Service isolation, achieved by deploying components of multi -tier applications using separate virtual machines (VMs), is a common \u27best\u27 practice. Various advantages cited include simpler deployment architectures, easier resource scalability for supporting dynamic application throughput requirements, and support for component-level fault tolerance . This paper presents results from an empirical study which investigates the performance implications of component placement for deployments of multi -tier applications to Infrastructure-as-a- Service (IaaS) clouds. Relationship s between performance and resource utilization (CPU, disk, network) are investigated to better understand the implications which result from how applications are deployed. All possible deployments for two variants of a multi -tier application were tested, one computationally bound by the model, the other bound by a geospatial database. The best performing deployments required as few as 2 VMs, half the number required for service isolation, demonstrating potential cost savings with service consolidation. Resource use (CPU time, disk I/O, and network I/O) varied based on component placement and VM memory allocation. Using separate VMs to host each application component resulted in performance overhead of ~1 -2%. Relationships between resource utilization an d performance were harnessed to build a multiple linear regression model to predict performance of component deployments. CPU time, disk sector reads, and disk sector writes are identified as the most powerful performance predictors for component deployments
