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99.5% uptime downtime & error budget

99.5% uptime allows about 3h 36m of downtime per 30-day month, roughly 1d 20h a year. Here is the full ladder, the error budget in requests, and how fast you can burn it.

allowed downtime / month3h 36m30-day window
error budget25K reqsof 5M / month
failure allowance0.5%of all requests

allowed_downtime

Allowed downtime at 99.5%, by window

Allowed downtime at 99.5% across time windows
windowallowed downtime
per day7m 12s
per week50m 24s
per 30 days3h 36m
per 90 days10h 48m
per 365 days1d 20h

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 99.5%

A common informal bar for early internal tools and B2B software with patient users. You reach it with health checks, automated restarts, and a deploy process that rolls back fast. It still tolerates the occasional manual recovery, which is why it is cheap to hold and rarely good enough to put in a contract.

Need more? See 99.9% uptime and what the next nine costs. Lighter need? 99% uptime is cheaper to hold.

faq

Questions & answers

How much downtime does 99.5% uptime allow?
99.5% uptime allows about 3h 36m of downtime per 30-day month, which works out to roughly 1d 20h a year. Go past that in a window and you have missed the target for that window.
What is the error budget for 99.5% uptime?
Over 5M requests in a month, 99.5% permits about 25K failed requests before the budget is spent. The budget is 0.5% of whatever volume you serve, so it scales with traffic.
Is 99.5% uptime good enough?
It depends on what your users need and what the next tier costs to hold. A common informal bar for early internal tools and B2B software with patient users. The breakdown below shows what it takes to hold 99.5% 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 →