Engineering teams often don’t notice cloud or observability spend until the invoice lands, by which time the damage is already done. The bill can jump because of misconfigurations, autoscaling, logging spikes, data transfer, idle resources, or AI workloads, and the current tools usually explain the problem too late rather than preventing it in real time.