DOCSLIB.ORG

IBM Linuxone and Linux on Z Systems SOA

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
IBM Linuxone and Linux on Z Systems SOA The new Linux on z Ecosystem opens new horizons Wilhelm Mild Executive IT Architect Integration Architectures for Mobile, Linux & z Systems © Copyright IBM ©Corporation Copyright 2017. IBM Technical Corporation University/Symposia 2017 materials may not be reproduced in whole or in 1 part without the prior written permission of IBM. New marketplace dynamics drive hyper growth opportunity for the IBM Mainframe CAMSS Traditional 1964–2014 • Batch • General Ledger • Transaction Systems • Client Databases • Accounts payable / receivable 1 Open • Inventory, CRM, ERP Systems Linux & Java MIPS 1999–2014 • Server Consolidation Traditional • Oracle Consolidation • Early Private Clouds • Email • Java®, Web & eCommerce 2 1964 1999 2014 2020 CAMSS 2015–2020 • On/Off Premise, Hybrid Cloud 15 years of Enterprise Linux® ™ • Big Data & Analytics on IBM z Systems • Enterprise Mobile Apps • Security solutions • Open Source ecosystem enhancement 1. MIPS: Millions of Instructions per Second or the metric z uses to measure client workload 2. CAMSS: Cloud, Analytics, Mobile, Social, Security Open source participation is important to the IBM Strategy 2015 62k+ IBMers contributing to 150+ Open Orgs Founder & Platinum Sponsor IBM is a top-3 contributor in the past 4 releases Founder & Platinum Sponsor IBM has 450+ developers & 20 core A Dramatic Commitment to Open Technology ! IBM has the largest Cloud reviewers Foundry deployment IBM has 10 dedicated core IBM a founding contributors member of the newly Leading dev of nightly established builds for x86, Power & foundation Mainframe systems 2.1b npm downloads #2 in Commits in 2015 in the past month behind Docker Donation of IBM SystemML machine IBM pledged 3,500 devs 5 IBMers contributing to IBM is a founding to Spark across 12 labs member Education for 1m + data Linux & Apache Projects 500+ organizations scientists & engineers on participating Spark. Provides customer-led guidance to cloud 1999 standards-defining orgs Open Source in the Enterprise https://www.blackducksoftware.com/future-of-open-source Ecosystem Strategy HOW - How are we planning to achieve these objectives? Aim: To create a single view of all the IBM and ISV vendors for z Systems: • Evaluating - target list based on our knowledge to date and requests from field Client zChamp Feedback Feedback • Progressing -discussions around porting, or porting underway Seller feedback • Completed - ongoing currency focus ie. Distros, required here • Have dropped - low interest or not suited to Process to Capture z Systems architecture this feedback & prioritize it Linux your Way - Greater flexibility and choice Choose the distribution, runtime, hypervisor, database and analytics – it’s the Linux you know and love with the openness, flexibility and agility you need for you business. Distributions Hypervisors Languages Runtimes Management Other Database Analytics vRealize Cloud Manager Community Versions DB2 Open Source & ISV Linux SW Capability Languages and Dev Environment Databases Messaging & Streaming Ported - verified Work in progress (target quarter/half) Node.js MySQL RabbitMQ Work under Evaluation/not started Ruby PostgreSQL Apache Kafka Rails MariaDB Logstash (ELK) Python, PyPy Python JIT MongoDB Fluentd LLVM Redis Apache Flume OpenJDK, OpenJDK 9 JIT build Apache CouchDB Apache ActiveMQ OpenJDK 9 JIT(3Q17) Cloudant^ (CouchDB GCCGO, Golang compiler Graylog2* based) oCaml, oCaml native compiler Apache Geode Apache Apex(Data Torrent)* Erlang CouchBase Apache NiFi* PHP/Zend Apache HBase IronMQ* R ScyllaDB(1Q17) Apache Camel* Clojure RethinkDB Scala HAWQ (2H17) Graph DBs Swift (Apple) OrientDB* Spark GraphX BIRT (Eclipse plug-in) Hazelcast* Neo4j Mono(C#...) [open source for .NET] MemSQL* Pegasus* GOLD(alternate Linux linker) Aerospike* Titan* ATLAS BLAS(z13 SIMD Vector Druid* Extension) * Pending input on priority LuaJIT Apache Ignite* ^ IBM offering Rust*, JIT* for PHP, Dart* * Content and priority are subject to change Various sources of input: e.g. BlueMix, Github stats, feedback from: direct client input, IBM client reps, on