Microservices Architecture for Modern Digital Platforms
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Software Architecture: Past, Present, Future
Software Architecture: Past, Present, Future Wilhelm Hasselbring 1 Introduction For large, complex software systems, the design of the overall system structure (the software architecture) is an essential challenge. The architecture of a software system defines that system in terms of components and connections among those components [55, 58]. It is not the design of that system which is more detailed. The architecture shows the correspondence between the requirements and the constructed system, thereby providing some rationale for the design decisions. This level of design has been addressed in a number of ways including informal diagrams and descriptive terms, module interconnection languages, and frameworks for systems that serve the needs of specific application domains. An architecture embodies decisions about quality properties. It represents the earliest opportunity for evaluating those decisions. Furthermore, reusability of components and services depends on how strongly coupled they are with other components in the system architecture. Performance, for instance, depends largely upon the complexity of the required coordination, in particular when the components are distributed via some network. The architecture is usually the first artifact to be examined when a programmer (particularly a maintenance programmer) unfamiliar with the system begins to work on it. Software architecture is often the first design artifact that represents decisions on how requirements of all types are to be achieved. As the manifestation of early design decisions, it represents design decisions that are hardest to change and hence most deserving of careful consideration. W. Hasselbring () Kiel University, Kiel, Germany e-mail: [email protected] © The Author(s) 2018 169 V. -
Reseller Approved Manufacturer(S)
Reseller Approved Manufacturer(s) 1Plus1 Technology EMC 5X Technology Red Hat, SAP 6D Global Adobe Accelera Solutions AppSense, EMC, HP, Imprivata, Liquidware Labs, Nutanix, Precise Biometrics, Red Hat, ServiceNow, Tintri, Vmware Adaptive Cyber RSA Adapture F5 Aderas, Inc. Delphix Advanced Computer Concepts Adobe, Condusiv, Gigamon, Nimble, RSA, SafeNet, Symantec, Veritas Advanced Market Place HP, Symantec Advanced Network Management F5, Splunk, VMware Advantaged Solutions SAP Affigent, LLC (Formerly TKCIS) Adobe, Axway, QTS, Salesforce.com, SAP Agilet Solutions Symantec Agosto Google Aikya Incorporated Salesforce.com AITS (Advanced IT Services, LLC) Symantec Akira Technologies Adobe Alamo City Engineering Services, Inc Adobe, AvePoint, Avue, HP, IBM, Imperva, Oblong, Precise Biometrics, Socrata, Tripwire Alchemy Technology Group AppSense Alexander Open Systems (AOS) F5 Alliance Technology Group Symantec Allied Network Solutions Adobe, SAP Alpha Sum Business Machines Adobe, Symantec, Veritas Alpha Technologies Tintri AlphaSix Corp (Synnex) Adobe, Arista, Nutanix, Splunk, Qlik Alvarez & Associates Adobe Amerinet of Michigan F5 AnaVation, LLC Salesforce.com Angus-Hamer, Inc. Adobe Apollo (Group) Information Systems Arista, FireEye Applied Engineering Management Carahsoft CON-SKUs Corp/Vizuri Aprisa Technology Adobe, EMC, RSA, Symantec, Veritas, Vmware Aquila HP, FireEye ARH, LLC EMC, F5, Symantec Assurance Data Imperva Atrion Nimble ATSolutions Inc Nimble August Schell ALL Aurora Adobe, Jama, Symantec Aurotech Veritas Avid Systems Good Technology/Blackberry, Precise Biometrics, RSA B7 ALL BAI Federal / Blackwood Associates Inc FireEye, Gigamon, Infoblox, Splunk BCS Systems Kofax Bear Bridge Symantec, Veritas Bear Data F5 Bell Techlogix Symantec, Vmware BizTech Fusion Box Black Box Network Services Certipath Blue Door Networks Splunk Blue Tech Adobe, Jama, SafeNet, Symantec Bluesource Inc Symantec Buchanan & Edwards EMC, F5, SAP Cambridge Computer Services Nimble Carolina Advanced Digital Infoblox Cask, LLC. -
An Experimental Study on Microservices Based Edge Computing Platforms Qian Qu, Ronghua Xu, Seyed Yahya Nikouei, Yu Chen Dept
