Our team measures reliability using clearly defined SLIs (such as latency, error rate, availability, and throughput) and sets SLOs that align with business expectations and user experience targets. We track these metrics through centralized monitoring and dashboards, and use error budgets to balance new feature releases with system stability. If error budgets are consumed too quickly, we shift focus toward reliability improvements. Key SRE practices that have helped maintain uptime include automated alerting based on meaningful thresholds, infrastructure as code for consistent environments, auto-scaling and self-healing configurations, and well-documented runbooks for incident response. We also conduct blameless post-mortems after incidents and run periodic reliability reviews to identify recurring risks. By reducing operational toil through automation and continuously refining observability, we’ve been able to improve uptime, shorten MTTR, and maintain strong system performance.