• Aravind Chinnaraju

The next generation of live‑service games must reconcile two seemingly incompatible goals: millisecond‑level responsiveness and rapidly escalating demands for sophisticated artificial intelligence. This article presents a holistic, theory‑driven blueprint; Cloud‑Native MLOps Architectures for Scalable, AI‑Ready Game Development that unifies cloud elasticity, machine‑learning operations, and game‑specific design principles into a single coherent framework. The blueprint begins with the Elastic Cloud Infrastructure Model for Games (ECIM‑G), which extends classical elasticity by integrating latency‑aware routing and adaptive GPU/FPGA resource blending. Building on this foundation, the AI‑First Micro‑services Architecture (AFMA) and the Unified Game & Model Pipeline (UGMP) weave inference side‑cars, model service meshes, and version‑locked rollbacks directly into standard DevOps practice, ensuring that code, assets, and models evolve in tandem. A Game‑Centric Cloud‑Native AI Stack then introduces a low‑latency feature store and deterministic simulation sandbox, enabling continuous offline–online reinforcement cycles while preserving data provenance and auditability. To manage diverse performance and sustainability constraints, the framework layers a Cloud‑Edge Collaborative AI Layer (CECAL) for dynamic model placement, a Quantum‑Inspired Burst Scheduler (Q‑Burst) for opportunistic acceleration of compute‑intensive tasks, and a Cross‑Cloud Orchestrator for Games (CCOG) that balances carbon awareness with throughput. Collectively, these components illustrate how MLOps centric design can transform game production pipelines, minimize operational risk, and future‑proof studios against evolving technological and regulatory landscapes. The article closes by outlining open research directions in carbon‑aware orchestration, foundation‑model fine‑tuning, and standardized evaluation metrics positioning MLOps as the critical enabler of scalable, AI‑driven game experiences.

Cloud‑Native Architecture, MLOps, Game Development, Live‑Service Games, Elastic Infrastructure, Micro‑services, Model Serving, Edge Computing, Latency Optimization, Generative AI, Reinforcement Learning, Feature Store, CI/CD Pipelines, Cross‑Cloud Orchestration, GPU Spot Instances, Quantum Acceleration, Carbon‑Aware Scheduling, Data Provenance, Simulation Sandbox, Sustainable Computing

"CLOUD‑NATIVE ARCHITECTURES FOR GENERATIVE AI‑READY, SCALABLE GAME DEVELOPMENT: AN MLOPS‑DRIVEN BLUEPRINT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.g796-g820, November-2024, Available :http://www.jetir.org/papers/JETIR2411684.pdf

"CLOUD‑NATIVE ARCHITECTURES FOR GENERATIVE AI‑READY, SCALABLE GAME DEVELOPMENT: AN MLOPS‑DRIVEN BLUEPRINT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. ppg796-g820, November-2024, Available at : http://www.jetir.org/papers/JETIR2411684.pdf