Wilfried Roset, an engineering manager and Grafana Champion, emphasizes the importance of applying Service Level Objectives (SLOs) to databases using synthetic monitoring to enhance user experience and operational efficiency. SLOs, which are quantifiable targets for IT service performance and reliability, were introduced by Google and help maintain service quality by encompassing metrics like uptime, response times, and error rates. By viewing databases as APIs similar to HTTP services, SLOs can be effectively applied to databases, focusing on error rates and response times to improve service delivery. Real-traffic sampling and synthetic monitoring are two methods for implementing SLOs, with synthetic monitoring offering more control and independence from client-side metrics. Tools like sql_exporter and Grafana Mimir are highlighted for their roles in monitoring and tracking SLOs. Roset shares a success story where synthetic monitoring detected a network issue affecting database performance, underscoring the practicality and efficiency of SLOs in maintaining high-quality database services.