An Experimental Study of Load Balancing of OpenNebula Open-Source Cloud Computing Platform

Cloud Computing is becoming a viable computing solution for services oriented computing. Several open-source cloud solutions are available to these supports. Open-source software stacks offer a huge amount of customizability without huge licensing fees. As a result, open source software are widely used for designing cloud, and private clouds are being built increasingly in the open source way. Numerous contributions have been made by the open-source community related to private-IaaS-cloud. OpenNebula - a cloud platform is one of the popular private cloud management software. However, little has been done to systematically investigate the performance evaluation of this open-source cloud solution in the existing literature. The performance evaluation aids new and existing research, industry and international projects when selecting OpenNebula software to their work. The objective of this paper is to evaluate the load-balancing performance of the OpenNebula cloud management software. For the performance evaluation, the OpenNebula cloud management software is installed and configured as a prototype implementation and tested on the DIU Cloud Lab. In this paper, two set of experiments are conducted to identify the load balancing performance of the OpenNebula cloud management platform- (1) Delete and Add Virtual Machine (VM) from OpenNebula cloud platform; (2) Mapping Physical Hosts to Virtual Machines (VMs) in the OpenNebula cloud platform.Comment: 6 page

Practical tooling for serverless computing

Cloud applications are increasingly built from a mixture of runtime technologies. Hosted functions and service-oriented web hooks are among the most recent ones which are natively supported by cloud platforms. They are collectively referred to as serverless computing by application engineers due to the transparent on-demand instance activation and microbilling without the need to provision infrastructure explicitly. This half-day tutorial explains the use cases for serverless computing and the drivers and existing software solutions behind the programming and deployment model also known as Function-as-a-Service in the overall cloud computing stack. Furthermore, it presents practical open source tools for deriving functions from legacy code and for the management and execution of functions in private and public clouds

Monitoring Large-Scale Cloud Systems with Layered Gossip Protocols

Monitoring is an essential aspect of maintaining and developing computer systems that increases in difficulty proportional to the size of the system. The need for robust monitoring tools has become more evident with the advent of cloud computing. Infrastructure as a Service (IaaS) clouds allow end users to deploy vast numbers of virtual machines as part of dynamic and transient architectures. Current monitoring solutions, including many of those in the open-source domain rely on outdated concepts including manual deployment and configuration, centralised data collection and adapt poorly to membership churn. In this paper we propose the development of a cloud monitoring suite to provide scalable and robust lookup, data collection and analysis services for large-scale cloud systems. In lieu of centrally managed monitoring we propose a multi-tier architecture using a layered gossip protocol to aggregate monitoring information and facilitate lookup, information collection and the identification of redundant capacity. This allows for a resource aware data collection and storage architecture that operates over the system being monitored. This in turn enables monitoring to be done in-situ without the need for significant additional infrastructure to facilitate monitoring services. We evaluate this approach against alternative monitoring paradigms and demonstrate how our solution is well adapted to usage in a cloud-computing context.Comment: Extended Abstract for the ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC 2013) Poster Trac

Towards a Holistic Cloud System with End-to-End Performance Guarantees

Computing technologies are undergoing a relentless evolution from both the hardware and software sides, incorporating new mechanisms for low-latency networking, virtualization, operating systems, hardware acceleration, smart services orchestration, serverless computing, hybrid private-public Cloud solutions and others. Therefore, Cloud infrastructures are becoming increasingly attractive for deploying a wider and wider range of applications, including those with more and more stringent timing constraints, like the emerging use case of deploying time-critical applications. However, despite the availability of a number of public Cloud offerings, and of products (or open-source suites) for deploying in-house private Cloud infrastructures, still there are no solutions readily available for managing time-critical software components with predictable end-to-end timing requirements in the range of hundreds or even tens of milliseconds. The goal of this discussion is to present the multi-domain challenges associated with orchestrating a holistic Cloud system with endto- end guarantees, which is the subject of my current PhD investigations

Towards Process Support for Migrating Applications to Cloud Computing

Cloud computing is an active area of research for industry and academia. There are a large number of organizations providing cloud computing infrastructure and services. In order to utilize these infrastructure resources and services, existing applications need to be migrated to clouds. However, a successful migration effort needs well-defined process support. It does not only help to identify and address challenges associated with migration but also provides a strategy to evaluate different platforms in relation to application and domain specific requirements. This paper present a process framework for supporting migration to cloud computing based on our experiences from migrating an Open Source System (OSS), Hackystat, to two different cloud computing platforms. We explained the process by performing a comparative analysis of our efforts to migrate Hackystate to Amazon Web Services and Google App Engine. We also report the potential challenges, suitable solutions, and lesson learned to support the presented process framework. We expect that the reported experiences can serve guidelines for those who intend to migrate software applications to cloud computing.Muhammad Aufeef Chauhan, Muhammad Ali Baba

Open-source Serverless Architectures: an Evaluation of Apache OpenWhisk

The serverless computing paradigm ushers in new concepts for running applications and services in the cloud. Currently, commercial solutions dominate the market, though open-source solutions do exist. As a consequence of this, there is little research detailing how well the different open-source solutions perform. In this paper, one such open-source solution, Apache OpenWhisk, is investigated to shed light on the capabilities and limitations inherent of such serverless computing architecture, and principally to provide further research on this particular solution's performance. This is accomplished through an extensive evaluation of OpenWhisk, involving a variety of experiments and benchmarks