Computational risk management for building highly reliable network services

Building reliable network services that can deliver consistent high performance to clients in the presence of failures and bursty demand is expensive and inefficient. Resources often need to be heavily overprovisioned to accommodate peak demand and the cost of such overprovisioning "prices out" many applications that could stand to benefit from a performance safety-net and ultimately provide more reliable service to end users. To address these problems, we propose an approach based on a shared Computational Service Provider (CSP). A CSP is an entity which provides massive amounts of widely distributed computation and storage and makes resources available through a mix of spot and derivative markets. Services obtain resources through the CSP and, drawing inspiration from finance, employ quantitative risk management techniques for trading off cost, performance, and risk to probabilistically achieve target levels of delivered client performance.