Cost-aware horizontal scaling of NoSQL databases using probabilistic model checking

摘要

In this work we target horizontal scaling of NoSQL databases, which exhibit highly varying, unpredictable and difficult to model behavior coupled with transient phenomena during VM removals and/or additions. We propose a solution that is cost-aware, systematic, dependable while it accounts for performance unpredictability and volatility. To this end, we model the elasticity as a dynamically instantiated Markov decision process, which can be both solved and verified using probabilistic model checking. Further, we propose a range of complementary decision making policies, which are thoroughly evaluated in workloads from real traces. The evaluation provides strong insights into the trade-offs between performance and cost that our policies can achieve and prove that we can avoid both over- and under-provisioning.