Cloud Computing (CC) is a model that enables ubiquitous, convenient, and on-demand network access to a shared pool of configurable computing resources. In CC applications, it is possible to access both software and hardware architectures remotely and with little or no knowledge about their physical or logical locations. Due to its low deployment and management costs, the CC paradigm is being increasingly used in a wide variety of online services and applications, including remote computation, software-as-a-service, off-site storage, entertainment, and communication platforms. However, several aspects of CC applications, such as system design, optimization, and security issues, have become too complex to be efficiently treated using traditional algorithmic approaches under the increasingly high complexity and performance demands of current applications. Recently, advances in Computational Intelligence (CI) techniques have fostered the development of intelligent solutions for CC applications. CI methods such as artificial neural networks, deep learning, fuzzy logic, and evolutionary algorithms have enabled improving CC paradigms through their capabilities of extracting knowledge from high quantities of real-world data, thus further optimizing their design, performance, and security with respect to traditional techniques. This chapter introduces recent CI techniques, reviews the main applications of CI in CC, and presents challenges and research trends.