Gateway API v1.0 as Mesh-Lite Traffic Management
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P119Keywords:
Gateway API, Mesh-Lite Architecture, Traffic Management, Kubernetes, Service Mesh, Cloud Networking, API Gateway, Microservices, Observability, Load Balancing, Policy Enforcement, Edge Computing, Scalability, Network Resilience, Multi-Cluster Deployment, Declarative Configuration, Latency Optimization, Cloud-Native Networking, Service Orchestration, Resource EfficiencyAbstract
Modern distributed architectures call for traffic management strategies that are scalable yet do not weigh down the system with unnecessary overhead. Such strategies should also facilitate observability, enforcement of policies, and intelligent routing, importantly, without the accounts of full service meshes. The paper positions Gateway API v1.0 as a mesh-lite model that serves as a bridge between straightforward ingress controllers on one side and complex service mesh infrastructures on the other. In effect, Gateway API introduces the use of Kubernetes resources as a standard for routing, resilience, and security policies thus gaining in modularity, extensibility, and in the same time operational simplicity. The assessment was carried out by the installation of Gateway API in multi-cluster and edge-cloud setups, and performance metrics such as latency, throughput, and configuration complexity were measured and compared with Istio and Envoy-based meshes. The results show that Gateway API is capable of providing observability and traffic governance at almost mesh levels while it reduces the resource consumption by 40–60%, which in turn facilitates lifecycle management and integration. Case studies highlight its feasibility for the hybrid and edge scenarios where the full mesh cannot be efficiently used. In essence, findings represent Gateway API v1.0 as a cloud-native networking tool that has undergone a practical evolutionary process, thus enabling scalable service orchestration and adaptive traffic control that is in harmony with Kubernetes’ declarative model. Consequently, this has been traffic management redefined for the modern distributed and edge-native ecosystems.
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