Platform Observability Is Broad but Still Too Shallow
Platform Engineering, Tuesday, September 22nd, 2026
Wide telemetry coverage doesn't equal useful observability; platform teams need shared conventions and AI-aware metrics.
The article argues that having telemetry everywhere doesn't guarantee useful observability, quoting Honeycomb's Liz Fong-Jones: 'You can have telemetry everywhere and still not have useful observability.'
Budget constraints often force teams to reduce data fidelity, shorten retention, or focus monitoring on critical services, especially as AI workloads increase data volume. Platform teams should embed OpenTelemetry into golden paths and standardize service names, ownership, and business context.
Observability must also expand to cover AI-specific signals like token consumption, inference latency, hallucinations, and guardrail failures, with success measured by whether engineers can resolve incidents independently.