cloud landing zone design

Enterprise cloud environments are frequently exposed to security threats due to misconfigurations, excessive permissions, and fragmented security tooling, compounded by the absence of unified, coordinated protection across Kubernetes, OpenStack, and Infrastructure-as-Code (IaC) platforms. This work proposes the first open-source microservices-based security framework that uniquely integrates identity governance, multi-platform configuration auditing, runtime threat detection, and automated IaC remediation into a single closed-loop system. Designed with standardized REST/gRPC interfaces and scalable for medium-to-large deployments, the framework synergistically combines Falco, ELK, Terraform, Checkov, and OPA. In enterprise evaluations, it reduced vulnerability assessment time from 120 to 18 minutes, achieved a false positive rate below 5%, decreased security incidents by 62%, and lowered operational costs by approximately 40%, all while being released under the Apache 2.0 license.

This study addresses the inefficiencies in SaaS onboarding within regulated enterprises, where siloed security and compliance controls—spanning third-party risk management, cybersecurity, identity and access management, and disaster recovery—often result in process delays, redundant assessments, and ambiguous accountability. To overcome these challenges, this work proposes an end-to-end, control-driven SaaS onboarding framework that integrates multi-domain controls into a unified lifecycle model encompassing requirement intake, architectural validation, identity design, resilience assessment, and post-deployment governance. By leveraging cross-domain control mapping, phased process modeling, and governance checklists, the framework codifies key design patterns such as secure connectivity, federated identity, least-privilege access, and shared-responsibility disaster recovery. Empirical implementation demonstrates that the approach significantly reduces onboarding friction, enhances audit traceability, and strengthens both the security posture and operational resilience of SaaS platforms.

This study addresses environment inconsistencies, expanded supply chain attack surfaces, and weak compliance arising from redundant builds in cloud deployments by proposing an artifact promotion control model that establishes a “build once” principle. Methodologically, the work rigorously distinguishes artifact from environment identities, demonstrates that secret injection compromises artifact integrity, derives that release roles require no production credentials, and implements end-to-end autonomous governance on AWS in accordance with NIST SP 800-204D. Experimental results show that the model supports fully autonomous releases via a single command, completing 22 deployments in the first month with individual rollbacks requiring only 36 seconds. These findings indicate a significant reduction in operational complexity alongside strengthened integrity guarantees for cloud deployment pipelines.

Cloud architecture design faces challenges including ambiguous requirements, implicit decision-making processes, and complex interdependencies among architectural elements. To address these, this paper introduces CloudArchitectBuddy—a novel system featuring a synergistic dual-mechanism framework: *structured state management* and *guided decision support*. It explicitly models requirement evolution and design decisions via a finite-state machine, integrates rule-based validation with large language models (LLMs) for requirement refinement and consistency checking, and establishes a hybrid human–AI collaboration paradigm combining structured workflows with natural-language dialogue. Evaluated with 16 industry practitioners, CloudArchitectBuddy achieves design quality comparable to pure chat-based interfaces while significantly improving usability (*p* < 0.01), architectural relationship comprehension (+32%), and missing requirement identification (+41%). These results empirically validate the effectiveness and practical value of its mixed-interaction approach.

To address challenges in highly regulated environments—including cross-cloud governance complexity, high operational overhead, and prolonged configuration cycles for cloud-native applications (CNAs)—this paper proposes a “batteries-included,” out-of-the-box reference architecture. The architecture tightly integrates policy-as-code, declarative APIs, service mesh, and a compliance metamodel to automatically embed governance capabilities across the application lifecycle while decoupling them from business logic. It introduces the first unified abstraction mechanism for cross-cloud governance elements, enabling lightweight deployment alongside elastic scalability. Experimental evaluation demonstrates substantial reduction in governance configuration time and validates strong adaptability in finance and government sectors—two representative highly compliant domains. The architecture supports agile delivery and automated compliance auditing, thereby filling a critical academic gap in generic CNA governance frameworks.

This study addresses the problem of Kubernetes infrastructure drift, where runtime states deviate from architectural intent, by proposing an editable living architecture model. This model explicitly maps runtime facts to architectural designs, supports bidirectional synchronization between textual and graphical views, and enables non-intrusive Architecture-as-Code management through periodic consistency checks. The proposed approach is implemented using a subset of the Archer KDL, a VS Code-based prototype tool, and snapshot restoration techniques. Experimental evaluations conducted on three representative applications validate the feasibility of the method, demonstrating strong performance in both snapshot restoration accuracy and inconsistency detection recall.

This study addresses the infrastructure complexity of cloud-edge-end协同 architectures, which has emerged as a major bottleneck hindering developer productivity and innovation. Through 101 semi-structured interviews across 86 organizations, this work empirically identifies deployment complexity and onboarding difficulty as core challenges. It proposes four architectural directions to mitigate these issues: Object-as-a-Service (unified object abstraction), internal developer platforms, declarative AI/ML pipelines, and lightweight edge runtimes. Findings indicate that high-level abstractions and automation significantly enhance developer experience—outweighing the impact of execution performance optimizations—and thereby establish a new paradigm for platform engineering and distributed system design.

While large language models (LLMs) can generate executable multi-service application environments, they often deviate from the architectural and security requirements essential for production deployment. This work proposes a method to automatically generate Dockerfiles and Docker Compose configurations solely from code repositories, evaluating deployment fidelity through end-to-end HTTP testing and structural comparison. It explicitly distinguishes between functional correctness and fidelity to deployment intent, deriving a minimal set of explicit deployment specifications that cannot be inferred automatically from source code alone. Experiments successfully reproduce the topology and dependencies of three heterogeneous multi-service systems, confirming functional feasibility; however, critical production-grade features—such as network isolation and multi-stage builds—are consistently absent, revealing fundamental limitations in current LLMs’ ability to model deployment intent.

This study addresses the limitations of traditional cloud sovereignty, which relies on geographic location and struggles to manage governance challenges arising from geopolitical tensions, legal uncertainties, and expanding service boundaries. The authors propose Sovereign 2.0, a novel model that redefines sovereignty as evidence-based control rather than physical infrastructure placement. This framework establishes a three-layer control structure—governance, operational, and technical—integrating post-quantum-ready cryptographic mechanisms such as TLS and key escrow. It enables enforceable service governance across federated environments through governance authority, privileged access management, data lifecycle controls, observability, and incident response. The model introduces a pioneering three-tier risk assurance system covering both steady-state and crisis scenarios, delivering verifiable sovereignty throughout the cloud service lifecycle and significantly enhancing system resilience and recoverability, with profound implications for cloud architecture design, procurement strategies, and security governance.

Current DevOps infrastructures for blockchain applications are predominantly controlled by single entities, lacking decentralized deployment and governance mechanisms. This work proposes a decentralized deployment architecture decoupled from specific governance and upgrade schemes, integrating DAO-based governance, smart contract upgradability, and DevOps best practices. By adopting an extended registry pattern, the architecture enables deterministic deployments and, for the first time, incorporates version control, testing and validation, and user interface components into a unified decentralized framework. The project provides an open-source reference implementation that substantially lowers the barrier to practical decentralized deployment. Experimental evaluation demonstrates the effectiveness and practicality of the proposed architecture.