Cloud data centers (CDCs) provide key infrastructure for cloud computing. Allocating computing resources is very important for the CDCs to function efficiently. Current allocation of resources in CDCs is mostly dedicated and static. However, workloads for cloud applications are highly variable which cause poor application performance, poor resource utilization or both. In this paper, adaptive dimensioning methods for CDCs are developed so that right amount of computing resources are allocated for variable workloads to meet quality of service requirements.