A global gaming company operates a real-time multiplayer matchmaking service hosted on Google Kubernetes Engine (GKE). To maintain user satisfaction while allowing frequent service updates, the Site Reliability Engineering (SRE) team needs to align operational alerting with customer experience using Google Cloud Observability. Which TWO of the following operational strategies should the team implement to establish an effective reliability framework?
- Define the Service Level Indicator (SLI) as the ratio of successful latency-compliant requests to the total valid requests measured at the Google Cloud HTTP(S) Load Balancer.Answer
- BConfigure static threshold alerts based on GKE cluster CPU and memory utilization exceeding 85% to trigger immediate page alerts.
- Implement multi-window, multi-burn-rate alerts in Cloud Monitoring to notify the team when error budget consumption rates threaten the SLO.Answer
- DSet the Service Level Indicator (SLI) to a fixed 99.9% target and treat the Service Level Objective (SLO) as the real-time measurement of incoming request traffic.
Answer
The team should define the SLI as the ratio of successful latency-compliant requests to total requests measured at the load balancer, and implement multi-window, multi-burn-rate alerts in Cloud Monitoring based on error budget consumption.
Defining the SLI as a ratio of successful/low-latency requests to total requests correctly measures user experience at the application entry point. Furthermore, using multi-window, multi-burn-rate alerting ensures the team is alerted only when the rate of error budget consumption poses a genuine threat to meeting the SLO, balancing reliability with feature deployment velocity.
Step-by-Step Solution
Key Concept
Defining SLIs as user-centric metric ratios and alerting on multi-window error budget burn rates rather than static infrastructure metrics.