AI safety company founded by ex-OpenAI researchers Dario and Daniela Amodei. Builds the Claude family of large language models with a focus on steerability, interpretability, and reducing harmful outputs.
Method: a rolling quarter (13 weeks ≈ 91 days). Each cell is one 7-day slice of Statuspage-standard uptime (1 − (critical + 0.3 × major) / window; minors and maintenance excluded; red when the slice dips below the stated SLA).
Claude — Incidents by Day last 7d
MinorMajorCritical
Total 13 incidents
0
1
3
4
5
05-2805-2905-3005-3106-0106-0206-0306-04
Worst Incidents
Ranked by severity-weighted duration (impact × wall-clock). Click any incident for the full update timeline.
Type of Failure
Categorised from the public incident headlines (outage / latency / auth / etc.).
Elevated errors
10
77%
Degraded
3
23%
When It Breaks
Incident starts by weekday × hour, UTC. Hover a cell for incident detail.
S
0
M
Monday06:00–07:00 UTC
1incident
1 minor
Opus 4.7 elevated errorsJun 1
Monday09:00–10:00 UTC
1incident
1 minor
Sonnet 4.5 elevated errorsJun 1
Monday12:00–13:00 UTC
1incident
1 minor
Elevated errors for Claude Opus 4.7Jun 1
Monday14:00–15:00 UTC
1incident
1 minor
Elevated errors on Claude Sonnet 4.6Jun 1
Monday18:00–19:00 UTC
1incident
1 minor
Degraded performance for Claude Sonnet 4.6Jun 1
5
T
Tuesday06:00–07:00 UTC
1incident
1 major
Elevated errors on multiple modelsJun 2
1
W
Wednesday04:00–05:00 UTC
1incident
1 major
Issue affecting some Claude Code servicesJun 3
Wednesday07:00–08:00 UTC
1incident
1 minor
Elevated errors on Opus 4.7Jun 3
2
T
Thursday08:00–09:00 UTC
1incident
1 major
Elevated errors on Claude Opus 4.7May 28
Thursday19:00–20:00 UTC
1incident
1 minor
Billing and subscription management issuesMay 28
2
F
Friday08:00–09:00 UTC
1incident
1 minor
Elevated errors on Claude Opus 4.8May 29
Friday18:00–19:00 UTC
1incident
1 major
Elevated errors for Claude Opus 4.8May 29
2
S
Saturday22:00–23:00 UTC
1incident
1 minor
opus 4.7 elevated errorsMay 30
1
00
06
12
18
HOUR OF DAY · UTC13 incident starts · hover any cell for detail
Hottest hour
Monday 06:00 1
Worst day
Monday 5
Worst time of day
06:00–07:00 2
How fast they fix things
Distribution of resolution times alongside the 12-week trend so you can see whether they're getting faster or slower.
Typical fix
38m
half of incidents resolve faster
On a bad day
3h 20m
9 in 10 resolve faster than this
Distribution
<15m
0
15m–1h
8
1–4h
4
4–24h
1
24h+
0
+0 ongoing (not counted above)
MTTR Trend (12 weeks)
Are they recovering faster or slower over time? Lower is better.