Declarative automated cloud resource orchestration

TLDR

Cloud computing’s widespread deployment creates challenges in orchestrating complex, geographically distributed compute, storage, and network subsystems for diverse clients. The paper introduces COPE, a distributed platform that enables declarative automated cloud resource orchestration, and evaluates its viability using production traces from a large hosting company. COPE employs the COPElog declarative policy language to specify system-wide constraints and goals, then optimizes compute, storage, and network resource allocations based on policy specifications and current cloud system states to better meet provider objectives and customer SLAs. Initial evaluation with production traces demonstrates COPE’s viability, and a scenario involving geographically distributed data centers illustrates its applicability.

Abstract

As cloud computing becomes widely deployed, one of the challenges faced involves the ability to orchestrate a highly complex set of subsystems (compute, storage, network resources) that span large geographic areas serving diverse clients. To ease this process, we present COPE (Cloud Orchestration Policy Engine), a distributed platform that allows cloud providers to perform declarative automated cloud resource orchestration. In COPE, cloud providers specify system-wide constraints and goals using COPElog, a declarative policy language geared towards specifying distributed constraint optimizations. COPE takes policy specifications and cloud system states as input and then optimizes compute, storage and network resource allocations within the cloud such that provider operational objectives and customer SLAs can be better met. We describe our proposed integration with a cloud orchestration platform, and present initial evaluation results that demonstrate the viability of COPE using production traces from a large hosting company in the US. We further discuss an orchestration scenario that involves geographically distributed data centers, and conclude with an ongoing status of our work.