Developer and operational teams often overlook application monitoring due to factors such as deadlines and company culture, leading to inadequate monitoring practices. Automating monitoring processes can alleviate this issue by reducing costs, minimizing manual interventions, and enhancing problem-solving efficiency, particularly important in complex microservices architectures. Best practices for automating monitoring include designing applications with integrated monitoring frameworks, classifying resources for better analysis, and adding monitoring tools even to legacy systems. Utilizing containers and cluster orchestrators like Kubernetes further simplifies infrastructure management and ensures consistent monitoring across varied platforms. Such automation is crucial for anticipating outages and maintaining high-level monitoring capabilities in dynamic, distributed environments.