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Observability Explained: How Logs, Metrics and Traces Keep Distributed Systems Healthy

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Observability refers to the ability to understand a system's internal state by analyzing the signals it produces, making it essential for diagnosing issues in complex distributed architectures. The concept rests on three core pillars: logs, which record discrete events with contextual detail; metrics, which track numerical measurements like error rates and latency over time; and distributed traces, which follow a single request across multiple services. Logs help engineers pinpoint what failed and when, while metrics reveal broader performance trends and anomalies across the system. Distributed tracing assigns a unique trace ID to each request, breaking it into spans per service so engineers can identify exactly where slowdowns or failures occur. Together, these three signals give engineering teams a structured path from detecting a problem to finding its root cause without manual reproduction.

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Observability Explained: How Logs, Metrics and Traces Keep Distributed Systems Healthy · ShortSingh