1 An Experimental Study on Microservices based Edge Computing Platforms Qian Qu, Ronghua Xu, Seyed Yahya Nikouei, Yu Chen Dept. of Electrical & Computer Engineering, Binghamton University, SUNY, Binghamton, NY 13902, USA fqqu2, rxu22, snikoue1, [email protected] Abstract—The rapid technological advances in the Internet of development and easy deployment among multiple service Things (IoT) allows the blueprint of Smart Cities to become providers. feasible by integrating heterogeneous cloud/fog/edge computing Because of many attractive features, such as good scalabil- paradigms to collaboratively provide variant smart services in our cities and communities. Thanks to attractive features like fine ity, fine granularity, loose coupling, continuous development, granularity and loose coupling, the microservices architecture and low maintenance cost, the microservices architecture has has been proposed to provide scalable and extensible services in emerged and gained a lot of interests both in industry and large scale distributed IoT systems. Recent studies have evaluated academic community [17], [21]. Compared to traditional SOAs and analyzed the performance interference between microser- in which the system is a monolithic unit, the microservices vices based on scenarios on the cloud computing environment. However, they are not holistic for IoT applications given the architecture divides an monolithic application into multiple restriction of the edge device like computation consumption and atomic microservices that run independently on distributed network capacity. This paper investigates multiple microservice computing platforms. Each microservice performs one specific deployment policies on edge computing platform. The microser- sub-task or service, which requires less computation resource vices are developed as docker containers, and comprehensive ex- and reduces the communication overhead. -
Comparing Service- Based Architectures
Comparing Service- based Architectures @neal4d nealford.com 1 agenda Micro Service-oriented Service-based 2 Service-oriented Architecture 3 origins: hubs System B System A System C 4 origins: hubs System B System A System C System D (ftp only) 5 origins: hubs System E (http only) System B System A System C System D (ftp only) 6 origins: hubs System E (http only) System B System A System C System D (ftp only) 7 origins: hubs System E (http only) System B Integration System A Hub System C System D (ftp only) 8 origins: hubs System E (http only) System B Integration System A Hub System C System D (ftp only) 9 origins: hubs System E (http only) System B Integration System A Hub System C System D (ftp only) 10 origins: hubs looks great, but what about single point of failure and performance bottleneck considerations? 11 orchestration hub intelligent hub service oriented architecture / enterprise service bus pattern 12 service-oriented architecture abstraction service taxonomy shared resources middleware interoperability 13 service-oriented architecture business services BS BS BS BS BS BS message bus process choreographer service orchestrator enterprise services ES ES ES ES ES ES application services AS infrastructure services IS 14 service-oriented architecture business services BS BS BS BS BS BS messageabstract bus enterprise-level coarse-grained process choreographer owned and defined by business users data represented as WSDL, BPEL, XML, etc. service orchestrator no implementation - only name, input, and output enterpriseAre we services -
Case Study on Building Data- Centric Microservices
Case Study on Building Data- Centric Microservices Part I - Getting Started May 26, 2020 | Version 1.0 Copyright © 2020, Oracle and/or its affiliates Public DISCLAIMER This document in any form, software or printed matter, contains proprietary information that is the exclusive property of Oracle. Your access to and use of this confidential material is subject to the terms and conditions of your Oracle software license and service agreement, which has been executed and with which you agree to comply. This document and information contained herein may not be disclosed, copied, reproduced or distributed to anyone outside Oracle without prior written consent of Oracle. This document is not part of your license agreement nor can it be incorporated into any contractual agreement with Oracle or its subsidiaries or affiliates. This document is for informational purposes only and is intended solely to assist you in planning for the implementation and upgrade of the product features described. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described in this document remains at the sole discretion of Oracle. Due to the nature of the product architecture, it may not be possible to safely include all features described in this document without risking significant destabilization of the code. TABLE OF CONTENTS DISCLAIMER INTRODUCTION ARCHITECTURE OVERVIEW Before You Begin Our Canonical Application -
