BEST PRACTICE GUIDE for CLOUD and AS-A-SERVICE PROCUREMENTS Executive Summary 1 Introduction
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Elliptic Curve Cryptography in Cloud Computing Security
Elliptic curve cryptography in cloud computing security Manu Gopinathan ([email protected]) Øyvind Nygard ([email protected]) Kjetil Aune([email protected]) December 1st, 2015 1 Abstract Cloud computing is a technological advancement that has been growing swiftly during the last decade. In simple terms, cloud computing is a technology that enables shared, remote, on-demand and ubiquitous access to services through the Internet. It enables consumers to access applications and services that reside on remote servers, without having to allocate large amounts of storage space on their own computer and without the need for extensive compatibility configurations. Many such cloud applications provide services that are meant to handle sensitive user data and thus the protection of this data in terms of access and integrity is of major concern. Space- and time complexity of encryption algorithms can prove to be imperative when it comes to system performance. In this paper we will briefly present how elliptic curve cryptography (EEC) works, and then describe the advantages of it and how it can be used as an encryption solution to security related issues in cloud computing. 2 Introduction In this section we will briefly describe the notion of cloud computing to aid us in the discussion of ECC in cloud computing later. According to the National Institute of Standards and Technology (NIST), essential characteristics for a service based on the cloud computing model are [1]: 1. On-demand self-service: The consumer can provision service capabilities, such as server time and network storage, without actively interacting with the service provider. 2. -
Software As a Service
Software as a Service Haojie Hang Ogheneovo Dibie Executive Summary • In this presentation, we go through the Software as a Service Methodology, examine its benefits and drawbacks and talk about two state-of-art SaaS systems– Amazon Web Service and Google App Engine • We also look into Service Oriented Architecture powering SaaS applications and its impact on modern web 2.0 applications • Finally, we examine hybrids of traditional and SaaS applications Overview • What is Software as a Service (SaaS) • Background o Brief history o Concept o Big picture o Related terms • Computing Today o SasS is everywhere o The SaaS Market • Benefits of SaaS • Drawbacks of SaaS o Robustness o Privacy o Security o Reliability • Service Oriented Architectures (SOA) o Guiding principles of SOA • Case studies o Amazon Web Services (AWS) o Google App Engine • Influence of SOA on Web 2.0 development o Zend Framework • Hybrids of Traditional and SaaS applications o Dropbox o Microsoft Office • Summary • References What is SaaS? • Definition: Software as a Service (SaaS), a.k.a. on- demand software, is a software delivery model in which software and its associated data are hosted centrally and accessed using a thin-client, usually a web browser over the internet. – Wikipedia • Simply put, SaaS is a method for delivering software that provides remote access to software as a web- based service. The software service can be purchased with a monthly fee and pay as you go. What is SaaS? • Where does the term SaaS come from? o The SAAS acronym allegedly first appeared -
Openstack: the Path to Cloud
OpenStack: The Path to Cloud Considerations and recommendations for businesses adopting cloud technology openstack.org Table of Contents Executive Overview 1 Enterprise Cloud Strategy 2 Approaches to an OpenStack Private Cloud 5 Forming the OpenStack Team 9 Organization and Process Considerations 13 Choosing Workloads for Your Cloud 16 Implementation Phases 22 Post-deployment 30 Summary 32 References 33 Glossary 34 *Underlined gray bold words and concepts are defined in the Glossary at the end. CONTRIBUTORS Carol Barrett, Cloud Software Planner, Intel Corporation Tyler Britten, Technical Advocate, Blue Box, an IBM company Kathy Cacciatore, Consulting Marketing Manager, OpenStack Foundation Pete Chadwick, Senior Product Manager, SUSE Paula Phipps, Senior Manager, Infrastructure Software Marketing, Hitachi Data Systems Gerd Prüßmann, Director Cloud Solutions, Mirantis Megan Rossetti, Cloud Infrastructure Operations, Walmart Yih Leong Sun, PhD, Senior Software Cloud Architect, Intel Corporation Shamail Tahir, Offering Manager, IBM Heidi Joy Tretheway, Senior Marketing Manager, OpenStack Foundation Susan Wu, Director of Technical Marketing, Midokura Executive Overview This book is written to help enterprise architects implement an OpenStack® cloud. With architects with one foot in information technology and the other in business operations in mind, we want to offer insights and best practices to help you achieve multiple (and sometimes competing) goals. If you’re looking for vendor-neutral answers about planning your path to an OpenStack cloud, you’re in the right place. Members of the OpenStack community—technologists, business leaders and product managers—collaborated on this book to explain how to get started with an OpenStack cloud. We’ve included pros and cons to help you make better choices when setting up your cloud, along with anticipated investments of both time and money. -
