Many Internet service providers such as Netflix, Uber, and AirBnB use cloud providers' multiple data centers (DCs) to provide reduced user-perceived latency and better data availability without having their own DCs on multiple locations. Typically, those Internet applications want to get composite benefits from multiple storage services in each DC e.g., hot data in memory and cold data in object storage. Thus, applications developers need to find optimized DC locations and (combined) storage services to realize a tradeoff suitable for their requirements. However, this task of choosing both DC locations and combining different storage tiers to realize composite benefits are tedious and not an easy task due to
TripS (Switch Storage System) is a light-weight data palcement decision system considering both DC locations and storage tiers. TripS can run on top of any system (or application) that needs to find the optimized data placement in a multi-cloud environment. TripS also can help applications to handle dynamics from cloud infrastructure and applications (especially, short-term dynamics e.g., burst access, transient DC (network) failure, or overloaded node).
To evaluate the optimized data plamcement in a multi-cloud environment, TripS requires inputs from an underlying system.