Jiazhang Liu;Yiren Ding Team 8 [10/22/13] 1 Traditional Database • Servers • Database Admin • DBMS Traditional Database 1 • High cost • Lack of elasticity • Hard to maintain 2 Introduction • Relational Cloud: “database-as-a-service” (DBaaS ) • Why is it attractive? – Hardware and energy cost much lower – The cost is proportional to actual use (pay-per-use) • So, how to make Relational Cloud more attractive? – Efficient multi-tenancy – Elastic scalability – Database privacy 3 Efficient multi-tenancy • Given a set of databases and workloads, what is the best way to serve them from a given set of machines? Efficient multi-tenancy 3 • Solution: – uses a single database server on each machine which hosts multiple logical databases. – Relational Cloud periodically determines which databases should be placed on which machines using a novel non-linear optimization formulation. – a cost model that estimates the combined resource utilization of multiple databases running on a machine. 4 Elastic scalability • A good DBaaS must support database and work- loads of different sizes. • The challenge arise when a database workload exceeds the capacity of a single machine. • Must support scale-out, where responsibility for query processing is partitioned among multiple nodes to achieve higher throughput. 5 Database Privacy • Encrypt all the data stored in the DBaaS. – privacy concerns would largely be eliminated. • However, any impact on processing encrypted data? 5 Database Privacy – Developed CryptDB: to provide privacy with an acceptable impact on performance (22.5% reduction in throughput) 6 Database partitioning • to scale a single database to multiple nodes, useful when the load exceeds the capacity of a single machine. • to enable more granular placement and load balance on the back-end machines compared to placing entire databases. 7 Database Placement • Resource allocation is a major challenge when designing a scalable, multi-tenant Service like Relational Cloud. 7 Database Placement • Resource Monitor Monitor the resource requirements of each workload • Combined Load Predictor Predicting the load multiple workloads will generate when run together on a server • Consolidation Engine Assigning workloads to physical servers 8 SYSTEM DESIGN • Relational Cloud Architecture 9 10 Flipboard • Greg Scallan, Chief Architect at Flipboard says, “Our service currently runs 100% on AWS in multiple availability zones.” • “We chose AWS because they were able to provide a majority of the solution we needed as we built our data center. Also, we appreciated the flexibility as we tried out various solutions to our business vision.” 11 Sources • Relational Cloud: A Database-as-a-Service for the Cloud： http://people.csail.mit.edu/nickolai/papers/curin o-relcloud-cidr.pdf • AWS Case Study: Flipboardhttps://aws.amazon.com/solutions/case -studies/flipboard/ • AWS Documentationhttp://docs.aws.amazon.com/AW SEC2/latest/UserGuide/concepts.html 12 Questions?