Setting SLOs and error budgets means choosing the reliability indicators that matter to users, setting realistic targets on them, and turning the gap to perfection into a budget that governs how much risk you take.
SLOs make reliability a deliberate decision rather than an absolute. You pick indicators that reflect user experience, set targets you can actually meet, and use the error budget, the allowed unreliability, to decide when to ship and when to stabilise. The discipline is choosing indicators that matter and targets you will honour.
A good SLI moves when users are actually affected, usually a ratio of good events to total events: successful requests over all requests, or requests under a latency threshold. Avoid convenient internal metrics that look healthy while users suffer. Pick a small number that genuinely represents the experience.
An SLO target (say 99.9% over 30 days) should be achievable and meaningful; too strict and you will ignore it, too loose and it protects nothing. The error budget is one minus the SLO, and it only matters if you act on it: healthy budget means you can take risks and ship, a nearly-exhausted budget means slow down and prioritise reliability. Alert on the burn rate, not just the raw number.
Ops Singularity computes SLIs from the request-level telemetry it ingests and can prioritise incidents by their impact on your SLOs, so Sentinel AI acts first where an error budget is burning fastest, tying autonomous resolution directly to the reliability targets you set.
Base it on user expectations and the cost of reliability, and pick a target you will actually honour. Common choices are 99.9% or 99.95%, leaving an error budget that allows shipping.
An agreed rule for what happens as the budget depletes, typically freezing risky changes and prioritising reliability work until it recovers.
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