Topic starter
19/08/2026 4:06 pm
TL;DR: Only 13% of collected telemetry is used, while 84% of companies consume less than a quarter of what they ingest and average annual observability spend reaches $905,000, according to Sawmills’ 2025 State of Observability and Telemetry Report. The governance problem is no longer visibility alone, but how to control telemetry volume, quality, and cost without blinding incident response.
Editorial analysis by NHI Mgmt Group, based on content published by Sawmills: “Sawmills Releases 2025 State of Observability & Telemetry Report”.
By the numbers:
- Only 13% of collected telemetry is used.
- 86% of companies run two or more observability platforms.
Key questions
Q: What breaks when observability teams collect everything?
A: Collecting everything turns observability into a storage and search problem, not a diagnostic one.
Q: Why do fragmented telemetry sources slow down incident response?
A: Because no single source tells the full story.
Q: What are the signs that observability data is no longer useful?
A: Common signs include large volumes of unused telemetry, rising ingestion and storage costs, duplicated platforms, and repeated complaints that dashboards are crowded but incidents still take too long to diagnose.
Practitioner guidance
- Audit telemetry value by source and use case Map logs, traces, and metrics to the incidents and workflows they actually support, then remove or sample data that has no clear operational consumer.
- Set retention and routing policies for high-volume signals Apply explicit rules for duplicate logs, high-cardinality metrics, and low-value debug output so expensive data does not flow into long-term storage by default.
- Create ownership for telemetry pipelines Assign a team to govern ingestion, enrichment, and discard rules so observability sprawl is managed as a lifecycle problem rather than a platform setting.
Bottom line: Most observability environments now contain a large amount of low-value data that adds cost without improving troubleshooting outcomes.
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19/08/2026 4:39 pm
Telemetry waste has become an operational governance failure, not a tooling inconvenience. When most collected data is never used, observability stops serving incident response and starts taxing it. The real issue is that teams often optimise for collection capacity while neglecting signal quality, ownership, and retention policy. Practitioners should treat telemetry governance as a control plane for operational reliability.
A question worth separating out:
Q: How should teams reduce observability costs without losing useful telemetry?
A: Start at the pipeline, not the backend. Filter obvious noise, remove high-cardinality fields, and tail-sample traces so routine traffic is reduced after full context is available. That preserves error and latency signal while cutting ingest, storage, and query costs before they become locked into the observability bill.
👉 Read our full editorial: Observability data waste is raising costs and slowing incident response