Microservice-based architectures enhance flexibility, autonomy, and velocity but increase system complexity, necessitating continuous service performance observation to ensure business success. Service-level objectives (SLOs) are crucial for setting and measuring service-quality targets, utilizing service-level indicators (SLIs) to track performance in relation to service-level agreements (SLAs). According to the Google Site Reliability Engineering handbook, monitoring latency, traffic, errors, and saturation—the four golden signals—is essential for delivering high-performing software by using SLOs to track business success. Creating SLOs involves selecting appropriate SLIs and employing complex metric expressions to evaluate service quality, focusing on availability, reliability, and performance, with latency being a key measure of response times. Tools like Dynatrace offer templates and a wizard for simplifying SLO creation, which involves defining metrics and using operators like partition and default to accurately calculate performance ratios. The partition operator divides time series into good and bad timeslots, while the default operator addresses data gaps. Increasing the precision of SLOs can be achieved through custom metrics, and the process is supported by alerting capabilities to prevent objective violations.