Two nines: a 99% baseline
99% sounds high until you convert it: 14 minutes 24 seconds of allowed downtime every single day. That is a service users will regularly catch being down, not an edge case they hear about second-hand.
Two nines is a reasonable target for internal tools, batch pipelines, and staging environments, where an outage inconveniences colleagues rather than customers. Any paying, customer-facing product should start at three nines.
What a 2 9s target buys you
“2 9s” is the shorthand: the number of leading nines in the percentage gives the nickname, and each extra nine cuts the allowance by a factor of ten. That makes the jump from 2 9s to 3 9s the cheapest reliability win you will ever buy, and every nine after it roughly ten times harder.
In SRE terms a 2 9s objective hands you an enormous error budget, which is genuinely useful when velocity matters more than availability: experimental features, internal services, anything with no external promise attached. It has no place in a customer-facing SLA.
How a 99% allowance accumulates
The same 1% allowance becomes 7 hours 12 minutes in a 30-day month and 3 days 15 hours across a 365-day year. A handful of long incidents can consume it, but so can small failures that recur every day.
Track the total duration and the incident count together. A service can remain inside its percentage while frequent short interruptions still make it feel unreliable to users.
When a 99% target is a deliberate choice
A large error budget can be rational when a service is used only during office hours, has a manual workaround, or can catch up asynchronously after an interruption. In those cases, paying for redundancy may create less value than faster product work.
Make the trade explicit: document supported hours, the recovery owner, and the longest tolerable interruption. If another production service depends on the system, its 99% target becomes a ceiling for that downstream service too.
Downtime allowed at each SLA level
| Uptime | Per day | Per month | Per year |
|---|---|---|---|
| 99% Two nines | 14m 24s | 7h 12m | 3d 15h |
| 99.9% Three nines | 1m 26s | 43m 12s | 8h 45m 36s |
| 99.95% | 43s | 21m 36s | 4h 22m 48s |
| 99.99% Four nines | 9s | 4m 19s | 52m 34s |
| 99.999% Five nines | 864ms | 26s | 5m 15s |
| 99.9999% Six nines | 86ms | 3s | 32s |
| 99.9999999% Nine nines | 86μs | 2.6ms | 32ms |
SLA calculation cheatsheet
Availability calculation
Availability (%) = (Total Time - Downtime) / Total Time × 100Example: If a service was down for 7.3 hours in a 30-day month:
- Total Time = 30 days × 24 hours = 720 hours
- Availability = (720 - 7.3) / 720 × 100 = 98.99%
Response time SLA
Response Time Compliance (%) = (Responses Within Threshold / Total Responses) × 100Mean time metrics
- MTBF (Mean Time Between Failures) = Total Operational Time / Number of Failures
- MTTR (Mean Time To Repair) = Total Repair Time / Number of Repairs
- MTTA (Mean Time To Acknowledge) = Total Time to Acknowledge / Number of Incidents
Service credit calculation
Service Credit = (Monthly Service Fee) × (Credit Percentage for SLA Breach)SLA penalty example
- If availability drops below 99.9% but remains above 99.0%: 10% credit
- If availability drops below 99.0%: 25% credit
Track SLAs and downtime metrics at a glance
Hyperping reports on service reliability using data collected by your monitors. Select the reporting period, then review the results in the dashboard or export them.
- Track uptime, Mean Time to Recovery (MTTR), and SLA compliance for any reporting period.
- Export the selected period as a CSV file for audits, client reports, spreadsheets, or internal analysis.
- Review the complete incident history and use filters to narrow the records included in your report.
SLA & uptime management guides
What is uptime?
Uptime is the amount of time that a service is available and operational, typically expressed as a percentage over a given period such as a month or a year.
What is an SLA?
A service-level agreement (SLA) defines the level of service you expect from a vendor, laying out the metrics by which service is measured, as well as remedies or penalties should agreed-on service levels not be achieved.
How to prevent downtime?
Redundancy, monitoring and alerting are key to ensure a safe and reliable service.
Frequently asked questions
- How do you calculate availability?
- Availability (%) = (Total Time − Downtime) / Total Time × 100. For example, a service that was down 7.3 hours in a 30-day month (720 hours) has an availability of (720 − 7.3) / 720 × 100 = 98.99%.
- How much downtime does 99% uptime allow?
- At 99% uptime, the maximum allowed downtime is 14 minutes 24 seconds per day, 7 hours 12 minutes per 30-day month, and 3 days 15 hours 36 minutes per 365-day year.
- What's the difference between 99.9% and 99.99% uptime?
- Each additional nine reduces allowed downtime tenfold: 99.9% allows about 8 hours 46 minutes of downtime per year, while 99.99% allows just under 53 minutes. Meeting 99.99% generally requires automated failover, since a human response rarely fits inside the budget.
- How do I track SLA compliance?
- Continuous uptime monitoring measures availability from outside your infrastructure and records every outage. Hyperping checks your endpoints at up to 30-second intervals from multiple regions and reports uptime, MTTR, and SLA compliance over any period.
- When is 99% uptime acceptable?
- A 99% target can suit noncritical internal tools, prototypes, or services with a workable fallback. Customer-facing and revenue-critical services usually need a tighter target because 99% permits several hours of downtime per month.