Professional Cloud DevOps Engineer
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A DevOps team manages a business-critical microservice running on Google Kubernetes Engine (GKE). The team has defined an availability Service Level Objective (SLO) of 99.9% over a rolling 30-day window.
Currently, the team experiences alert fatigue caused by transient error spikes triggering paging alerts, while simultaneously missing slow, steady budget drain that exhausts the monthly error budget before scheduled reviews.
Which alerting strategy should the team implement in Cloud Monitoring to reliably detect both rapid and slow budget depletion while minimizing false positives?
Configure a single alerting policy using the select_slo_burn_rate selector configured with a 1-hour lookback period and a threshold of 1x baseline.
Configure an alerting policy using the select_slo_budget_fraction time-series selector to trigger an alert when the remaining error budget drops below 50% within a rolling 30-day window.
Configure an alerting policy using the select_slo_compliance time-series selector with a duration of 0 seconds to immediately trigger an incident whenever the compliance ratio drops below 0.999.
Configure two separate alerting policies using the select_slo_burn_rate time-series selector: a fast-burn alert with a 1-hour lookback period and a 10x threshold, and a slow-burn alert with a 24-hour lookback period and a 2x threshold.
Configure a single alerting policy using the select_slo_burn_rate selector configured with a 1-hour lookback period and a threshold of 1x baseline.
Configure an alerting policy using the select_slo_budget_fraction time-series selector to trigger an alert when the remaining error budget drops below 50% within a rolling 30-day window.
Configure an alerting policy using the select_slo_compliance time-series selector with a duration of 0 seconds to immediately trigger an incident whenever the compliance ratio drops below 0.999.
Configure two separate alerting policies using the select_slo_burn_rate time-series selector: a fast-burn alert with a 1-hour lookback period and a 10x threshold, and a slow-burn alert with a 24-hour lookback period and a 2x threshold.
Multi-burn-rate alerting is a best-practice Site Reliability Engineering (SRE) strategy that monitors the rate at which an error budget is consumed across multiple time horizons. In Google Cloud Monitoring, this is configured using the select_slo_burn_rate time-series selector, which measures the ratio of the current failure rate to the sustainable failure rate for an SLO.
Using two complementary policies with different lookback windows and burn-rate multipliers ensures comprehensive coverage of failure modes, balancing rapid time-to-detect (TTD) with high alert precision.