Hiranya Jayathilaka

Response time service level agreements for cloud-hosted web applications

Cloud computing is a successful model for hosting web-facing applications that are accessed by their users as services. While clouds currently offer Service Level Agreements (SLAs) containing guarantees of availability, they do not make performance guarantees for deployed applications. In this work we present Cerebro -- a system for establishing statistical guarantees of application response time in cloud settings. Cerebro combines off-line static analysis of application control structure with on-line cloud performance monitoring and statistical forecasting to predict bounds on the response time of web-facing application programming interfaces (APIs). Because Cerebro does not require application instrumentation or per-application cloud benchmarking, it does not impose any runtime overhead, and is suitable for use at cloud scales. Also, because the bounds are statistical, they are appropriate for use as the basis for SLAs between cloud-hosted applications and their users. We investigate the correctness of Cerebro predictions, the tightness of their bounds, and the duration over which the bounds persist in both Google App Engine and AppScale (public and private cloud platforms respectively). We also detail the effectiveness of our SLA prediction methodology compared to other performance bound estimation methods based on simple statistical analysis.

EAGER: Deployment-Time API Governance for Modern PaaS Clouds

To track, control, and compel reuse of web APIs, we investigate a new approach to API governance -- combined policy, implementation, and deployment control of web APIs. Our approach, called EAGER, provides a software architecture that integrates into PaaS platforms to support systemwide, deployment-time enforcement of governance policies. Specifically, EAGER checks for and prevents backward incompatible API changes from being deployed into production PaaS clouds, enforces service reuse, and facilitates enforcement of other best practices in software maintenance via policies. Our experiments with an EAGER prototype show that enforcing API governance at deployment-time in PaaS clouds is efficient and scalable to thousands of APIs and policies.

Service-Level Agreement Durability for Web Service Response Time

Cloud computing is an attractive model for deploying web services in a highly scalable manner. Users access such cloud-hosted services via their web-facing application programming interfaces (APIs). Prior work has shown that it is possible to use a combined approach of static analysis and cloud platform monitoring to predict the response time upper bounds of such web APIs. This technique can be employed to automatically generate service level agreements (SLAs) concerning the performance of cloud-hosted web APIs. In this work, we explore the validity period of auto-generated SLAs in cloud settings. We discuss a simple model by which API consumers can establish a response time SLA with the cloud platform, and renegotiate it when/if the SLA becomes invalid due to the dynamic nature of the cloud. Using empirical methods and simulations on a real world public cloud platform, we show that it is possible to auto-generatehighly durable response time SLAs for cloud-hosted web APIs, thereby keeping the number of SLA invalidations and renegotiations very low, over long periods.