The Future of DevOps: Converging AI Engineering, Platform Engineering, and Observability for Hyper-Automated Delivery
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V6I2P112Keywords:
DevOps, AI Engineering, Platform Engineering, Observability, Hyper-Automation, CI/CD, Internal Developer Platforms, Autonomous Systems, DevOps PipelinesAbstract
DevOps is experiencing a revolutionary change as the intersection of AI engineering, platform engineering, and next-level observability takes place. Traditional DevOps practices are not enough to deliver digital at the scale, speed, and reliability required as the digital delivery cycles become more complex and faster. This paper discusses the direction the future of DevOps is heading towards, with a particular focus on the rise of hyper-automated delivery pipelines driven by machine learning, Internal Developer Platforms (IDPs), and real-time observability. When AI is integrated into CI/CD patterns, it makes it possible to automate release verification, predictive troubleshooting, and auto-scaling. By designing golden paths and self-service workflows, platform engineering can provide better developer experience governance and consistency at the same time. In the meantime, observability is transforming passive monitoring into an active layer of decision-making that drives intelligent automation. The paper also looks at the architecture and cultural changes needed to enable this convergence and the various challenges, including toolchain fragmentation and data silos, AI trust, and explainability. The new paradigms of digital twins, edge computing, and human-in-the-loop systems are mentioned as the facilitators of robust and dynamic DevOps ecosystems. Practical implementations such as the Dynatrace platform demonstrate how these synergies are already being used by enterprises to achieve performance, reliability and speed. In the end, the overlap of these areas is not only the technological change but the reinvention of software construction and operation as we enter the era of intelligent automation
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