Modern software systems generate vast telemetry data, yet monitoring this data can become surprisingly expensive. Observability cost refers to the financial and operational overhead of collecting, storing, and analyzing logs, metrics, and traces. Managing this expense involves balancing data granularity with budget limits, often through sampling and retention policies. Engineering leaders, DevOps teams, and FinOps practitioners benefit most by optimizing performance without breaking the bank.
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