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ChuckBuildsandClaude Opus 5
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Plugin metrics were persisted to the cache inside monitor_call, so every call by every plugin rewrote a small JSON file. Measured on a running rig: one plugin's plugin_metrics file changed nine times a minute, with fourteen such files active. Each is around 350 bytes, which on ext4 costs a 4KB block plus a journal entry, so the cost is dominated by the write itself rather than the payload. Cache writes accounted for essentially all of that device's 2.4 MB/min of SD traffic, on a card that wears out and has already failed twice on the other rig. Metrics cannot be de-duplicated the way health state can, because call_count changes on every call and the timings usually do too. So they are rate-limited instead: at most one write per plugin per 30 seconds. The in-memory copy stays authoritative and exact -- a plugin's call_count is still precise the instant after it runs. Only the cross-process snapshot the web UI reads is delayed, and telemetry up to half a minute old is still a fair description of a long-running plugin. reset_metrics clears the throttle timestamp, so a reset is not left showing a deleted key for the rest of the interval. Extrapolating the sampled rate, this takes metric writes from roughly 126 a minute to 28. Health persistence, the other half of the churn, is handled separately in #475. Verified by reverting the throttle: the churn test then reports 50 writes for 50 calls. 88 tests pass across resource monitor, plugin system and web API. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01STMbQE4YctTacQXfbYqKuW