We present Roots, a full-stack monitoring and analysis system for performance anomaly detection and bottleneck identification in cloud platform-as-a-service (PaaS) systems. Roots facilitates application performance monitoring as a core capability of PaaS clouds, and relieves the developers from having to instrument application code. Roots tracks HTTP/S requests to hosted cloud applications and their use of PaaS services. To do so it employs lightweight monitoring of PaaS service interfaces. Roots processes this data in the background using multiple statistical techniques that in combination detect performance anomalies (i.e. violations of service-level objectives). For each anomaly, Roots determines whether the event was caused by a change in the request workload or by a performance bottleneck in a PaaS service. By correlating data collected across different layers of the PaaS, Roots is able to trace high-level performance anomalies to bottlenecks in specific components in the cloud platform. We implement Roots using the AppScale PaaS and evaluate its overhead and accuracy.

In this paper, we describe Roots - a system for automatically identifying the "root cause" of performance anomalies in web applications deployed in Platform-as-a-Service (PaaS) clouds. Roots does not require application-level instrumentation. Instead, it tracks events within the PaaS cloud that are triggered by application requests using a combination of metadata injection and platform-level instrumentation.

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.

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.

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.

As scalable information technology evolves to a more cloud-like model, digital assets (code, data and software environments) increasingly require curation as web-accessible services. "Service-izing" digital assets consists of encapsulating assets in software that exposes them to web and mobile applications via well-defined yet flexible, network accessible, application programming interfaces (APIs). In this paper, we postulate that recent advances in cloud computing make cloud platforms as-a-service (PaaS) ideal for deployment, lifecycle management, and policy-based control i.e. API governance - for extant and future digital assets. Toward this end, we overview API governance as a PaaS technology and outline some early results generated by our investigation of a prototype we are developing, called EAGER, for implementing API governance at scale.

As the popularity of cloud computing continues to increase, a significant amount of legacy code implemented using older parallel computing standards is outdated and left behind. This forces the organizations to port the old applications into new cloud platforms. This, however, violates the "develop once - run anywhere" principle promised by utility computing. As a solution to this problem, we explore the possibility of executing unmodified MPI applications over a modern parallel computing platform. Using BSP as a bridging model between MPI and the Hadoop framework, we implement a prototype MPI runtime for today's computing clouds, which eliminates the overhead of porting legacy code.

Enterprise Service Bus facilitates message-based communication between modular software components in a SOA application. In addition to message routing, the ESB communication abstraction includes filtering and transformation capabilities that enable composing separate software modules quickly, with minimal code changes. For this reason, this richer communication capability is often termed "mediation".