going research Open Source & ISV Linux SW Capability Orchestration/ Deployment Management & Machine & Deep Learning Operating Systems Ported - verified Deployment Config - Monitoring Work in progress (target quarter/half) Work under Evaluation/not started Docker Chef Spark MLLib SLES <enterprise> Docker Swarm Puppet Word2vec RHEL <enterprise> Docker Compose Ansible TensorFlow Ubuntu <enterprise> EigenBLAS(z13 SIMD Kubernetes virt-install Debian Vector Extension) LXD Consul SystemML* Fedora Apache Mesos cAdvisor H2O* ClefOS (CentOS) Marathon Etcd Neon* OpenSUSE* Chronos Apache ZooKeeper Apache SINGA* CoreOS* Mesosphere (DC/OS) Sysdig IaaS & PaaS RancherOS* (1H17) SaltStack Heapster OpenStack SDN(Networking) Exechealthz Zenoss* Cloud Foundry local Onos (2Q17) Flannel ElasticBox* OpenShift OpenContrail* kube-dnsmasq Icinga 2* Juju OpenDaylight* Calico (2Q17) DataDog* Deis Open vSwitch* * Pending input on priority Docker Machine* ^ IBM offering Docker Kitematic* * Content and priority are subject to change Various sources of input: e.g. BlueMix, Github stats, feedback from: direct client input, IBM client reps, on going research Open Source & ISV Linux SW Capability Ported - verified Work in progress (target quarter/half) Work under Evaluation/not started App development & Web Application Dev/Perf & Big Data & Analytics DevOps CMS Front End Elasticsearch (ELK) Xerces-c Apache jMeter Kibana (ELK) Apache Spark XMLSec Wordpress D3 Apache Solr protobuf Ceilometer Angular (MEAN) Apache Storm Doxygen Apache Tomcat Express (MEAN) Anaconda (3Q17) ANTLR HAProxy Beats Apache Maven NGNIX Grafana Jenkins Apache HTTP(utils) Ionic* Notebooks Apigility JBoss Graphene* Apache Zeppelin* Mule Drupal Meteor* Jupyter* PM2 Joomla Ipython* Htop SugarCRM Graphite* IPTraf Magento Hibernate Alfresco SonarQube (2Q17) OpenResty TomEE* * Pending input on priority ^ IBM offering * Content and priority are subject to change Various sources of input: e.g. BlueMix, Github stats, feedback from: direct client input, IBM client reps, on going research Open Source & ISV Linux SW Capability Sample popular Tools and Applications* that have been verified by Sine Nomine Associates. Following links provide more details and most up to date lists: http://www.sinenomine.net/products/mainframe-linux/ClefOS_6-packages http://www.sinenomine.net/products/mainframe-linux/ClefOS_7-packages App development System System System Distro & DevOps productivity tools configuration tools libraries pigz Bacula phpMyAdmin db4 ClefOS (CentOS) autossh ipsec-tools webmin freetds eXtplorer-mod Mono/.net netcat dhcp_probe libibverbs php-mcrypt openVPN lightttpd libapreq2 GeoIP php-pear-DB ossec-hids mod-rpaf libmcrypt php-php-gettext h3270 thttpd libnet mock s3270 scsi-target-utils libsodium Perl Tools(e.g. perl- libapreq2, perl- HAO openpgm Net-Ping…) heartbeat pkcs11-helper Regina & Rexx zeromq * Content and priority are subject to change Linux on z Systems Technology: Not a “box” but “Linux Your Way” “Linux Your Way” means a commitment to: An Open Source Ecosystem Unmatched TCA with unmatched scale The best performance Agility in Development Development Process Application Deployment Application Architecture Packaging Infrastructure Datacenter Physical Servers Waterfall Monolithic Hosted N-Tier Virtual Machines DevOps Microservices Containers Cloud What is DevOps DevOps - Enterprise capability for continuous service delivery that enables clients to seize market opportunities and reduce time to customer feedback. DevOps Lifecycle Customers Business Owners Development/Test Operations/Production Plan and Measure Develop and Test Release and Deploy Monitor and Optimize Continuous Innovation, Feedback and Improvements Accelerate Software Delivery – i.e Open source Ansible , Jenkins Expanding collaboration to include customers, LOB and others to eliminate organization silos Balance speed, cost, quality and risk Automating manual processes across delivery lifecycle to eliminate waste/delays and compliance tracking Reduce time to customer feedback Enabling a customer feedback loop for continuous improvement Microservices and APIs: Flexibility and Standardization Freedom to choose runtimes, languages, datastores etc. API API • Wise to encourage preferred technologies. • Convergence often happens naturally. Microservice Flexibility in terms of: (Node.js) • Interconnectivity Microservice • Governance (Java + API MongoDB) • Scalability Microservice (Java + DB2) APIs provides: • Standard interfaces Microservices application • Simple integration Approaches for Application Deployment Virtualization vs. Containers Virtualization – Infrastructure oriented OpenStack Mongo DB App 2 App n • Customers have virtualized their servers to gain efficiencies (running in (running in (running in . (running in a Guest VM) Guest VM 1) Guest VM 2) Guest VM n) • Focus is on virtual server resource management OS Kernel OS Kernel OS Kernel OS Kernel • One or several application per Guest VM / Operating System instance, as previously on physical servers Hypervisor • Provides application isolation - an application or guest failing or Infrastructure misbehaving does not adversely affect other applications residing Virtual Virtual Virtual in other Guest VMs Network Compute Storage • Provides persistence across server restarts. App 1 App 2 App n (WAS) Mongo . Containers and Docker - Service oriented (running in (running in (running in container 1) container 2) container n) • Application-centric - infrastructure resources
Load more

Recommended publications
  • Oracle Metadata Management V12.2.1.3.0 New Features Overview
    An Oracle White Paper October 12 th , 2018 Oracle Metadata Management v12.2.1.3.0 New Features Overview Oracle Metadata Management version 12.2.1.3.0 – October 12 th , 2018 New Features Overview Disclaimer This document is for informational purposes. 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. This document in any form, software or printed matter, contains proprietary information that is the exclusive property of Oracle. 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. 1 Oracle Metadata Management version 12.2.1.3.0 – October 12 th , 2018 New Features Overview Table of Contents Executive Overview ............................................................................ 3 Oracle Metadata Management 12.2.1.3.0 .......................................... 4 METADATA MANAGER VS METADATA EXPLORER UI .............. 4 METADATA HOME PAGES ........................................................... 5 METADATA QUICK ACCESS ........................................................ 6 METADATA REPORTING .............................................................
    [Show full text]
  • IBM Z Systems Introduction May 2017
    IBM z Systems Introduction May 2017 IBM z13s and IBM z13 Frequently Asked Questions Worldwide ZSQ03076-USEN-15 Table of Contents z13s Hardware .......................................................................................................................................................................... 3 z13 Hardware ........................................................................................................................................................................... 11 Performance ............................................................................................................................................................................ 19 z13 Warranty ............................................................................................................................................................................ 23 Hardware Management Console (HMC) ..................................................................................................................... 24 Power requirements (including High Voltage DC Power option) ..................................................................... 28 Overhead Cabling and Power ..........................................................................................................................................30 z13 Water cooling option .................................................................................................................................................... 31 Secure Service Container .................................................................................................................................................
