An operations team is defining reliability metrics and alerting policies for a telemetry data ingestion pipeline built on Google Cloud Pub/Sub and Cloud Dataflow. They want to adopt Google Cloud Site Reliability Engineering (SRE) best practices to measure service quality and manage operational alerts. Which of the following statements accurately describe the correct implementation of SLIs, SLOs, or error budgets for this service? (Select TWO.)
- The Service Level Indicator (SLI) is calculated as the ratio of successfully processed messages within a target latency threshold to the total number of valid incoming messages.Answer
- BThe Service Level Objective (SLO) represents the measured real-time ratio of success, whereas the Service Level Indicator (SLI) is the target percentage defined in customer contracts.
- Alerting policies should evaluate multi-window error budget burn rates to trigger notifications before the error budget is exhausted.Answer
- DAlerting policies should immediately page on-call engineers whenever Dataflow worker CPU utilization exceeds 85% for more than 5 minutes.
Answer
The Service Level Indicator (SLI) is defined as the quantifiable ratio measuring successful events over total valid events, and operational alerting should be based on multi-window error budget burn rates rather than static resource metrics.
Defining the Service Level Indicator (SLI) as a quantifiable ratio of successful events over total valid events reflects actual user-perceived performance. Furthermore, configuring alerts around error budget burn rates ensures on-call engineers are paged when service degradation risks exhausting the error budget, adhering strictly to Google Cloud SRE practices.
Step-by-Step Solution
Key Concept
Defining SLIs as quantitative performance ratios and implementing multi-window error budget burn-rate alerts.