Zero-touch DevOps: A GenAI-orchestrated SDLC automation framework

The rapid evolution of software delivery pipelines has increased both the velocity of deployments and the complexity of maintaining reliability and compliance. While traditional DevOps practices emphasize automation and collaboration, they remain constrained by human intervention in key phases of the Software Development Life Cycle (SDLC), including pipeline orchestration, compliance verification, and incident remediation. This paper introduces a Zero-Touch DevOps framework, enabled by Generative Artificial Intelligence (GenAI), to achieve fully autonomous SDLC orchestration for large-scale, high-performance systems.
·        The proposed framework integrates GenAI agents into DevOps workflows, serving as intelligent orchestrators that:
·        Predict and prevent failures through anomaly detection and defect prediction.
·        Enable self-healing pipelines by autonomously rolling back unstable releases, repairing configurations, and scaling resources.
·        Ensure continuous compliance by translating regulatory requirements into executable policies.
·        Optimize throughput and latency through dynamic pipeline tuning.
Validation was conducted in a FinTech microservices ecosystem handling millions of daily transactions. Experimental results demonstrated a 72% reduction in deployment failures, a 45% improvement in Mean Time to Detection (MTTD), and a 50% reduction in Mean Time to Remediation (MTTR) compared to conventional DevOps pipelines. In addition, compliance pass rates improved from 78% to 100%, eliminating audit penalties.
This research contributes: (a) a novel GenAI-Orchestrated SDLC automation model, (b) a maturity roadmap for zero-touch adoption, and (c) empirical validation in a mission-critical domain. The findings suggest that Zero-Touch DevOps is not only feasible but essential for achieving resilient, adaptive, and fully autonomous delivery pipelines.