Evaluating Service-Oriented and Microservice Architecture Patterns to Deploy Ehealth Applications in Cloud Computing Environment
applied sciences Article Evaluating Service-Oriented and Microservice Architecture Patterns to Deploy eHealth Applications in Cloud Computing Environment Huriviades Calderón-Gómez 1,2 , Luis Mendoza-Pittí 1,2 , Miguel Vargas-Lombardo 2,* , José Manuel Gómez-Pulido 1,3 , Diego Rodríguez-Puyol 3,4,5, Gloria Sención 6 and María-Luz Polo-Luque 3,7 1 Department of Computer Science, University of Alcalá, 28805 Alcalá de Henares, Spain; [email protected] (H.C.-G.); [email protected] (L.M.-P.); [email protected] (J.M.G.-P.) 2 e-Health and Supercomputing Research Group (GISES), Technological University of Panama, 0819-07289 Panama City, Panama 3 Department of Medicine and Medical Specialties, Ramón y Cajal Institute for Health Research (IRYCIS), 28034 Madrid, Spain; [email protected] (D.R.-P.); [email protected] (M.-L.P.-L.) 4 Foundation for Biomedical Research, Hospital Universitario Príncipe de Asturias, 28805 Alcalá de Henares, Spain 5 Department of Medicine and Medical Specialties, University of Alcalá, 28805 Alcalá de Henares, Spain 6 School of Medicine Autonomous, University of Santo Domingo, Santo Domingo 10105, Dominican Republic; [email protected] 7 Department of Nursing and Physiotherapy, University of Alcalá, 28801 Alcalá de Henares, Spain * Correspondence: [email protected] Citation: Calderón-Gómez, H.; Mendoza-Pittí, L.; Vargas-Lombardo, Abstract: This article proposes a new framework for a Cloud-based eHealth platform concept focused M.; Gómez-Pulido, J.M.; on Cloud computing environments, since current and emerging approaches using digital clinical Rodríguez-Puyol, D.; Sención, G.; history increasingly demonstrate their potential in maintaining the quality of the benefits in medical Polo-Luque, M.-L. -
Salesforce Shield
Salesforce Shield Enhance protection, monitoring, and retention of critical Salesforce data Overview The State of Cloud Security Companies of all sizes and industries are using Salesforce across departments to run their businesses faster. As adoption of Salesforce for critical business capabilities grows, monitoring Security and user behavior, tracking changes to data, and preventing data privacy concerns loss is more important than ever. With more sensitive data in are the top the cloud, security and compliance requirements also become inhibitors IT organizations face increasingly complex. Salesforce Shield helps address these when trying to integrate requirements while allowing you to proactively monitor user data for a shared single activity and enforce security policies. view of customers.* Salesforce Shield provides enhanced protection, monitoring, and retention of your critical data stored in Salesforce. Improving security policies and practices is the top • Native Encryption: Natively encrypt your most sensitive data priority for IT teams while retaining critical app functionality including search, over the next 12 to 18 workflow, and validation rules. months.* • Detailed Data & Monitoring: Gain access to detailed performance, security, and usage data for your Salesforce 65% apps in order to monitor critical business data, understand of IT leaders plan on user adoption across your apps, and troubleshoot and increasing data stored in optimize custom application performance. the cloud over the next 12 - 18 months.* • Security Policies: Build flexible, customizable security policies that give IT the power to identify and prevent malicious activity in real time. Retain data history for forensic * Salesforce State of IT level compliance as well as greater operational insights into Report, 2017 your business. -
Splunk Case Study: Familysearch
