Multi‐Cloud Load Balancing with Application Performance Monitoring (APM) and Chaos Engineering Practices

This chapter explores holistic solutions to multicloud load balancing as part of holistic Application Performance Monitoring and intentional chaos engineering to improve system reliability and predictability of performance. It focuses on improving rapid decision-making and service efficiency during critical situations by leveraging cloud-based computational support. The chapter highlights the significance of machine learning-assisted mobile cloud infrastructures for supporting real-time emergency management and disaster response applications. It confirms that a system of multi-clouds can be designed to be economically viable in guaranteeing enterprise-tiered reliability and performance features and load balancing, observability and chaos engineering causal behavior. The chaos engineering was structured and carried out based on the established frameworks. The baseline round-robin strategy serves as the control condition, while latency-aware and health-aware approaches demonstrate progressive optimization.