Most engineering leadership teams are grappling with the fact that reliability costs too much, teams are burnt out, and they feel something has to change. Typically, teams resort to optimization: smarter alerting, faster runbooks, better dashboards, and more training. Teams invest heavily, see modest gains, and then end up right back where they started when the next incident hits. Optimization doesnât fail because of execution. Itâs that the underlying model is broken. Reactive SRE â managing reliability by responding to incidents after they occurâ is actually really expensive. No amount of refinements will change this. Organizations need to understand why the reactive model is flawed; until they do, they will keep spending more, only to stand still. The cost of reacting The cost of downtime is often defined by the revenue impact: the minutes of unavailability multiplied by a per-hour rate. However, that number doesnât accurately represent what reactive operations actually cost. True costs include the hours engineers spend investigating incidents. It also includes senior SREs being pulled off a critical project to triage alerts that were just noise, hours-long postmortems, remediation work, meetings held to decide the next step, and burnout and the attrition rate that follow when engineers spend more time firefighting than building. The 2024 CrowdStrike outage is considered to be the largest IT outage. A faulty software upgrade caused a global disruption for 8.5 million Windows systems globally. Flights were grounded, hospital record systems became inaccessible, and financial transactions were disrupted. On paper, Fortune 500 companies suffered a $5.4 billion financial loss, but there was a hidden cost. SRE and DevOps teams had to perform manual remediation plans for days, resulting in team burnout and fatigue. This is a big indicator of how much a reactive model takes from the people on the inside. Reactive SRE