What best describes Observability Monitoring?

• A. Metrics (Errors) - Logs (Measures) - Diagnostics Trace
• B. Only monitor CPU usage
• C. Focus exclusively on network bandwidth
• D. Provide real-time social media analytics

Answer: (A)

Observability monitoring relies on collecting and correlating multiple data types to understand how a system behaves and to diagnose issues. The best description includes three primary data sources: metrics, logs, and traces. Metrics provide time-series numbers such as error rates, request counts, and latency, giving you a high-level view of performance. Logs store detailed events and messages that explain what happened at specific moments, adding context for incidents. Traces map the journey of a single request through a distributed system, revealing where bottlenecks or failures occur across services. Together, these signals give a complete picture, enabling proactive monitoring and rapid troubleshooting. The other options are too narrow: monitoring only CPU usage misses many important signals; focusing solely on network bandwidth ignores application behavior; and real-time social media analytics has no relevance to system observability.