    [Show full text]
  • Apache Log4j 2 V
    ...................................................................................................................................... Apache Log4j 2 v. 2.4.1 User's Guide ...................................................................................................................................... The Apache Software Foundation 2015-10-08 T a b l e o f C o n t e n t s i Table of Contents ....................................................................................................................................... 1. Table of Contents . i 2. Introduction . 1 3. Architecture . 3 4. Log4j 1.x Migration . 10 5. API . 16 6. Configuration . 19 7. Web Applications and JSPs . 50 8. Plugins . 58 9. Lookups . 62 10. Appenders . 70 11. Layouts . 128 12. Filters . 154 13. Async Loggers . 167 14. JMX . 181 15. Logging Separation . 188 16. Extending Log4j . 190 17. Programmatic Log4j Configuration . 198 18. Custom Log Levels . 204 © 2 0 1 5 , T h e A p a c h e S o f t w a r e F o u n d a t i o n • A L L R I G H T S R E S E R V E D . T a b l e o f C o n t e n t s ii © 2 0 1 5 , T h e A p a c h e S o f t w a r e F o u n d a t i o n • A L L R I G H T S R E S E R V E D . 1 I n t r o d u c t i o n 1 1 Introduction ....................................................................................................................................... 1.1 Welcome to Log4j 2! 1.1.1 Introduction Almost every large application includes its own logging or tracing API. In conformance with this rule, the E.U.
    [Show full text]
  • Machine Learning and Deep Learning for IIOT
    Machine Learning and Deep Learning for IIOT Chanchal Chatterjee, Dell EMC Reston, March 22 2016 1 Goals of the Meeting ➢ Provide insights on methods and systems for machine learning and deep learning. ➢ Provide machine/deep learning use cases for IIOT. ➢ Provide architectures and frameworks for machine/deep learning for IIOT. 2 Machine Learning & Deep Learning – Confusing, Eh! From Machine Learning Mastery (http://machinelearningmastery.com/) 3 Machine Learning and Deep Learning Dependencies • Types of Data • Types of Learning • Types of Algorithms 4 Types of Data • Structured Data • Time Series • Events • Graph • Unstructured Data • Video/Images • Voice • Text 5 Types of Learning • Un-Supervised • Do not require training data • Assume normal instances far more frequent than anomalies • Semi-Supervised • Training data has labeled instances for only the normal class • Assume normal instances far more frequent than anomalies • Supervised 6 Types of Algorithms • ML: Machine Learning • Anomaly Detection • Trends, Predictions & Forecasting • Association & Grouping • DL: Deep Learning • Ladder Network • Convolutional Neural Network • Recurrent Neural Network • Deep Belief Networks 7 Some Details 8 Machine Learning • Anomaly Detection • Point Anomaly • Contextual Anomaly • Collective Anomaly • Graph Anomaly • Trends, Predictions & Forecasting • Associations & Grouping 9 Deep Learning • Ladder Network • Convolutional NN (CNN) • Recurrent NN (RNN) • Recurrent Recursive NN (R2NN) • Long Short Term Memory (LSTM) • Deep Belief Networks (DBM) • Restricted
    [Show full text]
  • Introducing Linux on IBM Z Systems IT Simplicity with an Enterprise Grade Linux Platform
    Introducing Linux on IBM z Systems IT simplicity with an enterprise grade Linux platform Wilhelm Mild IBM Executive IT Architect for Mobile, z Systems and Linux © 2016 IBM Corporation IBM Germany What is Linux? . Linux is an operating system – Operating systems are tools which enable computers to function as multi-user, multitasking, and multiprocessing servers. – Linux is typically delivered in a Distribution with many useful tools and Open Source components. Linux is hardware agnostic by design – Linux runs on multiple hardware architectures which means Linux skills are platform independent. Linux is modular and built to coexist with other operating systems – Businesses are using Linux today. More and more businesses proceed with an evolutionary solution strategy based on Linux. 2 © 2016 IBM Corporation What is IBM z Systems ? . IBM z Systems is the family name used by IBM for its mainframe computers – The z Systems families were named for their availability – z stands for zero downtime. The systems are built with spare components capable of hot failovers to ensure continuous operations. IBM z Systems paradigm – The IBM z Systems family maintains full backward compatibility. In effect, current systems are the direct, lineal descendants of System/360, built in 1964, and the System/370 from the 1970s. Many applications written for these systems can still run unmodified on the newest z Systems over five decades later. IBM z Systems variety of Operating Systems – There are different traditional Operating Systems that run on z Systems like z/OS, z/VSE or TPF. With z/VM IBM delivers a mature Hypervisor to virtualize the operating systems.
