Artificial intelligence enabled system and method for real-time cloud resource monitoring and visualization

A system for real-time cloud resource monitoring and visualization, comprising:

• a computing device comprising a processor for executing instructions from a cloud resource visualization module located within the computing device, wherein the cloud resource visualization module is configured to display real-time visualizations of cloud resources, including operational states, interdependencies, and relationships, wherein the computing device communicatively connected with a cloud server over a network;
• the cloud server comprises an operational twin engine for executing instructions from a cloud resource processing module, whereby the cloud resource processing module configured to aggregate data from a plurality of sources, including infrastructure-as-Code (IaC) tools, cloud provider application programming interfaces (APIs), logs and event records, security frameworks and compliance systems, cost management tools, wherein the cloud resource processing module configured to process the aggregated data using advanced artificial intelligence (AI) techniques, including Graph Neural Networks (GNNs) for predictive analytics, relationship mapping, and attack path analysis;
• Generative AI for real-time optimization of resource allocation, compliance adherence, and cost forecasting;
• the cloud resource processing module generates a real-time operational twin of the cloud ecosystem with visual representations of cloud resource relationships, performance metrics, compliance statuses, security vulnerabilities, dynamic updates of changes in the cloud environment, including new deployments, configuration changes, and detected issues, whereby the cloud resource processing module transmits the generated real-time operational twin of the cloud ecosystem to the computing device over the network;
• and
• the cloud resource visualization module on the computing device configured to provide real-time, interactive visualizations of the operational twin, including overlays for compliance, security, and cost metrics, and presents AI-driven insights and recommendations for proactive decision-making, such as security remediation, resource optimization, and compliance corrections, wherein the cloud resource visualization module configured to enable the user to interact with visual elements, including modifying configurations, initiating remediation workflows, and generating compliance reports.