Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World

This report documents the program and the outcomes of GI-Dagstuhl Seminar 16394 "Software Performance Engineering in the DevOps World". The seminar addressed the problem of performance-aware DevOps. Both, DevOps and performance engineering have been growing trends over the past one to two years, in no small part due to the rise in importance of identifying performance anomalies in the operations (Ops) of cloud and big data systems and feeding these back to the development (Dev). However, so far, the research community has treated software engineering, performance engineering, and cloud computing mostly as individual research areas. We aimed to identify cross-community collaboration, and to set the path for long-lasting collaborations towards performance-aware DevOps. The main goal of the seminar was to bring together young researchers (PhD students in a later stage of their PhD, as well as PostDocs or Junior Professors) in the areas of (i) software engineering, (ii) performance engineering, and (iii) cloud computing and big data to present their current research projects, to exchange experience and expertise, to discuss research challenges, and to develop ideas for future collaborations

How blockchain impacts cloud-based system performance: a case study for a groupware communication application

This paper examines the performance trade-off when implementing a blockchain architecture for a cloud-based groupware communication application. We measure the additional cloud-based resources and performance costs of the overhead required to implement a groupware collaboration system over a blockchain architecture. To evaluate our groupware application, we develop measuring instruments for testing scalability and performance of computer systems deployed as cloud computing applications. While some details of our groupware collaboration application have been published in earlier work, in this paper we reflect on a generalized measuring method for blockchain-enabled applications which may in turn lead to a general methodology for testing cloud-based system performance and scalability using blockchain. Response time and transaction throughput metrics are collected for the blockchain implementation against the non-blockchain implementation and some conclusions are drawn about the additional resources that a blockchain architecture for a groupware collaboration application impose

Executable Models and Instance Tracking for Decentralized Applications on Blockchains and Cloud Platforms -- Metamodel and Implementation

Decentralized applications rely on non-centralized technical infrastructures and coordination principles. Without trusted third parties, their execution is not controlled by entities exercising centralized coordination but is instead realized through technologies supporting distribution such as blockchains and serverless computing. Executing decentralized applications with these technologies, however, is challenging due to the limited transparency and insight in the execution, especially when involving centralized cloud platforms. This paper extends an approach for execution and instance tracking on blockchains and cloud platforms permitting distributed parties to observe the instances and states of executable models. The approach is extended with (1.) a metamodel describing the concepts for instance tracking on cloud platforms independent of concrete models or implementation, (2.) a multidimensional data model realizing the concepts accordingly, permitting the verifiable storage, tracking, and analysis of execution states for distributed parties, and (3.) an implementation on the Ethereum blockchain and Amazon Web Services (AWS) using state machine models. Towards supporting decentralized applications with high scalability and distribution requirements, the approach establishes a consistent view on instances for distributed parties to track and analyze the execution along multiple dimensions such as specific clients and execution engines.Comment: This is an unpublished preprint; both versions archived on arXiv.org have not been published. Although initially intended for publication, the preprint has undergone further improvements and has been utilized as input for new publications. (see also: https://www.unifr.ch/inf/digits/en/group/team/haerer.html

CBProf: Customisable Blockchain-as-a-Service Performance Profiler in Cloud Environments

Blockchain technologies, e.g., Hyperledger Fabric and Sawtooth, have been evolving rapidly during past years and enable potential decentralised innovations in a substantial amount of business applications, e.g. crowd journalism, car-sharing and energy trading. The development of decentralised business applications has to face challenges in selecting suitable blockchain technologies, customising network protocols among distributed peers, and optimising system performance to meet application requirements. Also, manually testing and comparing those different technologies are time-consuming. Therefore, an effective tool is needed for profiling the performance characteristics of blockchain services in different cloud environments. In this paper, we present the Customisable Blockchain-as-a-Service Performance Profiler (CBProf), a tool we developed for automating blockchain deployment and performance profiling in cloud environments. We also provide the implementation and functionality demonstration of this tool