Secure and Governed API Gateway Architectures for Multi-Cluster Cloud Environments
Vinoth Punniyamoorthy, Kabilan Kannan, Akshay Deshpande, Lokesh Butra, Akash Kumar Agarwal, Adithya Parthasarathy, Suhas Malempati, Bikesh Kumar

TL;DR
This paper introduces a governance-aware, intent-driven API gateway architecture for multi-cluster cloud environments, enhancing policy consistency, performance, and stability through declarative intents and continuous validation.
Contribution
It proposes a novel architecture that decouples intent specification from enforcement, enabling scalable, policy-compliant API gateway management across heterogeneous cloud clusters.
Findings
42% reduction in policy drift
31% faster configuration propagation
Less than 6% latency overhead
Abstract
API gateways serve as critical enforcement points for security, governance, and traffic management in cloud-native systems. As organizations increasingly adopt multi-cluster and hybrid cloud deployments, maintaining consistent policy enforcement, predictable performance, and operational stability across heterogeneous gateway environments becomes challenging. Existing approaches typically manage security, governance, and performance as loosely coupled concerns, leading to configuration drift, delayed policy propagation, and unstable runtime behavior under dynamic workloads. This paper presents a governance-aware, intent-driven architecture for coordinated API gateway management in multi-cluster cloud environments. The proposed approach expresses security, governance, and performance objectives as high-level declarative intents, which are systematically translated into enforceable gateway…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSecurity and Verification in Computing · Cloud Computing and Resource Management · Software System Performance and Reliability