    [Show full text]
  • Chainsys-Platform-Technical Architecture-Bots
    Technical Architecture Objectives ChainSys’ Smart Data Platform enables the business to achieve these critical needs. 1. Empower the organization to be data-driven 2. All your data management problems solved 3. World class innovation at an accessible price Subash Chandar Elango Chief Product Officer ChainSys Corporation Subash's expertise in the data management sphere is unparalleled. As the creative & technical brain behind ChainSys' products, no problem is too big for Subash, and he has been part of hundreds of data projects worldwide. Introduction This document describes the Technical Architecture of the Chainsys Platform Purpose The purpose of this Technical Architecture is to define the technologies, products, and techniques necessary to develop and support the system and to ensure that the system components are compatible and comply with the enterprise-wide standards and direction defined by the Agency. Scope The document's scope is to identify and explain the advantages and risks inherent in this Technical Architecture. This document is not intended to address the installation and configuration details of the actual implementation. Installation and configuration details are provided in technology guides produced during the project. Audience The intended audience for this document is Project Stakeholders, technical architects, and deployment architects The system's overall architecture goals are to provide a highly available, scalable, & flexible data management platform Architecture Goals A key Architectural goal is to leverage industry best practices to design and develop a scalable, enterprise-wide J2EE application and follow the industry-standard development guidelines. All aspects of Security must be developed and built within the application and be based on Best Practices.
    [Show full text]
  • Maîtriser Apache Jmeter Du Test De Charge À Devops
    Maîtriser Apache JMeter Du test de charge à Devops Antonio Gomes Rodrigues, Bruno Demion (Milamber) et Philippe Mouawad Ce livre est en vente à http://leanpub.com/maitriser-jmeter-du-test-de-charge-a-devops Version publiée le 2018-09-30 ISBN 978-2-9555036-1-4 Ce livre est publié par Leanpub. Leanpub permet aux auteurs et aux éditeurs de bénéficier du Lean Publishing. Lean Publishing consiste à publier à l’aide d’outils très simples de nombreuses itérations d’un livre électronique en cours de rédaction, d’obtenir des retours et commentaires des lecteurs afin d’améliorer le livre. © 2014 - 2018 Antonio Gomes Rodrigues, Bruno Demion (Milamber) et Philippe Mouawad Tweet ce livre ! S’il vous plaît aidez Antonio Gomes Rodrigues, Bruno Demion (Milamber) et Philippe Mouawad en parlant de ce livre sur Twitter ! Le tweet suggéré pour ce livre est : Je viens d’acheter Maîtriser Apache JMeter : Du test de charge à #Devops par @ra0077, @milamberspace, @philmdot sur https ://leanpub.com/maitriser-jmeter-du-test-de-charge-a-devops Le hashtag suggéré pour ce livre est #jmeter. Découvrez ce que les gens disent à propos du livre en cliquant sur ce lien pour rechercher ce hashtag sur Twitter : #jmeter Couverture et quatrième de couverture conçues par Cécile Platteeuw (C’grafic) Table des matières Droits ............................................ 1 Présentation des auteurs ................................ 2 Antonio Gomes Rodrigues ............................. 2 Bruno Demion (Milamber) ............................. 2 Philippe Mouawad (Philippe M.) ......................... 3 L’écosystème d’Apache JMeter ............................ 5 Introduction ...................................... 5 Plugin polyvalent ................................... 5 JMeter Plugins .................................. 5 JMeter dans le cloud ................................. 18 BlazeMeter .................................... 19 Tricentis Flood .................................. 23 Redline 13 ...................................
