While there has been prior work to underprovision the power distribution infrastructure for a datacenter to save costs, the ability to underprovision the backup power infrastructure, which contributes significantly to capital costs, is little explored. There are two main components in the backup infrastructure – Diesel Generators (DGs) and UPS units – which can both be underprovisioned (or even removed) in terms of their power and/or energy capacities. However, embarking on such underprovisioning mandates studying several ramifications – the resulting cost savings, the lower availability, and the performance and state loss consequences on individual applications – concurrently. This paper presents the first such study, considering cost, availability, performance and application consequences of underprovisioning the backup power infrastructure. We present a framework to quantify the cost of backup capacity that is provisioned, and implement techniques leveraging existing software and hardware mechanisms to provide as seamless an operation as possible for an application within the provisioned backup capacity during a power outage. We evaluate the cost-performance-availability trade-offs for different levels of backup underprovisioning for applications with diverse reliance on the backup infrastructure. Our results show that one may be able to completely do away with DGs, compensating for it with additional UPS energy capacities, to significantly cut costs and still be able to handle power outages lasting as high as 40 minutes (which constitute bulk of the outages). Further, we can push the limits of outage duration that can be handled in a cost-effective manner, if applications are willing to tolerate degraded performance during the outage. Our evaluations also show that different applications react differently to the outage handling mechanisms, and that the efficacy of the mechanisms is sensitive to the outage duration. The insights from this paper can spur new opportunities for future work on backup power infrastructure optimization.