# The three villains to agentic observability: retention, sampling and rollups

DevFeed: [The three villains to agentic observability: retention, sampling and rollups](<https://devfeed.tech/articles/the-three-villains-to-agentic-observability-retention-sampling-and-rollups-5603.md>)

Original publisher: [Read original article](<https://clickhouse.com/blog/three-villains-agentic-observability>)

Author: Mike Shi

Published: 2026-04-08T14:12:02Z

Content type: article

Language: en

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

Topics: [ai observability](<https://devfeed.tech/topics/ai-observability.md>)

Tags: [agentic](<https://devfeed.tech/tags/agentic.md>), [ai](<https://devfeed.tech/tags/ai.md>), [automated-reasoning](<https://devfeed.tech/tags/automated-reasoning.md>), [cost](<https://devfeed.tech/tags/cost.md>), [logs](<https://devfeed.tech/tags/logs.md>), [metrics](<https://devfeed.tech/tags/metrics.md>), [observability](<https://devfeed.tech/tags/observability.md>), [root-cause-analysis](<https://devfeed.tech/tags/root-cause-analysis.md>), [storage](<https://devfeed.tech/tags/storage.md>), [traces](<https://devfeed.tech/tags/traces.md>)

## AI overview

The article argues that short retention, trace sampling, and metric roll-ups are storage-driven observability compromises that remove the full context needed for AI-assisted anomaly detection, root-cause analysis, and agent-driven reasoning.

## Source excerpt

Retention limits, sampling, and metric roll-ups aren't observability best practices - they're workarounds for storage systems that can't handle full-fidelity data, and they're becoming a hard blocker for AI-driven workflows.