# AnalogJ/scrutiny

Hard Drive S.M.A.R.T Monitoring, Historical Trends & Real World Failure Thresholds

Repository: https://github.com/AnalogJ/scrutiny
Canonical: https://ross.abutalabs.com/products/scrutiny
Language: Go
License: MIT
License Family: permissive
Last push: 2026-08-20T18:40:58+00:00

## Health v2 (maintenance only)
Score: 98/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 98, release rhythm 96, longevity 100
- inputs: {"age_days": 2202, "days_push": 13, "days_rel": 25, "gap_med": 1.5, "n_releases_24m": 9}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 8124, forks 296 (observed 2026-08-28T04:10:13.758013+00:00)

## What it is
Scrutiny is a self-hosted web dashboard for hard drive S.M.A.R.T monitoring that integrates with the smartd daemon. It tracks historical S.M.A.R.T attribute trends and applies real-world failure thresholds to predict failing drives before data loss.

## Use cases
- monitor hard drive health on a home server
- get alerts when a disk is about to fail
- view historical S.M.A.R.T attribute trends
- replace smartd's CLI-only output with a web dashboard
- detect degrading drives before data loss
- monitor SMART metrics across many drives

## When to choose
- you run a server or NAS with multiple drives and want a web UI for SMART data
- you need historical trends and failure prediction rather than just pass/fail SMART status
- you want a lightweight self-hosted dashboard that reuses smartd

## When to avoid
- you need RAID-array or filesystem-level monitoring rather than raw drive SMART metrics
- you want a full system monitoring solution covering CPU, memory, and network
- you need Windows or macOS drive health monitoring with first-class support

## Facets
- artifact type: application
- maturity: active
- function: monitoring, alerting, data-visualization, analytics
- domain: monitoring, self-hosted, hardware
- platform: self-hosted, go
- tags: smart, hard-drive-health, smartd, dashboard, disk-monitoring, failure-prediction, devops, linux, docker, web-server

## Member repositories
- AnalogJ/scrutiny (main) score 98

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:13.758013+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:30:37.452390+00:00, confidence not recorded.
  - readme: https://github.com/AnalogJ/scrutiny (fetched 2026-08-28T04:10:13.758013+00:00, sha d17c953a3896)
- Data as of 2026-08-30T08:39:29.467469+00:00.