CASE STUDY FamilySearch Moves to Continuous Delivery and Gains Real-Time Visibility for AWS Migration Industry • Online services • Nonprofit Executive summary Splunk Use Cases • Application delivery Founded over 100 years ago, FamilySearch International is the largest • DevOps genealogy organization in the world, hosting, maintaining and sharing • Cloud solution genealogical records at FamilySearch.org and through over 4,600 fam- • IT operations management ily history centers in 132 countries. FamilySearch needed a way to move • Log management to a continuous delivery model, manage its all-in migration to Amazon Web Services (AWS) and immediately troubleshoot website errors. • Security Since beginning its effort, the organization has seen benefits including: Challenges • Wanted to increase update release frequency • Successful migration from monthly releases to over 900 deploys per day • Needed to monitor and immediately detect • Ability to re-allocate 12 developers to more value-added tasks changes to website to move to a DevOps • Visibility into the AWS environment to support AWS migration strategy model • Issues with troubleshooting and keeping website stable Why Splunk Business Impact FamilySearch planned to move to a continuous delivery model on • Successful migration from monthly releases AWS to increase business agility and more rapidly deliver features to 900 deploys per day to its patrons. To do so, the company needed a monitoring service • Enabled developers to easily see whether or that could immediately detect changes across its website properties not components were healthy following the push of a new release. This service needed to support • Moved to a DevOps model and achieved continuous delivery the cultural change to a DevOps deployment model. -
FN1206: the Path to Operational Enlightenment
Use this if there will be two speakers for your session. FN1206: © 2019 SPLUNK INC. The Path to Operational Enlightenment An Introduction to Wire Data Simon O’Brien Vinu Alazath Principal Sales Engineer | Splunk Software Engineer | Splunk © 2019 SPLUNK INC. During the course of this presentation, we may make forward‐looking statements Forward- regarding future events or plans of the company. We caution you that such statements reflect our current expectations and estimates based on factors currently known to us Looking and that actual events or results may differ materially. The forward-looking statements made in the this presentation are being made as of the time and date of its live Statements presentation. If reviewed after its live presentation, it may not contain current or accurate information. We do not assume any obligation to update any forward‐looking statements made herein. In addition, any information about our roadmap outlines our general product direction and is subject to change at any time without notice. It is for informational purposes only, and shall not be incorporated into any contract or other commitment. Splunk undertakes no obligation either to develop the features or functionalities described or to include any such feature or functionality in a future release. Splunk, Splunk>, Turn Data Into Doing, The Engine for Machine Data, Splunk Cloud, Splunk Light and SPL are trademarks and registered trademarks of Splunk Inc. in the United States and other countries. All other brand names, product names, or trademarks belong to their respective owners. © 2019 Splunk Inc. All rights reserved. © 2019 SPLUNK INC. Agenda Challenges Product Overview Architecture and Deployment Demo Stream futures © 2019 SPLUNK INC. -
From Component-Based Architectures to Microservices: a 25-Years-Long Journey in Designing and Realizing Service-Based Systems
From Component-based Architectures to Microservices: A 25-years-long Journey in Designing and Realizing Service-based Systems Giuseppe De Giacomo[0000−0001−9680−7658], Maurizio Lenzerini[0000−0003−2875−6187], Francesco Leotta[0000−0001−9216−8502], and Massimo Mecella[0000−0002−9730−8882] Sapienza Universit`adi Roma Dipartimento di Ingegneria Informatica Automatica e Gestionale fdegiacomo,lenzerini,leotta,[email protected] Abstract. Distributed information systems and applications are gen- erally described in terms of components and interfaces among them. How these component-based architectures have been designed and im- plemented evolved over the years, giving rise to the so-called paradigm of Service-Oriented Computing (SOC). In this chapter, we will follow a 25-years-long journey on how design methodologies and supporting technologies influenced one each other, and we discuss how already back in the late 90s the ancestors of the SOC paradigm were there, already paving the way for the technological evolution recently leading to mi- croservice architectures and serverless computing. Keywords: components · SOC · middleware technologies · microser- vices · design methodologies 1 Introduction Divide et impera1 describes an approach, relevant to many fields, where, to solve a problem, it is required or advantageous to break or divide what opposes the solution. As an example, in computer science and engineering, it is applied at the level of standalone programs, by organizing codes in functions, classes and libraries, but it is also at the basis of how complex business processes, spanning several departments/offices of the same organization and/or different organizations, are implemented by making different parties collaborating on a computer network [1]. -
