Clouds have emerged as a new paradigm to access compute, storage, and networked resources in secure and cost effective manner. Their major benefits are seen in the commercial domain with its key features such as on-demand and more flexible resource provisioning, pay per use, and customized application environments. Also research communities such as High Energy Physics (HEP), Biology, and Neuroscience are investigating the applicability of Clouds, with their strengths and weaknesses in scientific environments. In this paper we will show that in scientific environments there are certain areas where cloud services should be exploited to support the challenging e-Science requirements. Among them are, support for virtual communities, dynamic service and resource discovery, identity and resource federation, and access to data catalogues. The Grid community has actively contributed to address some of these issues, thus we propose to reuse existing efforts to complement Cloud services with Grid computing best practices, production services, and experiences, including standardization. In this paper we will provide guidelines of how to realize multi-cloud federated deployments based on a survey of existing Grid technologies in context augmenting it with lessons learned gained in scientific environments. The contribution focuses on the areas of compute, data, information, and security. We will also show potential benefits that scientists can gain by adopting proposed solutions in cloud-based deployments.