The rapid evolution of cloud computing, distributed systems, and software-defined networking (SDN) has fundamentally reshaped how modern enterprises design, deploy, and manage digital infrastructure. The transition from monolithic, on-premises environments to cloud-native architectures, microservices-based applications, and virtualized networking frameworks has significantly increased scalability, flexibility, and innovation velocity. However, this technological advancement has also introduced substantial operational complexity. Traditional siloed operational models—where cloud operations, application development, and network engineering teams function independently—are increasingly inadequate for managing highly dynamic, distributed, and interconnected ecosystems. In conventional IT environments, infrastructure provisioning, application deployment, and network configuration were handled as separate processes with distinct tools, workflows, and performance metrics. This fragmentation often resulted in delayed deployments, inconsistent policy enforcement, limited cross-layer visibility, and heightened vulnerability to outages or security breaches. As organizations adopt multi-cloud strategies, container orchestration platforms, and API-driven networking, the lack of integration between operational domains becomes a critical bottleneck to agility and resilience.Integrated DevOps practices address these limitations by unifying cloud, application, and network operations under a shared framework of automation, Infrastructure as Code (IaC), Continuous Integration/Continuous Deployment (CI/CD), and end-to-end observability. Rather than focusing solely on collaboration between development and operations teams, integrated DevOps extends its principles across the entire technology stack. This approach promotes shared ownership, policy-driven governance, and cross-functional accountability, enabling organizations to manage infrastructure, code, and connectivity as programmable, version-controlled assets. Automation plays a central role in this integration. Through declarative configurations and orchestration pipelines, provisioning and deployment processes become reproducible and scalable. Advanced observability frameworks—encompassing metrics, distributed tracing, and log aggregation—provide real-time visibility into system behavior across infrastructure, application, and network layers. Additionally, embedded DevSecOps practices ensure that security controls, compliance requirements, and vulnerability assessments are integrated directly into development and operational workflows. This review comprehensively examines the conceptual foundations, enabling technologies, and architectural patterns underpinning integrated DevOps for cloud, application, and network operations. It analyzes key methodologies such as GitOps, which leverages version control systems as the single source of truth; NetDevOps, which introduces automation and programmability into networking; and AIOps, which applies machine learning to operational data for predictive analytics and automated remediation. Furthermore, the review explores implementation challenges, including cultural resistance, toolchain complexity, governance concerns in multi-cloud environments, and skill gaps in cross-domain expertise. By synthesizing current practices and emerging innovations, this study highlights how integrated DevOps serves as a strategic enabler of operational resilience, scalable infrastructure management, and continuous digital transformation.