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99.9% uptime downtime & error budget

99.9% uptime allows about 43m 12s of downtime per 30-day month, roughly 8h 46m a year. Here is the full ladder, the error budget in requests, and how fast you can burn it.

allowed downtime / month43m 12s30-day window
error budget5K reqsof 5M / month
failure allowance0.1%of all requests

allowed_downtime

Allowed downtime at 99.9%, by window

Allowed downtime at 99.9% across time windows
windowallowed downtime
per day1m 26s
per week10m 5s
per 30 days43m 12s
per 90 days2h 10m
per 365 days8h 46m

burn_rate

How fast the monthly budget burns

At 1x you spend the whole 30-day budget exactly over 30 days. 14.4x is Google's fast-burn alert threshold, the rate that drains the month in about two days.

Time to exhaust the 30-day budget at each burn rate
burn ratebudget gone in
1x30d
2x15d
5x6d
10x3d
14.4x (fast-burn page)2d 2h

what_it_takes

What it takes to hold 99.9% (three nines)

The default target for most user-facing SaaS. Holding it means no single manual step on the recovery path can take more than a few minutes: a load balancer, automated rollouts and rollbacks, and alerting that pages before users notice. This is the first tier where staying up stops being luck and starts being design.

Need more? See 99.95% uptime and what the next nine costs. Lighter need? 99.5% uptime is cheaper to hold.

faq

Questions & answers

How much downtime does 99.9% uptime allow?
99.9% uptime allows about 43m 12s of downtime per 30-day month, which works out to roughly 8h 46m a year. Go past that in a window and you have missed the target for that window.
What is the error budget for 99.9% uptime?
Over 5M requests in a month, 99.9% permits about 5K failed requests before the budget is spent. The budget is 0.1% of whatever volume you serve, so it scales with traffic.
Is 99.9% uptime good enough?
It depends on what your users need and what the next tier costs to hold. The default target for most user-facing SaaS. The breakdown below shows what it takes to hold 99.9% and whether the next nine is worth it.

Picking a target is easy. Holding it in production is the work.

I review where a system actually spends its error budget and what the next nine really costs. Book a call, or leave your email and I'll reach out.

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Prefer proof first? See how this plays out in real case studies →