A practical way to define SLOs and error budgets, connect them to release decisions, and avoid reliability debates without data.
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Error budgets are not a reporting exercise. They are a decision framework that balances feature velocity and reliability risk. If teams never change behavior when budget burns, SLOs are just dashboards.
For an API service:
This implies a 0.1% error budget.
If monthly traffic is 10,000,000 valid requests:
That number should immediately affect release policy.
Without this policy, budget tracking has no operational value.
(
sum(rate(http_requests_total{status=~"5.."}[5m])) /
sum(rate(http_requests_total[5m]))
) > 0.005
This detects a short-term burn rate above 0.5%, which can quickly consume a monthly budget.
Error budgets work when they change priorities in real time, not when they are reviewed once a quarter.
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