecture patterns using one Adaptive Dynamic Routers architecture. We hypothesize that a dynamic self-adaptation of the routing architecture is beneficial over any fixed architecture selections for reliability and performance trade-offs. That is, if encountered with traffic and load changes, our approach dynamically self-adapts between more central or distributed routing to optimize system reliability and performance. We evaluate our approach by analyzing our previously-measured data during an experiment of 1200 hours of runtime. Our extensive systematic evaluation with 1089 cases confirms that our hypothesis holds and our approach is beneficial in terms of reliability and performance. Moreover, we empirically validate our results on Google Cloud Platform infrastructure.