Distributed systems have evolved into the foundational infrastructure supporting modern digital services, enabling cloud-native applications, microservices-based architectures, big data platforms, and globally distributed enterprise ecosystems. By leveraging geographically dispersed computing resources, distributed systems provide scalability, high availability, and fault tolerance. However, as system scale and architectural complexity increase, operational management becomes significantly more challenging. Organizations must address issues related to dynamic resource provisioning, configuration consistency, dependency management, automated scaling, continuous updates, and security enforcement across heterogeneous environments. Traditional manual administration approaches are insufficient for handling such complexity, often leading to configuration drift, deployment failures, environment inconsistencies, and increased operational risk. To overcome these limitations, automation-driven paradigms such as Infrastructure-as-Code (IaC) and Continuous Integration/Continuous Deployment (CI/CD) have emerged as essential components of modern distributed system management. Infrastructure-as-Code transforms infrastructure provisioning and configuration into machine-readable, version-controlled definitions, enabling reproducibility, consistency, and rapid environment replication. Simultaneously, CI/CD frameworks automate application build, testing, validation, and deployment processes, ensuring continuous delivery of reliable software updates across distributed architectures. The integration of IaC and CI/CD establishes a unified automation pipeline in which infrastructure and application lifecycles are managed cohesively, promoting operational efficiency, traceability, and resilience. This review comprehensively examines the conceptual foundations, architectural frameworks, and practical implementations of integrating IaC with CI/CD for distributed system automation. It analyzes declarative and imperative infrastructure models, automated deployment strategies, immutable infrastructure principles, and cloud-native orchestration practices. Furthermore, the paper evaluates the operational benefits of automation—including scalability optimization, reduced configuration drift, accelerated recovery, enhanced collaboration, and improved compliance management—while critically assessing associated challenges such as state management complexity, security vulnerabilities in automation scripts, pipeline debugging difficulties, and cost governance concerns. In addition, emerging paradigms such as GitOps, policy-as-code, DevSecOps, AI-driven pipeline optimization, and self-healing infrastructure mechanisms are discussed to highlight the ongoing evolution toward intelligent and autonomous system management. By synthesizing current practices and research directions, this review provides a structured perspective on how integrated automation frameworks enhance reliability, scalability, and security in distributed environments, while outlining future research opportunities aimed at achieving more adaptive, predictive, and cost-efficient distributed system operations.