Proposing a Comprehensive Method for Extracting Monitoring Indicators for Cloud Service Layers

With the rapid expansion of cloud services within organizations, effective monitoring and oversight of performance, security, and availability have become crucial. This paper begins with an analysis of various methods for extracting cloud service monitoring indicators, focusing on the requirements and metrics essential for a Cloud Services Monitoring Center. We review and compare different techniques for extracting Key Performance Indicators (KPIs) across cloud services, highlighting the strengths, challenges, and specific applications of each method. Based on this evaluation, we propose a hybrid approach for extracting monitoring indicators tailored to different cloud service layers, aiming to establish a robust Cloud Services Monitoring Center. For the Infrastructure as a Service (IaaS) layer, we recommend methods such as network traffic analysis, log monitoring, and telemetry. For the Platform as a Service (PaaS) layer, we suggest API-based, event-based, and AIdriven methods. For the Software as a Service (SaaS) layer, we identify agent-based and container-based approaches. This hybrid framework is designed to address specific needs, leverage available resources, and meet operational objectives effectively. Keywords- Monitoring, Key Performance Indicators (KPIs), Cloud Service, Hierarchical model.