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Exploring the Serverless First Strategy in Cloud Application Development

Exploring the Serverless First Strategy in Cloud Application...

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International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW)

作者： Adriano Prado Cavalheiro Claudio Schepke PPGES - Graduate Program in Software Engineering Federal University of Pampa Alegrete Brazil

This paper explores the Serverless First strategy in cloud application development. Serverless computing has gained popularity due to its flexibility and scalability. In our work, we provide a systematic review of the literature about the Serverless paradigm in cloud computing and an evaluation of the advantages of this approach by performing a comparative analysis among three ways for the implementation of an application: AWS Lambda, AWS Lambda with Chalice framework, and the traditional form using the Flask framework. The literature review results show the gains in scaling, cost reduction, and ease of maintenance achieved with the Serverless First strategy. However, some limitations and challenges were also highlighted, such as the greater complexity of the environment, less control over resources, resource limitations imposed by the cloud provider, and difficulties in debugging and managing the infrastructure. The case study demonstrates in practice that the Chalice framework provided the most straightforward and rapid implementation, the AWS Lambda without Chalice offered greater flexibility and control, and the Flask version allowed local testing and total control but required more manual setup and lacked automatic scalability.

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Assessing the Performance of Docker in Docker Containers for Microservice-Based Architectures

Assessing the Performance of Docker in Docker Containers for...

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Euromicro Conference on Parallel, Distributed and Network-Based Processing

作者： Felipe Bedinotto Fava Luiz Felipe Laviola Leite Luís Fernando Alves Da Silva Pedro Ramires Da Silva Amalfi Costa Angelo Gaspar Diniz Nogueira Amanda Fagundes Gobus Lopes Claudio Schepke Diego Luis Kreutz Rodrigo Brãndao Mansilha Graduate Software Engineering (PPGES) - Laboratory of Advances Studies in Computation (LEA) Federal University of Pampa (UNIPAMPA) Alegrete Brazil

We provide a comprehensive and updated assessment of Docker versus Docker in Docker (DinD), evaluating its impact on CPU, memory, disk, and network. Using different workloads, we evaluate DinD's performance across distinct hardware platforms and GNU/Linux distributions on cloud Infrastructure as a Service (laaS) platforms like Google Compute Engine (GCE) and traditional server-based environments. We developed an automated tools suite to achieve our goal. We execute four well-known benchmarks on Docker and its nested-container variant. Our findings indicate that nested-containers require up to 7 seconds for startup, while the Docker standard containers require less than 0.5 seconds for Debian and Alpine operating systems. Our results suggest that Docker containers based on Debian consistently outperform their Alpine counter-parts, showing lower CPU latency. A key distinction among these Docker images lies in the varying number of installed libraries (e.g., stretching from 13 to 119) across different Linux distributions for the same system (e.g., MySQL). Furthermore, the number of events and CPU latency indicates that the influence of DinD over Docker proves that it is insignificant for both operating systems. In terms of memory, running containers of Debian-based images consume 20% more size of memory than those based on Alpine. No significant differences are between nested-containers and Dockers for disk and network IO. It is worth emphasizing that some of the disparities, such as a bigger memory footprint, appear to be a direct result of the software stack in use, including different kernel versions. libraries. and other essential packages.

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Performance analysis of the Raft consensus algorithm on Hyperledger Fabric and Ethereum on cloud

Performance analysis of the Raft consensus algorithm on Hype...

引用

IEEE International Conference on Cloud Computing Technology and Science (CloudCom)

作者： João H. F. Battisti Vitor E. Batista Guilherme P. Koslovski Maurício A. Pillon Charles C. Miers Marco A. Marques Marcos Simplício Diego Kreutz Graduate Program in Applied Computing (PPGCAP) Santa Catarina State University (UDESC) Brazil Laboratory of Computer Networks and Architecture (LARC) Universidade de São Paulo (USP) Brazil Graduate Program in Software Engineering Federal University of Pampa (Unipampa) Brazil

The use of private or consortium blockchains in organizations’ applications is growing. A relevant aspect of blockchains is the choice of consensus mechanism. This decision delimits which blockchain solutions are suitable for the private scenario. Once the consensus mechanism is chosen, more than one blockchain may be enabled. However, this decision making is not trivial and requires detailed experimental indicators about algorithms and blockchains performance. In this context, we provide a comprehensive performance analysis of the Raft consensus mechanism based on its implementation in Hyperledger Fabric and Ethereum blockchain solutions. We performed our experiments on an OpenStack private cloud using each blockchain developer’s default settings for virtual machines. Our findings show how the implementation of each solution can impact the application’s performance under certain conditions.

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