> ## Documentation Index
> Fetch the complete documentation index at: https://docs.jacobpevans.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Drive reliability

> Population failure statistics for reasoning about disk risk, and the rule that drive records state measurements rather than predictions.

Base rates for reasoning about HDD risk, and the recording standard that
depends on them. The purpose of this page is to replace adjectives with
numbers.

## The rule

**No drive record calls a disk "dying," "worn," "end-of-life," or "on
borrowed time."** Those are predictions written as observations. Record the
measured values, cite a base rate from this page, and let the reader do the
arithmetic.

This is not stylistic. Age-based intuition about disk risk is often wrong —
the data below show failure rates that don't track age the way most people
expect.

## Source data

[Backblaze Drive Stats Q1 2026](https://www.backblaze.com/blog/backblaze-drive-stats-for-q1-2026/)
— 341,263 drives, 30,203,180 drive-days in the quarter, 529,968,464 lifetime.

| Metric                          | Value                          |
| ------------------------------- | ------------------------------ |
| Quarterly AFR (all drives)      | **1.24%**                      |
| Lifetime AFR (all drives)       | **1.39%**                      |
| AFR, >20 TB pool (young drives) | 0.85%                          |
| 2024 AFR, for trend             | 1.57%, down from 1.70% in 2023 |

AFR (annualized failure rate) is the share of drives expected to fail over a
year of continuous service.

## Failure vs. age

The finding that matters most, from
[Are Hard Drives Getting Better? Let's Revisit the Bathtub Curve](https://www.backblaze.com/blog/are-hard-drives-getting-better-lets-revisit-the-bathtub-curve/):

| Cohort      | Failure-rate peak | At age        |
| ----------- | ----------------- | ------------- |
| 2013 drives | 13.73%            | **3 yr 3 mo** |
| 2021 drives | 14.24%            | **7 yr 9 mo** |

The age at which the failure rate spikes moved **later by roughly two years**
between those cohorts. Backblaze's own conclusion is that the classic bathtub
curve no longer describes their population: "the neat story of early
failures, calm middle age, and gentle decline no longer fits the world our
drives inhabit."

**Consequence.** A 6–7.5 year old drive is not self-evidently near failure. It
sits inside the band where a modern cohort still shows a low per-drive AFR, at
or before the age where the 2021 cohort's rate peaked. Age alone is not a
defect and is not recorded as one.

## What actually predicts failure

Backblaze and Google independently identified a small set of SMART attributes
that correlate with impending failure. Backblaze uses five, chosen because
they are consistent across manufacturers:

| ID  | Attribute                          |
| --- | ---------------------------------- |
| 5   | Reallocated Sectors Count          |
| 187 | Reported Uncorrectable Errors      |
| 188 | Command Timeout                    |
| 197 | Current Pending Sector Count       |
| 198 | Offline Uncorrectable Sector Count |

Google's analysis found 5, 187, 197, and 198 consistently correlated, and
reported that after a drive's **first** scan error — SMART 187 going
non-zero — it is **39× more likely to fail within 60 days** than a drive with
none.

Two limits, because they change how strongly these may be cited:

* Both analyses are **univariate**, one attribute at a time. They establish
  correlation, not a calibrated per-drive probability.
* **Not every model implements every attribute.** A missing attribute is not a
  reading of zero. Where one is absent, say so and substitute the evidence
  that does exist — normally a completed extended self-test.

## Recording standard

1. **Record measurements, not prognosis.** Power-on hours, the five
   predictive attributes, self-test outcomes with their LifeTime hour,
   temperature.
2. **Read self-test results from `smartctl -l selftest`**, never the `-c`
   summary. `-c` reports "completed without error" even when no test has run;
   confirm the LifeTime hour advanced.
3. **State absence explicitly.** "Attribute 197 not implemented on this
   model" — never silently imply zero.
4. **Cite a base rate rather than an adjective.** Record the measured
   pattern — power-on hours, each predictive attribute's value, the self-test
   result — instead of a subjective label. A full attribute readout is
   checkable; "high-hours refurb nearing end of life" is not.
5. **Redundancy is the control, not drive selection.** A non-zero population
   AFR means any drive can fail at any age — that's what in-pool redundancy
   and off-site copies absorb, not preemptive replacement. See
   [ZFS backup and replication](/infrastructure/zfs-backup-replication) for
   how those layers combine.

## Worked examples (not published data)

The statistics above are population-level base rates from Backblaze and
Google. Applying the recording standard to one drive is a different
exercise. The two cases below are **invented to illustrate the reasoning** —
they are not measurements, and not part of either dataset.

**Example — keep in service.** A drive several years into service reads
zero on every predictive attribute it implements, and completes a full
extended self-test without error. Nothing measured on it indicates a
defect, regardless of its age.

**Example — pull from the pool.** A drive that accumulates Current Pending
Sectors — even with Reallocated Sectors and Offline Uncorrectable Sectors
still at zero — has crossed one of the five predictive attributes. That's
evidence-backed grounds to remove a disk from a pool that can't absorb
another failure, independent of the drive's age.

In this second example, a non-zero pending-sector count raises failure
probability materially, but it doesn't mean the drive has failed: zero
reallocated and zero offline-uncorrectable sectors means the platters
haven't lost data. Retest a pulled drive standalone before any disposal
decision.

**Correlated age is a pool property, not a drive property.** Disks bought and
deployed together tend to fail less independently than the base rate
assumes — which matters most during a rebuild, when the surviving disks take
their heaviest read load. That's an argument for rebuild-window planning and
verified restores, not for treating any individual disk as suspect.