Clouds offer significant advantages over traditional cluster computing architectures including flexibility, high-availability, ease of deployments, and on-demand resource allocation - all packed up in an attractive pay-as-you-go economic model for the users. However, cloud users are often forced into vendor lock-in due to the use of incompatible APIs, cloud-specific services, and complex pricing models used by the cloud service providers (CSPs). Cloud management platforms (CMPs), supporting hybrid and multi-cloud deployments, offer an answer by providing a unified abstract interface to multiple cloud platforms. Nonetheless, modelling applications to use multi-clouds, automated resource selection based on the user requirements from various available CSPs, cost optimization, security, and runtime adaptation of deployed applications and services still remain a challenge.

In this talk, I'll give an introduction to Melodic, which is a middleware platform for Cross-Cloud data-intensive applications. The Melodic platform enables data-intensive applications to run within defined security, cost, and performance boundaries seamlessly on geographically distributed and federated cloud infrastructures. Melodic thereby realizes the potential of heterogeneous cloud environments for big data and data-intensive applications by transparently taking advantage of distinct characteristics of available private and public clouds, dynamically optimize resource utilization, consider data locality, conform to the user’s privacy needs and service requirements, and counter vendor lock-in.