Observability in software systems, especially those utilizing microservices, involves understanding the system's behavior through three key pillars: logs, metrics, and traces. Logs provide detailed, timestamped records of events, which are essential for diagnosing specific issues but can be costly due to storage requirements. Metrics offer numerical data on system performance, facilitating quick assessments and alerting through graphical representations, yet they require careful selection and labeling to be effective. Traces allow tracking the lifecycle of data across distributed systems, helping identify bottlenecks, though they are complex to implement across diverse coding environments. Combining these pillars enhances DevOps teams' ability to proactively and reactively maintain system health, reduce problem resolution time, and leverage machine learning tools for detecting anomalies. Employing all three pillars together provides a comprehensive insight into system functionality, enabling efficient troubleshooting and system optimization.