// calculate error budgets and downtime from any SLA percentage
Calculate SLA/SLO error budgets and allowed downtime instantly. Enter any uptime percentage to see allowed errors, downtime per day/week/month/year, and MTTR.
Enter a value between 0 and 100. Common values: 99.9 (three nines), 99.99 (four nines).
Used to calculate allowed error count alongside downtime budgets.
Awaiting calculation
Enter an SLA percentage and click CalculateType your SLA or SLO percentage, or click a quick-select preset (99%, 99.9%, 99.99%, etc.).
Optionally enter your requests per day to get allowed error counts alongside downtime windows.
Click Calculate to see all budgets broken out by day, week, month, and year. Copy the full table with one click.
An SLA (Service Level Agreement) defines the uptime guarantee between a provider and customer. An SLO (Service Level Objective) is an internal reliability target. This tool converts any uptime percentage into practical downtime budgets and error windows across multiple time periods.
An SLA (Service Level Agreement) is a contractual commitment between a service provider and a customer, often with financial penalties for breach. An SLO (Service Level Objective) is an internal engineering target — typically stricter than the SLA — used to proactively manage reliability before it impacts customers.
The error budget is the amount of unreliability you are allowed within your SLA/SLO window. For a 99.9% SLO over 30 days, you have 43.2 minutes of downtime budget. Once the budget is exhausted, new feature launches are typically paused until the next period begins.
"The nines" is shorthand for how many 9s appear in an uptime percentage. 99.9% is "three nines," 99.99% is "four nines," and 99.999% is "five nines." Each additional nine roughly reduces allowed annual downtime by a factor of 10.
Allowed downtime = total period duration × (1 − uptime fraction). For 99.9% uptime per month: 30 days × 24 hours × 60 minutes × 0.001 = 43.2 minutes. This calculator uses 365.25 days per year, 30.44 days per month, 7 days per week, and 1 day for daily figures.
Most consumer web services target 99.9% (three nines). Business-critical APIs often target 99.95% or 99.99%. Achieving five nines (99.999%) requires significant investment in redundancy and automated failover, and is typically reserved for life-critical or financial systems.
Yes — think of the percentage as your success rate, not just uptime. If your SLO is "99.9% of requests return 2xx," enter 99.9%. Then enter your requests per day and the tool will show you exactly how many errors per day/week/month you can afford.
A Service Level Agreement (SLA) or Service Level Objective (SLO) calculator converts an uptime percentage into concrete, human-readable downtime windows and error budgets. Rather than reasoning abstractly about "99.95% availability," engineers and operations teams can see exactly how many minutes per month, hours per year, or requests per day are within acceptable failure tolerance.
This tool is designed for software engineers, SRE teams, infrastructure architects, and anyone who needs to communicate reliability targets in plain terms — whether drafting a vendor contract, presenting to leadership, or planning a new service's reliability posture.
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These three terms are closely related but serve different purposes in the reliability engineering (SRE) world:
A common best practice is to set internal SLOs stricter than external SLAs — for example, an internal 99.95% SLO backing a 99.9% SLA — to provide a buffer for incident response without triggering customer-facing penalties.
The error budget is the inverse of your SLO. If your SLO is 99.9%, your error budget is 0.1%. Over a 30-day month, that works out to approximately 43.8 minutes of allowed downtime or failure. Once the error budget is consumed, SRE teams commonly implement a "feature freeze" — no new deployments until the next measurement period begins — allowing the team to focus exclusively on reliability work.
Error budgets make reliability concrete and actionable. They turn abstract percentages into a shared resource that both product and engineering teams can reason about together.
The table below shows the annual downtime budget for each common SLA tier, from two nines to six nines:
Achieving five nines is extremely difficult. A 5-minute annual downtime budget means even a single routine deployment rollback can exceed the entire year's tolerance. Six nines is rarely targeted outside of telecommunications infrastructure and safety-critical control systems.
When planning incident response, it is helpful to know not just annual downtime but also how much tolerance you have per day or per week. A 99.9% SLO allows roughly 86.4 seconds per day — meaning a single incident must be detected, diagnosed, and resolved within about a minute and a half to stay within budget. At 99.99%, the daily budget is just 8.6 seconds, making automated detection and self-healing systems essentially mandatory.
A burn rate measures how quickly you are consuming your error budget relative to the target rate. A burn rate of 1 means you are consuming budget at exactly the rate needed to exhaust it at the end of the window. A burn rate of 2 means you will exhaust the budget in half the time. Burn rate alerting — alerting when the burn rate exceeds a threshold like 2× or 14.4× — is a core practice in Google's Site Reliability Engineering methodology and allows teams to detect problems before the budget is fully consumed.
This tool is not limited to uptime. Any success-rate SLO can be modeled here. If your SLO is "99.5% of HTTP requests return a 2xx response," enter 99.5% as the uptime value. Then enter your average requests per day to see the absolute error counts you can absorb per day, week, and month. This makes it easy to set concrete alerting thresholds and explain budget consumption to non-technical stakeholders.
The core formula is straightforward: Allowed Downtime = Period Duration × Error Rate, where Error Rate = 1 − (SLA% / 100). For example, at 99.9%: error rate = 0.001. Multiplied by 525,960 minutes per year = 525.96 minutes = 8 hours 45 minutes 57 seconds. For request errors: Allowed Errors per day = Requests per day × Error Rate.