# Observability: Are You Measuring What Actually Matters?

DevFeed: [Observability: Are You Measuring What Actually Matters?](<https://devfeed.tech/articles/observability-are-you-measuring-what-actually-matters-77921.md>)

Original publisher: [Read original article](<https://www.honeycomb.io/blog/observability-are-you-measuring-what-matters>)

Author: Colin Burke

Published: 2026-06-15T13:00:00Z

Content type: article

Language: en

Sources: [Honeycomb Blog](<https://devfeed.tech/sources/honeycomb-blog.md>)

Topics: [observability](<https://devfeed.tech/topics/observability.md>), [ai observability](<https://devfeed.tech/topics/ai-observability.md>), [engineering-leadership](<https://devfeed.tech/topics/engineering-leadership.md>), [product-experimentation](<https://devfeed.tech/topics/product-experimentation.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-llms](<https://devfeed.tech/tags/ai-llms.md>), [measuring](<https://devfeed.tech/tags/measuring.md>), [metrics](<https://devfeed.tech/tags/metrics.md>), [observability](<https://devfeed.tech/tags/observability.md>)

## AI overview

Traditional observability measures such as uptime and MTTR show operational performance but do not establish business value. The article argues that teams should connect telemetry to customer experience, product outcomes, costs, and governance, especially for complex and AI-driven systems. It recommends baselining measures and relating them to outcomes stakeholders can evaluate.

## Source excerpt

Old observability metrics like uptime and MTTR aren't enough anymore. Teams must connect technical signals to business outcomes, especially as AI raises the stakes.