    [Show full text]
  • 2020 Linux on IBM Z and Linuxone Client Workshop November 9-13
    2020 Linux on IBM Z and LinuxONE Client Workshop November 9-13 Securing Workloads with Red Hat OpenShift Container Platform on IBM Z / LinuxONE — Pradeep Parameshwaran Security & Compliance Lead, Linux on IBM Z & LinuxONE [email protected] Linux on IBM Z and LinuxONE Client WS 2020 / © 2020 IBM Corporation Contents • Why OpenShift on IBM Z ? • The cloud with the Privacy and Security • Deployment architecture: OpenShift on IBM Z • Security blueprint: OpenShift on IBM Z • Summary of native and augmented security capabilities IDC estimates that 71% of organizations are in the process of implementing containers and orchestration or are already using them regularly. Containers are the next generation of software-defined compute that enterprises will leverage to accelerate their digital transformation initiatives,” says Gary Chen, Research Director at IDC. “IDC estimates that 71% of organizations are in the process of implementing containers and orchestration or are already using them regularly, and IDC forecasts that the worldwide container infrastructure software opportunity is growing at a 63.9 % 5-year CAGR and is predicted to reach over $1.5B by 2022. 3 Why Red Hat OpenShift on IBM Z? OpenShift a smart Kubernetes platform 5 Build once • Fully integrated and automated architecture • Seamless Kubernetes deployment on any cloud or on-premises environment • Fully automated installation, from cloud infrastructure to OS to application services • One click platform and application updates • Auto-scaling of cloud resources • Enterprise-grade security
    [Show full text]
  • Bigchaindb Server Documentation Release 1.2.0
    BigchainDB Server Documentation Release 1.2.0 BigchainDB Contributors Nov 13, 2017 Contents 1 Introduction 1 2 Quickstart 3 3 Production Nodes 5 4 Clusters 13 5 Production Deployment Template 15 6 Develop & Test BigchainDB Server 65 7 Settings & CLI 73 8 The HTTP Client-Server API 85 9 The Events API 103 10 Drivers & Tools 107 11 Data Models 109 12 Transaction Schema 117 13 Vote Schema 121 14 Release Notes 123 15 Appendices 125 Python Module Index 169 HTTP Routing Table 171 i ii CHAPTER 1 Introduction This is the documentation for BigchainDB Server, the BigchainDB software that one runs on servers (but not on clients). If you want to use BigchainDB Server, then you should first understand what BigchainDB is, plus some of the spe- cialized BigchaindB terminology. You can read about that in the overall BigchainDB project documentation. Note that there are a few kinds of nodes: •A dev/test node is a node created by a developer working on BigchainDB Server, e.g. for testing new or changed code. A dev/test node is typically run on the developer’s local machine. •A bare-bones node is a node deployed in the cloud, either as part of a testing cluster or as a starting point before upgrading the node to be production-ready. •A production node is a node that is part of a consortium’s BigchainDB cluster. A production node has the most components and requirements. 1.1 Setup Instructions for Various Cases • Quickstart • Set up a local BigchainDB node for development, experimenting and testing • Set up and run a BigchainDB cluster There are some old RethinkDB-based deployment instructions as well: • Deploy a bare-bones RethinkDB-based node on Azure • Deploy a RethinkDB-based testing cluster on AWS Instructions for setting up a client will be provided once there’s a public test net.
    [Show full text]
  • IBM Cloud Private with Linux on Z
    IBM Cloud Solution Brief IBM Cloud Private with Linux on IBM Z Empower how you build, deploy and manage cloud-native applications Introduction Highlights Many organizations have unique data sensitivity needs, such as internal policies, government regulations or industry compliance requirements. • Offers the benefits of a public cloud on a security-rich, scalable private cloud As a result, these organizations typically require private cloud. Yet in a platform for developing and delivering world of changing business demands, they also need to run demanding cloud-native apps applications and use multiple services both on-premise and on multiple • Helps make heritage applications cloud- clouds for the sake of agility. ready • Helps protect confidential and proprietary IBM Cloud™ Private with Linux® on IBM Z® provides the advantages of a Kubernetes and Docker workloads with IBM Secure Service Containers private cloud on a server platform optimized for data and cognitive • Enables organizations to build new services, and is designed to deliver the benefits of a public cloud in a microservice-based apps for improved security-rich, scalable and reliable environment. It enables enterprises to agility and innovation accelerate innovation using modern agile processes, integrates with • Designed to more securely use data and existing systems, and provides a strategic platform for multi-cloud services from external private cloud integration while maintaining the control and compliance that sources organizations need. • Supports heavy workloads with thousands of parallel users and thousands of Linux servers–in one box Connect almost anything on premise and in cloud IBM Cloud Private gives developers and IT operations a combination of critical capabilities to transform the enterprise.
