site-reliability-engineer

SLOs (Service Level Objectives) and SLIs (Service Level Indicators) establish reliability targets and measure actual performance. Define SLIs as measurable metrics tied to user journeys, set SLOs as acceptable thresholds, and track both continuously against your monitoring stack to quantify error budgets and reliability commitments.

Popular stacks include Prometheus for metrics collection, Grafana for visualization, ELK for log aggregation, and Datadog for integrated observability. Choose based on your scale, budget, and operational complexity; most modern SRE practices support multi-tool stacks that collect metrics, logs, and traces across distributed services.

Alerting rules should trigger on meaningful SLO violations and error budget depletion rather than individual anomalies. Define thresholds tied to SLIs, use alert grouping and routing to route incidents to appropriate teams, and establish notification channels (Slack, PagerDuty) that support escalation and acknowledgment workflows.

Runbooks document detection signals, immediate mitigation steps, escalation paths, and diagnostic commands for each critical incident type. Post-mortems capture what happened, root causes, and prevention actions. Both templates accelerate response time and embed organizational learning into future incident handling.

Yes. Modern monitoring stacks like Datadog, Grafana Loki, and ELK support unified observability by collecting and correlating metrics, structured logs, and distributed traces. This multi-signal approach enables faster root-cause analysis and reduces time spent context-switching between tools during incidents.

Health checks validate service readiness and dependencies; integrate them into load balancers and deployment gates. Error budget tracking measures available reliability against SLO commitments in real time, allowing teams to decide whether current error rates permit new deployments or require stabilization.