Table of Contents
In this document, we provide links to AppScale publications. This includes the AppScale User Guide as well as number of selected research publications that use AppScale.
AppScale User Guide
Chandra Krintz, Chris Bunch, and Navraj Chohan
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Abstract
In this paper we overview AppScale, an open source cloud platform. AppScale is a distributed and scalable cloud runtime system that executes cloud applications in public, private, and hybrid cloud settings. AppScale implements a set of APIs in support of common and popular cloud services and functionality. This set includes those defined by the Google App Engine public cloud as well as those for large-scale data analytics and high-performance computing.
Our goal with AppScale is to enable research and experimentation into cloud computing and to facilitate a ``write once, run anywhere'' programming model for the cloud, i.e., to expedite portable application development and deployment across disparate cloud fabrics. In this work, we describe the current AppScale APIs and the ways in which users can deploy AppScale clouds and applications in public and private settings. In addition, we describe the internals of the system to give insight into how developers can investigate and extend AppScale as part of research and development on next-generation cloud software and services.
Selected AppScale Research Publications
The following list of selected research publications are in reverse chronological order.
Database-Agnostic Transaction Support for Cloud Infrastructures
Navraj Chohan, Chris Bunch, Chandra Krintz, and Yoshihide Nomura (Fujitsu)
Presented in July 2011 at IEEE CLOUD
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Abstract
In this paper, we present and empirically evaluate the performance of database-agnostic transaction (DAT) support for the cloud. Our design and implementation of DAT is scalable, fault-tolerant, and requires only that the datastore provide atomic, row-level access. Our approach enables applications to employ a single transactional datastore API that can be used with a wide range of cloud datastore technologies. We implement DAT in AppScale, an open-source implementation of the Google App Engine cloud platform, and use it to evaluate DAT’s performance and the performance of a number of popular key-value stores.
Neptune: A Domain Specific Language for Deploying HPC Software on Cloud Platforms
Chris Bunch, Navraj Chohan, Chandra Krintz, and Khawaja Shams (JPL)
Presented in June 2011 at ACM ScienceCloud (Best Paper Award)
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Abstract
In this paper, we present the design and implementation of Neptune, a domain specific language (DSL) that automates configuration and deployment of existing HPC software via cloud computing platforms. We integrate Neptune into a popular, open-source cloud platform, and extend the platform with support for user-level and automated placement of cloud services and HPC components. Such platform integration of Neptune facilitates hybrid-cloud application execution as well as portability across disparate cloud fabrics. Supporting additional cloud fabrics through a single interface enables high throughput computing (HTC) to be achieved by users who do not necessarily own grid-level resources but do have access to otherwise independent cloud technologies. We evaluate Neptune using different applications that employ a wide range of popular HPC packages for their implementation including MPI, X10, MapReduce, DFSP, and dwSSA. In addition, we show how Neptune can be extended to support other HPC software and application domains, and thus be used as a mechanism for many task computing (MTC).
Active Cloud DB: A RESTful Software-as-a-Service for Language Agnostic Access to Distributed Datastores
Chris Bunch, Jonathan Kupferman, and Chandra Krintz
Presented in October 2010 at ICST CloudComp
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Abstract
In this paper, we present Active Cloud DB, an open source Software-as-a-Service (SaaS) application that allows for RESTful access to cloud-based distributed datastore technologies that implement the Google App Engine Datastore API. We implement Active Cloud DB as a Google App Engine application that we employ to expose the Google Datastore API to developers for use with any language and framework. We evaluate this SaaS on both Google App Engine and over AppScale, the open-source implementation of Google App Engine that enables Google App Engine applications to execute on cloud infrastructures without modification. As part of this work, we extend Active Cloud DB with simple caching support to improve the performance of datastore access and evaluate our technique with and without this support. We also make use of this support within multiple client-facing prototypes (e.g. Ruby on Rails, Python through Django) to show the ease-of-use and applicability of our contribution to other web development environments.
An Evaluation of Distributed Datastores Using the AppScale Cloud Platform
Chris Bunch, Navraj Chohan, Chandra Krintz, Jovan Chohan, Jonathan Kupferman, Puneet Lakhina, Yiming Li, and Yoshihide Nomura (Fujitsu)
Presented in July 2010 at IEEE CLOUD
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Abstract
We present new cloud support that employs a single API -- the Datastore API from Google App Engine (GAE) -- to interface to different open source distributed database (DB) technologies. We employ this support to ``plug in'' DB technologies to the API so that they can be used by web applications and services without modification. The system facilitates an empirical evaluation and comparison of these disparate systems by web software developers, and reduces the barrier to entry for their use by automating their configuration and deployment.
AppScale: Scalable and Open App Engine Application Development and Deployment
Navraj Chohan, Chris Bunch, Sydney Pang, Chandra Krintz, Nagy Mostafa, Sunil Soman, and Rich Wolski
Presented in October 2009 at ICST CloudComp
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Slides on SlideShare
Abstract
We present the design and implementation of AppScale, an open source extension to the Google App Engine (GAE) Platform-as-a-Service (PaaS) cloud technology. Our extensions build upon the GAE SDK to facilitate distributed execution of GAE applications over Xen-based clusters, including Infrastructure-as-a-Service (IaaS) cloud systems such as Amazon’s AWS/EC2 and Eucalyptus. AppScale provides a framework with which researchers can investigate the interaction between PaaS and IaaS systems as well as the inner workings of, and new technologies for, PaaS cloud technologies using real GAE applications.