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Author SHA1 Message Date
Claude
d84cf8c2b6
Fase 2: baselines and anomaly detection
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Baselines per hour of the week (with neighbouring hours) from four weeks
of hourly aggregates, computed in C# (independent of DATEFIRST) and
refreshed by the agent each hour. SQLI-ANOM-001 compares current load
with what is normal at this time: CPU far above normal, batch requests
far above or collapsed (application down?), page life expectancy
collapse. Not measurable until enough history exists.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01E3EExwndy8Z22EK2Qpt6BK
2026-09-29 08:01:11 +00:00
Claude
9372c2e927
Fase 1: local repository with finding tracking, time series and retention
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- Versioned, embedded migrations serialized with sp_getapplock so the agent
  and web UI can both migrate at startup
- Findings tracked per rule and subject: first seen, last seen, resolved;
  a rule that could not run never resolves its findings
- Time series (waits, file I/O, CPU, counters), blocking chains and
  deadlock graphs; idempotent inserts (timestamps truncated to match
  datetime2(0)), hourly aggregation and batched retention deletes
- Read API for the web UI; integration tests against SQL Server

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01E3EExwndy8Z22EK2Qpt6BK
2026-09-29 06:23:38 +00:00