The Observability Tax: A Forensic Audit of How Your Unified Platform Became a Liability
Observability spend is now consuming 20% to 25% of infrastructure budgets. When telemetry bills exceed database and compute costs, logging has ceased to be an operational aid and become an unmonitored tax on gross margin.
Observability was sold to the industry as the panacea for system reliability: instrument every trace, log every request header, emit metrics on every function call, and you will achieve total operational omniscience.
Instead, modern observability has become an unchecked tax on gross margins.
In recent forensic audits of scaling SaaS platforms, we routinely find companies spending 22% to 28% of their entire cloud budget on proprietary telemetry platforms like Datadog, Splunk, or New Relic—often paying more for monitoring than for the actual production databases serving customers.
Why does this happen?
High-cardinality tag explosion. Engineers blindly add user_id, session_id, or request_uuid as tags to custom metrics, causing timeseries databases to multiply metrics into billions of discrete streams.
Furthermore, 95% of ingested debug logs are never queried by a human engineer during an incident.
By implementing high-signal telemetry filtering at the edge, converting raw logs to sampled spans, and storing long-tail audit logs in cheap S3-compatible cold storage, we regularly slash observability bills by 60% while dramatically improving incident resolution speed.
Monk, Author, TEDx Speaker, and Solution Assembler. For 23 years quietly stabilizing platforms, eliminating operational drag, and making broken systems predictable.