Gremlin: Systematic Resilience Testing of Microservices
Gremlin: Systematic Resilience Testing of Microservices Victor Heorhiadi Shriram Rajagopalan Hani Jamjoom Michael K. Reiter Vyas Sekar UNC Chapel Hill IBM T. J. Watson Research IBM T. J. Watson Research UNC Chapel Hill Carnegie Mellon University [email protected] [email protected] [email protected] [email protected] [email protected] Abstract—Modern Internet applications are being disaggre- Company Downtime Postmortem findings gated into a microservice-based architecture, with services Parse.ly, 13 hours Cascading failure due to message bus being updated and deployed hundreds of times a day. The 2015 [25] overload accelerated software life cycle and heterogeneity of language CircleCI, 17 hours Cascading failure due to database over- runtimes in a single application necessitates a new approach 2015 [19] load BBC, 48 hours Cascading failure due to database over- for testing the resiliency of these applications in production in- 2014 [18] load frastructures. We present Gremlin, a framework for systemat- Spotify, Several Cascading failure due to degradation of a ically testing the failure-handling capabilities of microservices. 2013 [26] hours core internal service Gremlin is based on the observation that microservices are Twilio, 10 hours Database failure caused billing service to loosely coupled and thus rely on standard message-exchange 2013 [28] repeatedly bill customers patterns over the network. Gremlin allows the operator to TABLE 1: A subset of recent outages experienced by popular, easily design tests and executes them by manipulating inter- highly available Internet services. Postmortem reports revealed service messages at the network layer. We show how to use missing or faulty failure-handling logic. -
Testing Microservice Applications
Dmitrii Savchenko TESTING MICROSERVICE APPLICATIONS ACTA UNIVERSITATIS LAPPEENRANTAENSIS 868 Dmitrii Savchenko TESTING MICROSERVICE APPLICATIONS Thesis for the degree of Doctor of Science (Technology) to be presented with due permission for public examination and criticism in the Auditorium of the Student Union House at Lappeenranta-Lahti University of Technology LUT, Lappeenranta, Finland on the 18th of October, 2019, at noon. The thesis was written under a joint doctorate agreement between Lappeenranta-Lahti University of Technology LUT, Finland and South Ural State University, Russia and jointly supervised by supervisors from both universities. Acta Universitatis Lappeenrantaensis 868 Supervisors Adjunct Professor Ossi Taipale LUT School of Engineering Science Lappeenranta-Lahti University of Technology LUT Finland Associate Professor Jussi Kasurinen LUT School of Engineering Science Lappeenranta-Lahti University of Technology LUT Finland Associate Professor Gleb Radchenko School of Electrical Engineering and Computer Science Department of System Programming Federal State Autonomous Educational Institution of High Education South Ural State University (National Research University) Russian Federation Reviewers Professor Timo Mantere Dept. of Electrical Engineering and Automation University of Vaasa Finland Professor Markku Tukiainen School of Computing University of Eastern Finland Joensuu Finland Opponent Professor Ita Richardson Lero - The Irish Software Research Centre University of Limerick Ireland ISBN 978-952-335-414-2 ISBN 978-952-335-415-9 (PDF) ISSN 1456-4491 ISSN-L 1456-4491 Lappeenranta-Lahti University of Technology LUT LUT University Press 2019 Abstract Dmitrii Savchenko Testing microservice applications Lappeenranta, 2019 59 p. Acta Universitatis Lappeenrantaensis 868 Diss. Lappeenranta-Lahti University of Technology LUT ISBN 978-952-335-414-2, ISBN 978-952-335-415-9 (PDF), ISSN-L 1456-4491, ISSN 1456- 4491 Software maintenance costs are growing from year to year because of the growing soft- ware complexity.