Cloud Native

Cloud native computing focuses on building and deploying applications as microservices, leveraging containerization and orchestration technologies like Kubernetes to achieve scalability, resilience, and efficient resource utilization. Current research emphasizes optimizing resource allocation within these environments, employing machine learning models such as Temporal Fusion Transformers, DeepAR networks, and LSTM-GNNs to predict resource needs and proactively manage scaling, power consumption, and cold starts. This approach is significantly impacting various fields, from telecommunications (O-RAN) and robotics (RoboKube) to AI model deployment (LMaaS), improving efficiency, reducing costs, and enabling the deployment of complex applications at scale.