Cloud computing introduced many new software techniques as well as new issues. New requirement engineering processes, design techniques, code generation, and testing techniques need to be developed for cloud applications. Combinatorial testing is needed to test the cloud applications. Numerous numbers of combinatorial testing techniques are available, most of them produce static sequences of test configurations and their goal is often to provide sufficient coverage such as 2-way interaction coverage. But the goal of pairwise testing is to identify those compositions that are faulty for cloud applications. Currently, cloud computing has been applied to share computing resources to achieve coherence and economies of scale similar to a utility over a network. Testing-as-a-Service (TaaS) in a cloud environment can leverage the computation power provided by the cloud. Specifically, testing can be scaled to large and dynamic workloads, executed in a distributed environment with hundreds of thousands of processors, and these processors may support concurrent and distributed test execution and analysis. Pair-wise testing is a combinatorial test criterion technique based on specification, which requires that for each pair of parameters, every combination of their valid value should be covered by at least one test case in the test set. The generation of minimal pairwise test sets has been shown to be an NP-complete problem and there have been several deterministic algorithms published. Some of pairwise test techniques like IPOG, AETG, MIPOG, and ACO etc. are available to generate the pairwise test cases. The proposed approach is to generate the optimized pair-wise test cases for any cloud applications.