Data Warehouse Offload to Google Bigquery
DATA WAREHOUSE OFFLOAD TO GOOGLE BIGQUERY In a world where big data presents both a major opportunity and a considerable challenge, a rigid, highly governed traditional enterprise data warehouse isn’t KEY BENEFITS OF MOVING always the best choice for processing large workloads, or for applications like TO GOOGLE BIGQUERY analytics. Google BigQuery is a lightning-fast cloud-based analytics database that lets you keep up with the growing data volumes you need to derive meaningful • Reduces costs and business value, while controlling costs and optimizing performance. shifts your investment from CAPEX to OPEX Pythian’s Data Warehouse Offload to Google BigQuery service moves your workload from an existing legacy data warehouse to a Google BigQuery data • Scales easily and on demand warehouse using our proven methodology and Google experts–starting with a fixed-cost Proof of Concept stage that will quickly demonstrate success. • Enables self-service analytics and advanced analytics GETTING STARTED The Pythian Data Warehouse Offload to Google BigQuery service follows a proven methodology and delivers a Proof of Concept (POC) that demonstrates viability and value within three to four weeks. The POC phase will follow this workflow: 1. Assess existing data warehouse environment to identify tables and up to two reports that will be offloaded in this phase 2. Provision GCP infrastructure including Cloud storage, Bastion hosts, BigQuery, and Networking 3. Implement full repeatable extract/load process for selected tables 4. Implement selected reports on BigQuery 5. Produce report PYTHIAN DELIVERS By the end of the first stage of our engagement, you can expect to have: • Working prototype on BigQuery • Up to two reports • Demonstrated analysis capabilities using one fact with five associated dimensions www.pythian.com • Report that includes: an assessment of your current setup and support you need to plan and maintain your full (including a cost analysis for BigQuery), performance/ Google BigQuery data warehouse and enterprise analytics usability analysis of POC vs. -
Enhancing Bittorrent-Like Peer-To-Peer Content Distribution with Cloud Computing
ENHANCING BITTORRENT-LIKE PEER-TO-PEER CONTENT DISTRIBUTION WITH CLOUD COMPUTING A THESIS SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNESOTA BY Zhiyuan Peng IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE Haiyang Wang November 2018 © Zhiyuan Peng 2018 Abstract BitTorrent is the most popular P2P file sharing and distribution application. However, the classic BitTorrent protocol favors peers with large upload bandwidth. Certain peers may experience poor download performance due to the disparity between users’ upload/download bandwidth. The major objective of this study is to improve the download performance of BitTorrent users who have limited upload bandwidth. To achieve this goal, a modified peer selection algorithm and a cloud assisted P2P network system is proposed in this study. In this system, we dynamically create additional peers on cloud that are dedicated to boost the download speed of the requested user. i Contents Abstract ............................................................................................................................................. i List of Figures ................................................................................................................................ iv 1 Introduction .............................................................................................................................. 1 2 Background ............................................................................................................................. -
Performance Efficiency Pillar
