site-reliability-engineer

SLOs (Service Level Objectives) and SLIs (Service Level Indicators) are metrics that define and measure reliability targets. SLIs quantify actual performance—like API latency or error rate—while SLOs set acceptable thresholds for those metrics. Define SLIs based on user-impacting signals, then set SLO targets that balance reliability with development velocity, typically tracked through monitoring stacks like Prometheus or Grafana.

Configure a monitoring stack (Prometheus, Grafana, Datadog, New Relic, or ELK) to collect metrics from all services, then define alerting rules that fire on SLO violations or anomalies. Create runbooks alongside alerts to guide incident response, and deploy dashboards that surface end-to-end health, latency, and error budgets so on-call engineers can act quickly.

Incident response workflows coordinate detection, communication, and resolution through alerts and runbooks that guide responders toward root cause. Post-mortems—blameless reviews after incidents—document what happened, why, and improvement actions. Together they drive continuous reliability improvements by converting incidents into operational learning.

Yes, monitoring stacks track error budgets by recording actual performance against SLO targets. Error budgets measure how much downtime or performance degradation is acceptable within a period; monitoring systems calculate remaining budget by comparing observed metrics to SLO thresholds, alerting when budgets deplete.

Before deploying monitoring, define your SLIs and SLOs, instrument your services to emit metrics, and validate that your monitoring stack can ingest and store the required data. Establish runbook templates and alert routing so incidents trigger defined workflows; test dashboards and alerts in pre-production to ensure they surface actionable signals.

Health checks provide fast, binary signals of service availability that complement detailed metrics from dashboards and alerts. They enable rapid automatic failover, load-balancing decisions, and quick triage during incidents; combined with alerting and dashboards, they create redundant detection that catches both gradual degradation and sudden outages.