1. A method for cloud optimization using workload analysis, the method comprising: identifying, using a processor and a memory, an architecture of a workload received for execution in a cloud computing environment, the cloud computing environment including a set of cloud computing resources; identifying and marking a section of the workload for static analysis; performing static analysis on the section to determine a characteristic of instructions in the workload, wherein the characteristic of the instructions is discernible from the workload without executing the workload, wherein the characteristic of the instructions is indicative of a type of resource to use for executing the instructions, wherein the characteristic of the instructions in the workload is indicative of floating point intensive operations being present in the workload, wherein, responsive to the cache floating point intensive operations being present in the workload, the selecting selects a system as a part of the subset of the set of cloud computing resources, and wherein the system includes a level of support for floating point operations for executing the instructions; selecting a subset of the set of cloud computing resources, such that a cloud computing resource in the subset is available for allocating to the workload and has a characteristic that matches the characteristic of the instructions in the workload as determined from the static analysis; and suggesting the subset of cloud computing resources to a job scheduler for scheduling the workload for execution.