Write the policy
Define slow-burn and fast-burn actions: feature freeze, rollback, capacity increases, and who can grant an exception. Be explicit about what counts as SLO spend (customer-visible failures) versus noise (synthetics in a paused region).
Tie policy triggers to Watch.Dog alerts so responses are automatic, not ad hoc. If the fast-burn threshold trips, on-call should know whether to roll back, fail over, or activate a kill switch before paging leadership.
Set expectations per service tier. Critical customer journeys may lock deploys sooner than internal dashboards; document the split so product teams aren't surprised.
Make the policy visible
Show budget status in dashboards, sprint reviews, and on-call briefs. Add a traffic-light widget to your deployment UI so engineers see budget health before merging.
Require a burn review before shipping risky changes when budget is low. Include product managers so customer tradeoffs are intentional.
Publish a short FAQ for leadership and support so they know what "budget freeze" means and how it affects timelines.
Close the loop
Log every policy trigger with cause, remediation time, and which mitigations worked. Capture whether the alert was actionable or if tuning is needed.
Feed learnings back into monitors, capacity models, and incident runbooks. If policy freezes are frequent, you may need new synthetics, more capacity headroom, or tighter pre-release testing.
Close with customers: if a freeze delays a feature, update your roadmap and status page so trust stays intact.
Rehearse enforcement
Run monthly tabletop exercises where a fast burn forces a deploy freeze. Measure how quickly teams find the rollback, communicate to support, and unfreeze once budgets heal.
Review exceptions quarterly. If leadership keeps overriding the policy, adjust SLOs or improve how you measure customer pain.