There is a considerable amount of prior effort on co-locating applications on datacenter servers for boosting resource utilization. However, we note that it is equally important to take power into consideration from the co-location viewpoint. Applications can still interfere on power in stringent power constrained infrastructures, despite no direct resource contention between the coexisting applications. This becomes particularly important with dynamic load variations, where even if the power capacity is tuned for the peak load of an application, co-locating another application with it during its off-period can lead to overshooting of the power capacity. Therefore, to extract maximum returns on datacenter infrastructure investments one needs to jointly handle power and server resources. We explore this problem in the context of a private-cloud cluster which is provisioned for a primary latency-critical application, but also admits secondary best-effort applications to improve utilization during off-peak periods. Our solution, Pocolo, draws on principles from economics to reason about resource demands in power constrained environments and provides answers to the when/where/what questions pertaining to co-location. We implement Pocolo on a Linux cluster to demonstrate its performance and cost benefits over a number of latency-sensitive and best-effort datacenter workloads.