Dynamic resource provisioning aims at maintaining the end-to-end response time of a web application within a pre-defined SLA. Although the topic has been well studied for monolithic applications, provisioning resources for applications composed of multiple services remains a challenge. When the SLA is violated, one must decide which service(s) should be reprovisioned for optimal effect. We propose to assign an SLA only to the front-end service. Other services are not given any particular response time objectives. Services are autonomously responsible for their own provisioning operations and collaboratively negotiate performance objectives with each other to decide the provisioning service(s). We demonstrate through extensive experiments that our system can add/remove/shift both servers and caches within an entire multi-service application under varying workloads to meet the SLA target and improve resource utilization.

Many techniques have been proposed to scale web applications. However, the data interdependencies between the database queries and transactions issued by the applications limit their efficiency. We claim that major scalability improvements can be gained by restructuring the web application data into multiple independent data services with exclusive access to their private data store. While this restructuring does not provide performance gains by itself, the implied simplification of each database workload allows a much more efficient use of classical techniques. We illustrate the data denormalization process on three benchmark applications: TPC-W, RUBiS and RUBBoS. We deploy the resulting service-oriented implementation of TPC-W across an 85-node cluster and show that restructuring its data can provide at least an order of magnitude improvement in the maximum sustainable throughput compared to master-slave database replication, while preserving strong consistency and transactional properties.