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Open AccessProceedings ArticleDOI

Performance Evaluation of Microservices Architectures using Containers

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TLDR
In this article, the authors compare the performance of CPU and network running benchmarks in the two aforementioned models of microservices architecture and provide a benchmark analysis guidance for system designers, which can be used to develop applications based on monolithic architectures where the whole system runs inside a single container or inside a microservices architectures where one or few processes run inside the containers.
Abstract
Microservices architecture has started a new trend for application development for a number of reasons: (1) to reduce complexity by using tiny services; (2) to scale, remove and deploy parts of the system easily; (3) to improve flexibility to use different frameworks and tools; (4) to increase the overall scalability; and (5) to improve the resilience of the system. Containers have empowered the usage of microservices architectures by being lightweight, providing fast start-up times, and having a low overhead. Containers can be used to develop applications based on monolithic architectures where the whole system runs inside a single container or inside a microservices architecture where one or few processes run inside the containers. Two models can be used to implement a microservices architecture using containers: master-slave, or nested-container. The goal of this work is to compare the performance of CPU and network running benchmarks in the two aforementioned models of microservices architecture hence provide a benchmark analysis guidance for system designers.

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Citations
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Proceedings ArticleDOI

A Systematic Mapping Study in Microservice Architecture

TL;DR: This paper presents a systematic mapping study of microservices architectures and their implementation, focusing on identifying architectural challenges, the architectural diagrams/views and quality attributes related to microsevice systems.
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Genetic Algorithm for Multi-Objective Optimization of Container Allocation in Cloud Architecture

TL;DR: This work proposes a genetic algorithm approach, using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), to optimize container allocation and elasticity management, motivated by the good results obtained with this algorithm in other resource management optimization problems in cloud architectures.
Proceedings ArticleDOI

Architectural Patterns for Microservices: A Systematic Mapping Study

TL;DR: It is concluded that different architecture patterns emerge for different migration, orchestration, storage and deployment settings for a set of agreed principles.
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Contextual understanding of microservice architecture: current and future directions

TL;DR: This work provides a detailed analysis of the differences between Service-Oriented Architecture (SOA) and Microservices, and describes both research and industry perspectives on the strengths and weaknesses of both architectural directions.
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Modelling performance & resource management in kubernetes

TL;DR: This work analyzes performance of the Kubernetes system and develops a Reference net-based model of resource management within this system, characterised using real data from a Kuber netes deployment, and can be used as a basis to design scalable applications that make use of Kubernets.
References
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Book

Service-Oriented Architecture: Concepts, Technology, and Design

Thomas Erl
TL;DR: Leading the way to the true service-oriented enterprise, Thomas Erl demystifies the complexities of the open WS-I standards with detailed practical discussions and case studies.
Proceedings ArticleDOI

Mesos: a platform for fine-grained resource sharing in the data center

TL;DR: The results show that Mesos can achieve near-optimal data locality when sharing the cluster among diverse frameworks, can scale to 50,000 (emulated) nodes, and is resilient to failures.
Proceedings ArticleDOI

An updated performance comparison of virtual machines and Linux containers

TL;DR: This paper explores the performance of traditional virtual machine (VM) deployments, and contrast them with the use of Linux containers, using KVM as a representative hypervisor and Docker as a container manager.
Proceedings ArticleDOI

Container-based operating system virtualization: a scalable, high-performance alternative to hypervisors

TL;DR: This paper describes the design and implementation of Linux-VServer, an alternative to hypervisors that is better suited to scenarios that require system virtualization with high degrees of both isolation and efficiency, and shows how Linux- VServer provides comparable support for isolation and superior system efficiency.
Proceedings ArticleDOI

Performance Evaluation of Container-Based Virtualization for High Performance Computing Environments

TL;DR: This work conducted a number of experiments in order to perform an in-depth performance evaluation of container-based virtualization for HPC, and compared them with Xen, which is a representative of the traditional hypervisor-basedvirtualization systems used today.
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