SRE & Observability

Service reliability is the ability of a digital service to deliver the expected outcome consistently, within an acceptable time and under changing conditions.

A reliable service remains useful during traffic increases, software releases, dependency failures, and infrastructure changes. Uptime matters, but it is only one part of the customer experience

AI systems can return incorrect answers, use the wrong sources, exceed cost limits, or take too long to respond, even when infrastructure monitoring shows everything is working.

AI observability tracks prompts, retrieval, tool calls, outputs, quality, safety, latency, cost, and user outcomes to show whether an AI interaction was truly successful.

Observability vs monitoring gets treated as a vocabulary problem. It isn't. Teams that mix up the two end up with dashboards that look healthy while customers are stuck in a broken checkout flow, or with an observability stack nobody queries because no one defined what question it's supposed to answer.

Monitoring tells you a threshold got crossed. Observability lets you ask why, on the fly, about a failure mode nobody wrote an alert for. Both matter. Neither replaces the other.

SLO vs SLA: understand how reliability targets and contractual commitments differ, and how both help teams improve service performance, accountability, customer trust, and incident response.