Site Reliability Engineering (SRE) Services

Reliability is a product feature with a cost curve, and treating it as an absolute is what makes it expensive. Chasing five nines on a service where customers genuinely tolerate three is a bad allocation of engineering time; the discipline of SRE is deciding — explicitly, with the business in the room — how reliable each service needs to be, then engineering to that number and spending the remaining budget on shipping.

We start by defining service level objectives against indicators customers actually experience: request success rate, end-to-end latency at the tail, data freshness, job completion. Those become error budgets, which turn reliability into a shared currency rather than an argument — when the budget is healthy the team ships features, when it is spent the team fixes reliability. It converts an emotional debate into a policy.

Observability follows. Most teams have monitoring — dashboards showing CPU — without observability, meaning they cannot answer novel questions about production. We instrument distributed tracing across service boundaries, structured logs with consistent correlation IDs, and metrics that map to the SLOs rather than to the infrastructure. Alerts are rewritten to fire on symptoms customers feel, with the noisy infrastructure alerts that cause pager fatigue deliberately deleted.

The remaining work is practice. Incident command roles and severity definitions, runbooks written for someone at 3am, blameless postmortems that produce tracked actions rather than documents nobody reads, game days and controlled chaos experiments to validate failure assumptions, and capacity planning with load testing against realistic traffic shapes. We embed with your team so this becomes their capability rather than a dependency on ours.