    [Show full text]
  • Studying Dependency Updates and a Framework for Multi-Versioning in Docker Containers by Sara Gholami Ghasem Abad
    Studying Dependency Updates and a Framework for Multi-Versioning in Docker Containers by Sara Gholami Ghasem Abad A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Software Engineering and Intelligent Systems Department of Electrical and Computer Engineering University of Alberta © Sara Gholami Ghasem Abad, 2020 Abstract Containerized software systems are becoming more popular and complex as they are one of the essential techniques that enable cloud computing. One of the enabling technologies for containerized software systems is the Docker framework. Docker is an open-source framework for deploying containers, lightweight, standalone, and executable units of software with all their dependencies (packages and libraries) that can run on any computing environment. Docker images facilitate deploying and upgrading systems as all of the dependencies required for a software package are included in an image. However, there exist several risks with running Docker images in production environments. One risky situation can occur when upgrading images, as an upgrade may result in many changing packages or libraries at once. Therefore, in this thesis, we study the Docker images and analyze them to identify the risks of package changes. Also, we propose our solution, DockerMV, to mitigate this risk by running multiple versions of an image at the same time. In this first part of this thesis, we analyze the official Docker image repositories that are available on Docker Hub, Docker’s public registry that holds Docker images. For each image in these repositories, we extract details about its native, Node, and Python packages. Afterward, we investigate which types of applications have more package changes in their image upgrades.
    [Show full text]
  • D3.2 - Transport and Spatial Data Warehouse
    Holistic Approach for Providing Spatial & Transport Planning Tools and Evidence to Metropolitan and Regional Authorities to Lead a Sustainable Transition to a New Mobility Era D3.2 - Transport and Spatial Data Warehouse Technical Design @Harmony_H2020 #harmony-h2020 D3.2 - Transport and SpatialData Warehouse Technical Design SUMMARY SHEET PROJECT Project Acronym: HARMONY Project Full Title: Holistic Approach for Providing Spatial & Transport Planning Tools and Evidence to Metropolitan and Regional Authorities to Lead a Sustainable Transition to a New Mobility Era Grant Agreement No. 815269 (H2020 – LC-MG-1-2-2018) Project Coordinator: University College London (UCL) Website www.harmony-h2020.eu Starting date June 2019 Duration 42 months DELIVERABLE Deliverable No. - Title D3.2 - Transport and Spatial Data Warehouse Technical Design Dissemination level: Public Deliverable type: Demonstrator Work Package No. & Title: WP3 - Data collection tools, data fusion and warehousing Deliverable Leader: ICCS Responsible Author(s): Efthimios Bothos, Babis Magoutas, Nikos Papageorgiou, Gregoris Mentzas (ICCS) Responsible Co-Author(s): Panagiotis Georgakis (UoW), Ilias Gerostathopoulos, Shakur Al Islam, Athina Tsirimpa (MOBY X SOFTWARE) Peer Review: Panagiotis Georgakis (UoW), Ilias Gerostathopoulos (MOBY X SOFTWARE) Quality Assurance Committee Maria Kamargianni, Lampros Yfantis (UCL) Review: DOCUMENT HISTORY Version Date Released by Nature of Change 0.1 02/12/2019 ICCS ToC defined 0.3 15/01/2020 ICCS Conceptual approach described 0.5 10/03/2020 ICCS Data descriptions updated 0.7 15/04/2020 ICCS Added sections 3 and 4 0.9 12/05/2020 ICCS Ready for internal review 1.0 01/06/2020 ICCS Final version 1 D3.2 - Transport and SpatialData Warehouse Technical Design TABLE OF CONTENTS EXECUTIVE SUMMARY ....................................................................................................................
    [Show full text]