Utilities

SLA & Uptime Calculator

Calculate the maximum allowed downtime for any SLA percentage. See exactly how many minutes, hours, or days of downtime your SLA permits.

% uptime

Per Day

1m 26s

allowed downtime

Per Week

10m 4s

allowed downtime

Per Month (30d)

43m 11s

allowed downtime

Per Quarter

2h 9m 35s

allowed downtime

Per Year

8h 45m 35s

allowed downtime

Uptime Required

99.9%

0.100% error budget

SLA Comparison Table

SLATierDailyMonthlyYearlyTypical Use
99%Two Nines14m 24s7h 18m3d 15h 36mInternal tools, batch jobs
99.5%Two and a Half7m 12s3h 39m1d 19h 48mNon-critical services
99.9%Three Nines1m 26s43m 50s8h 45m 36sStandard SaaS, APIs
99.95%Three and a Half43s21m 55s4h 22m 48sBusiness-critical apps
99.99%Four Nines8.6s4m 23s52m 33sPayment systems, auth
99.999%Five Nines0.86s26s5m 15sCore infrastructure

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Understanding SLA and Uptime

A Service Level Agreement (SLA) defines the expected level of service availability between a provider and a customer. In the world of cloud computing and SaaS, SLAs are typically expressed as a percentage of uptime — such as 99.9% or 99.99%.

The difference between each "nine" might seem small numerically, but the operational impact is enormous. Going from 99.9% to 99.99% reduces your allowed downtime by 10x, from about 8 hours 45 minutes per year to just 52 minutes. Achieving five nines (99.999%) requires sophisticated redundancy, automated failover, and extremely fast incident response — allowing only 5 minutes 15 seconds of total downtime per year.

Error Budgets in Practice

Google popularized the concept of error budgets in their SRE book. The idea is simple: if your SLA is 99.9%, you have a 0.1% error budget. As long as you stay within that budget, you can deploy new features and make changes. When the error budget is exhausted, the team shifts focus entirely to reliability improvements.

This creates a healthy balance between innovation and stability. Teams that have plenty of error budget remaining can move faster, while teams that are close to exhausting their budget naturally slow down and prioritize reliability.

How Uptimes.ai Helps You Meet Your SLA

Uptimes.ai reduces Mean Time to Recovery (MTTR) by 90% through AI-powered root cause analysis. When an incident occurs, our autonomous RCA agent investigates the issue in real-time — checking logs, metrics, recent deployments, and service dependencies — so your team can resolve issues in minutes instead of hours.

Frequently Asked Questions

What does 99.9% SLA mean?+
A 99.9% SLA (commonly called "three nines") means your service can be unavailable for a maximum of 8 hours, 45 minutes, and 36 seconds per year. This translates to about 43 minutes per month or 1 minute and 26 seconds per day of allowed downtime.
What is the difference between 99.9% and 99.99% SLA?+
99.9% SLA allows 8 hours 45 minutes of downtime per year, while 99.99% (four nines) allows only 52 minutes 33 seconds per year. That's a 10x reduction in allowed downtime. Moving from three nines to four nines requires significant investment in redundancy, monitoring, and incident response.
How is SLA downtime calculated?+
SLA downtime is calculated by multiplying the total time period by (1 - SLA percentage). For example, for 99.9% SLA over a year: 365.25 days * 24 hours * 60 minutes * (1 - 0.999) = 525.96 minutes = 8 hours 45 minutes 36 seconds.
What is an error budget?+
An error budget is the maximum amount of time your service can be down without violating the SLA. It's the complement of the SLA percentage. For a 99.9% SLA, your error budget is 0.1%. SRE teams use error budgets to balance reliability with feature velocity — when the budget is spent, they freeze deployments and focus on stability.
What SLA should I target for my service?+
It depends on the criticality: internal tools typically target 99% (two nines), standard SaaS and APIs target 99.9% (three nines), business-critical applications target 99.95-99.99%, and core infrastructure like payment systems and auth target 99.99%+ (four nines). Higher SLAs exponentially increase cost and complexity.