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Case Study #33 — Top 100 Software Failures

Amazon S3 outage

A roughly 4-hour outage of AWS's S3 storage service in its US-East-1 region disrupted thousands of websites and apps, with estimated losses to S&P 500 companies alone of over $150 million.

2017-02-28
When it happened
Cloud / Technology
Sector
#33 of 100
Ranked by documented impact
01 — What Happened

The damage was public. The root cause was preventable.

A roughly 4-hour outage of AWS's S3 storage service in its US-East-1 region disrupted thousands of websites and apps, with estimated losses to S&P 500 companies alone of over $150 million.

Cloud
Sector affected
2017-02-28
Date of the event
#33
Rank in the Top 100 Software Failures
1
Distinct root-cause clause identified below
02 — The Root Cause

What the software actually got wrong

An engineer running an authorized debugging command to remove a small number of servers used a typo'd input that removed far more capacity than intended, taking two critical subsystems offline and requiring a lengthy full restart.

01Root Cause

An engineer running an authorized debugging command to remove...

What Happened

An engineer running an authorized debugging command to remove a small number of servers used a typo'd input that removed far more capacity than intended, taking two critical subsystems offline and requiring a lengthy full restart.

How Requs AI Catches This

Requs AI Edge Case flags this exact pattern at the requirements and architecture stage — before a single line of code implementing it exists — so the assumption behind it gets challenged while it is still cheap to fix.

03 — How This Gets Caught Before It Happens

Beyond code coverage and "shall" testing

Root causes like this one rarely show up in code coverage or requirements-compliance testing, because nobody wrote a requirement anticipating the specific edge case that broke. Requs AI Edge Case and Requs AI Software FMEA are built to surface exactly this class of overlooked failure mode — before the software is written.

Requs AI Edge Case

Surfaces this before code exists

Identifies edge cases like this one at requirements and architecture time, using the Common Defect Enumeration to catalog failure patterns seen across hundreds of real-world software failures — including this one.

Requs AI Software FMEA

Connects the failure mode to the hazard

Traces this class of root cause directly to the system-level hazard it can produce, so a defect pattern like this one gets flagged during design review instead of after it ships.

Find the overlooked root causes before they ship.

Schedule a demonstration, or explore how Requs AI Edge Case and Software FMEA use the Common Defect Enumeration.