# Is it over for metrics?

DevFeed: [Is it over for metrics?](<https://devfeed.tech/articles/is-it-over-for-metrics-5349.md>)

Original publisher: [Read original article](<https://clickhouse.com/blog/is-it-over-for-metrics-in-observability>)

Author: Mike Shi

Published: 2026-02-12T15:35:45Z

Content type: article

Language: en

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

Topics: [observability](<https://devfeed.tech/topics/observability.md>), [clickhouse](<https://devfeed.tech/topics/clickhouse.md>), [Monitoring](<https://devfeed.tech/topics/monitoring.md>), [log management](<https://devfeed.tech/topics/log-management.md>), [Traces](<https://devfeed.tech/topics/traces.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [cpu](<https://devfeed.tech/topics/cpu.md>)

Tags: [agents](<https://devfeed.tech/tags/agents.md>), [clickhouse](<https://devfeed.tech/tags/clickhouse.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [dashboards](<https://devfeed.tech/tags/dashboards.md>), [logs](<https://devfeed.tech/tags/logs.md>), [metrics](<https://devfeed.tech/tags/metrics.md>), [monitoring](<https://devfeed.tech/tags/monitoring.md>), [observability](<https://devfeed.tech/tags/observability.md>), [optimization](<https://devfeed.tech/tags/optimization.md>), [prometheus](<https://devfeed.tech/tags/prometheus.md>), [search](<https://devfeed.tech/tags/search.md>), [series](<https://devfeed.tech/tags/series.md>), [statistics](<https://devfeed.tech/tags/statistics.md>), [traces](<https://devfeed.tech/tags/traces.md>)

## AI overview

The article argues that metrics remain useful for quickly assessing known failure modes, but are less effective for investigating unexpected or user-reported problems. As structured event data becomes cheaper to aggregate in columnar databases such as ClickHouse, metrics may shift from the primary observability interface to an optimization layer over richer logs, traces, and events.

## Source excerpt

Is it over for metrics in modern observability? As high-cardinality events and fast columnar rollups reshape how engineers investigate production issues, metrics may be shifting from the center of the stack to a simple optimization layer over richer data.