1,225 research outputs found

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

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    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

    Quantifying and Predicting the Influence of Execution Platform on Software Component Performance

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    The performance of software components depends on several factors, including the execution platform on which the software components run. To simplify cross-platform performance prediction in relocation and sizing scenarios, a novel approach is introduced in this thesis which separates the application performance profile from the platform performance profile. The approach is evaluated using transparent instrumentation of Java applications and with automated benchmarks for Java Virtual Machines

    A QoS registry for adaptive real-time service-oriented applications

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    Real-time service-oriented applications are charac- terized by Quality of Service (QoS) requirements that cannot be properly managed by using classical real-time systems methodologies. In dynamic environments the QoS management can effectively leverage adaptive techniques, that provide flexibility and do not require a complex offline analysis. In turn, such techniques make a massive use of on-line collected data regarding the application performance and the resource requirements. Moreover, a common issue for adaptive systems is the one of deciding the initial configuration of the application and/or the run-time environment at the time of service instantiation. In this paper, we propose a QoS registry for coping with these issues and supporting the configuration of proper scheduling parameters in real-time Service Oriented Architectures (SOAs). The registry permits to gather QoS data related to different functional behaviors of applications, to predict the future trend based on data already collected and to permanently store such data for an effective reuse at the time of future re-instantiations. We have also built an implementation of such registry, computed its overhead costs and performed some experiments for showing the effectiveness in auto-tuning resource allocations for providing QoS guarantees in a real-time SOA

    ProvMark:A Provenance Expressiveness Benchmarking System

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    System level provenance is of widespread interest for applications such as security enforcement and information protection. However, testing the correctness or completeness of provenance capture tools is challenging and currently done manually. In some cases there is not even a clear consensus about what behavior is correct. We present an automated tool, ProvMark, that uses an existing provenance system as a black box and reliably identifies the provenance graph structure recorded for a given activity, by a reduction to subgraph isomorphism problems handled by an external solver. ProvMark is a beginning step in the much needed area of testing and comparing the expressiveness of provenance systems. We demonstrate ProvMark's usefuless in comparing three capture systems with different architectures and distinct design philosophies.Comment: To appear, Middleware 201

    Recursive internetwork architecture, investigating RINA as an alternative to TCP/IP (IRATI)

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    Driven by the requirements of the emerging applications and networks, the Internet has become an architectural patchwork of growing complexity which strains to cope with the changes. Moore’s law prevented us from recognising that the problem does not hide in the high demands of today’s applications but lies in the flaws of the Internet’s original design. The Internet needs to move beyond TCP/IP to prosper in the long term, TCP/IP has outlived its usefulness. The Recursive InterNetwork Architecture (RINA) is a new Internetwork architecture whose fundamental principle is that networking is only interprocess communication (IPC). RINA reconstructs the overall structure of the Internet, forming a model that comprises a single repeating layer, the DIF (Distributed IPC Facility), which is the minimal set of components required to allow distributed IPC between application processes. RINA supports inherently and without the need of extra mechanisms mobility, multi-homing and Quality of Service, provides a secure and configurable environment, motivates for a more competitive marketplace and allows for a seamless adoption. RINA is the best choice for the next generation networks due to its sound theory, simplicity and the features it enables. IRATI’s goal is to achieve further exploration of this new architecture. IRATI will advance the state of the art of RINA towards an architecture reference model and specifcations that are closer to enable implementations deployable in production scenarios. The design and implemention of a RINA prototype on top of Ethernet will permit the experimentation and evaluation of RINA in comparison to TCP/IP. IRATI will use the OFELIA testbed to carry on its experimental activities. Both projects will benefit from the collaboration. IRATI will gain access to a large-scale testbed with a controlled network while OFELIA will get a unique use-case to validate the facility: experimentation of a non-IP based Internet

    Automated Experiments for Deriving Performance-relevant Properties of Software Execution Environments

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    The execution environment can play a crucial role when analyzing the performance of a software system. However, detecting execution environment properties and integrating such properties into performance analyses is a manual, error-prone task. In this thesis, a novel approach for detecting performance-relevant properties of the software execution environment is presented. These properties are automatically detected using predefined experiments and integrated into performance prediction tools

    Enabling portable I/O analysis of commercially sensitive HPC applications through workload replication

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    Benchmarking and analyzing I/O performance across high performance computing (HPC) platforms is necessary to identify performance bottlenecks and guide effective use of new and existing storage systems. Doing this with large production applications, which can often be commercially sensitive and lack portability, is not a straightforward task and the availability of a representative proxy for I/O workloads can help to provide a solution. We use Darshan I/O characterization and the MACSio proxy application to replicate five production workloads, showing how these can be used effectively to investigate I/O performance when migrating between HPC systems ranging from small local clusters to leadership scale machines. Preliminary results indicate that it is possible to generate datasets that match the target application with a good degree of accuracy. This enables a predictive performance analysis study of a representative workload to be conducted on five different systems. The results of this analysis are used to identify how workloads exhibit different I/O footprints on a file system and what effect file system configuration can have on performance

    CloudScope: diagnosing and managing performance interference in multi-tenant clouds

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    © 2015 IEEE.Virtual machine consolidation is attractive in cloud computing platforms for several reasons including reduced infrastructure costs, lower energy consumption and ease of management. However, the interference between co-resident workloads caused by virtualization can violate the service level objectives (SLOs) that the cloud platform guarantees. Existing solutions to minimize interference between virtual machines (VMs) are mostly based on comprehensive micro-benchmarks or online training which makes them computationally intensive. In this paper, we present CloudScope, a system for diagnosing interference for multi-tenant cloud systems in a lightweight way. CloudScope employs a discrete-time Markov Chain model for the online prediction of performance interference of co-resident VMs. It uses the results to optimally (re)assign VMs to physical machines and to optimize the hypervisor configuration, e.g. the CPU share it can use, for different workloads. We have implemented CloudScope on top of the Xen hypervisor and conducted experiments using a set of CPU, disk, and network intensive workloads and a real system (MapReduce). Our results show that CloudScope interference prediction achieves an average error of 9%. The interference-aware scheduler improves VM performance by up to 10% compared to the default scheduler. In addition, the hypervisor reconfiguration can improve network throughput by up to 30%
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