error budget

The arithmetic takes ten seconds and is the part most often skipped. The stall is the signal: it means error budgets are something you have read about rather than used.

Anyone can divide bad requests by total. This answer shows the aggregation mistakes that quietly corrupt SLO dashboards, the rate-versus-increase traps that make budgets lie, and when subqueries cost too much.

Spending the budget is arithmetic; enforcing consequences is politics plus automation. The answer that lands names trigger thresholds, the deploy gate that blocks releases, and the dated escape valve.

Internal platforms hide a trap: the direct user is an engineer, but the real traffic belongs to their customers. Define SLIs from the consumer's vantage and turn the error budget into roadmap currency.

Their green page, your red SLO. Separate their true failure rate from the amplification your own client adds, buffer at the boundary, then escalate with a client-side scorecard instead of feelings.

An SLA is a price list for failure signed before the failures. Bring the measured distribution, negotiate methodology and exclusions harder than the headline number, and phase targets with dates.

You have added a dependency with a latency distribution an order of magnitude wider than anything else in your stack, whose failure mode is a plausible wrong answer rather than an error.

An internal platform with no stated objective still has one. Every team guesses it, they all guess differently, and the guesses only surface during an outage.

A request that streams for ninety seconds is not slow, it is long. Total latency mixes the part users wait for with the part they read, and an SLO built on it will page you for success.