Live Database Migration for Elasticity in a Multitenant Database for Cloud Platforms

TitleLive Database Migration for Elasticity in a Multitenant Database for Cloud Platforms
Publication TypeTechnical Report
Year of Publication2010
AuthorsDas, S, Nishimura S, Agrawal D, El Abbadi A
Date Published06/2010
InstitutionUCSB CS

The growing popularity of cloud computing as a platform for deploying internet scale applications has seen a large number of web applications being deployed in the cloud. These applications (or tenants) are typically characterized by small data footprints, different schemas, and variable load patterns. Scalable multitenant database management systems (DBMS) running on a cluster of commodity servers are thus critical for a cloud service provider to support a large number of small applications. Multitenant DBMSs often collocate multiple tenants. databases on a single server for effective resource sharing. Due to the variability in load, elastic load balancing of tenants. data is critical for performance and cost minimization. On demand migration of tenants. databases to distribute load on an elastic cluster of machines is a critical technology for elastic load balancing. Therefore, efficient live database migration techniques with minimal disruption and impact in service is paramount in such systems. Unfortunately, most popular DBMSs were not designed to be nimble enough for efficient migration, resulting in downtime and disruption in service when the live databases need migration. We focus on this problem of live database migration in a multitenant cloud DBMS. We evaluate different database multitenancy models in the context of migration and propose an efficient technique for live migration of a tenant.s database with minimal downtime and impact on performance. We implement the proposed migration technique in a database system designed for the cloud. Our evaluation using standard OLTP benchmarks shows that our proposed technique can migrate a live tenant database with as low as 70 ms service disruption; an order of magnitude improvement compared to known heavy weight techniques for migrating a database.