Performance Efficiency Pillar AWS Well-Architected Framework Performance Efficiency Pillar AWS Well-Architected Framework Performance Efficiency Pillar: AWS Well-Architected Framework Copyright © Amazon Web Services, Inc. and/or its affiliates. All rights reserved. Amazon's trademarks and trade dress may not be used in connection with any product or service that is not Amazon's, in any manner that is likely to cause confusion among customers, or in any manner that disparages or discredits Amazon. All other trademarks not owned by Amazon are the property of their respective owners, who may or may not be affiliated with, connected to, or sponsored by Amazon. Performance Efficiency Pillar AWS Well-Architected Framework Table of Contents Abstract and Introduction ................................................................................................................... 1 Abstract .................................................................................................................................... 1 Introduction .............................................................................................................................. 1 Performance Efficiency ....................................................................................................................... 2 Design Principles ........................................................................................................................ 2 Definition ................................................................................................................................. -
Paas Solutions Evaluation
PaaS solutions evaluation August 2014 Author: Sofia Danko Supervisors: Giacomo Tenaglia Artur Wiecek CERN openlab Summer Student Report 2014 CERN openlab Summer Student Report 2014 Project Specification OpenShift Origin is an open source software developed mainly by Red Hat to provide a multi- language PaaS. It is meant to allow developers to build and deploy their applications in a uniform way, reducing the configuration and management effort required on the administration side. The aim of the project is to investigate how to deploy OpenShift Origin at CERN, and to which extent it could be integrated with CERN "Middleware on Demand" service. The student will be exposed to modern cloud computing concepts such as PaaS, and will work closely with the IT middleware experts in order to evaluate how to address service needs with a focus on deployment in production. Some of the tools that are going to be heavily used are Puppet and Openstack to integrate with the IT infrastructure. CERN openlab Summer Student Report 2014 Abstract The report is a brief summary of Platform as a Service (PaaS) solutions evaluation including investigation the current situation at CERN and Services on Demand provision, homemade solutions, external market analysis and some information about PaaS deployment process. This first part of the report is devoted to the current status of the process of deployment OpenShift Origin at existing infrastructure at CERN, as well as specification of the common issues and restrictions that were found during this process using different machines for test. Furthermore, the following open source software solutions have been proposed for the investigation of possible PaaS provision at CERN: OpenShift Online; Cloud Foundry; Deis; Paasmaster; Cloudify; Stackato; WSO2 Stratos. -
Software As a Service for Data Scientists
Doi:10.1145/2076450.2076468 Globus Online manages fire-and-forget file transfers for big-data, high-performance scientific collaborations. By BRyce Allen, John BResnahan, Lisa childeRs, ian fosTeR, GoPi KanDasWaMy, RaJ KettiMuThu, JacK Kordas, MiKe LinK, Stuart Martin, Karl PicKett, anD SteVen TuecKe software as a service for Data scientists As Big Data emerges as a force in science,2,3 so, too, do new, onerous tasks for researchers. Data from specialized instrumentation, numerical simulations, and downstream manipulations must be collected, indexed, archived, shared, replicated, and analyzed. These tasks are not new, but the complexities involved in performing them for terabyte or when data volumes were measured larger datasets (increasingly common in kilobytes. The result is a computa- across scientific disciplines) are quite tional crisis in many laboratories and different from those that applied a growing need for far more powerful data-management tools, yet the typi- key insights cal researcher lacks the resources and expertise to operate these tools. The costs of research data life-cycle The answer may be to deliver re- management are growing dramatically as search data-management capabili- data becomes larger and more complex. ties to users as hosted “software as a saas approaches are a promising service,” or SaaS,18 a software-delivery solution, outsourcing time-consuming model in which software is hosted research data management tasks to third-party services. centrally and accessed by users using a thin client (such as a Web browser) Globus online demonstrates the potential over the Internet. As demonstrated in of saas for research data management, simplifying data movement for research- many business and consumer tools, ers and research facilities alike. -
Cloud Solutions – Infrastructure, Platform Or Software: Where Should You Go? Arlene F Minkiewicz PRICE Systems, LLC [email protected]
Cloud Solutions – Infrastructure, Platform or Software: Where should you go? Arlene F Minkiewicz PRICE Systems, LLC [email protected] © 2016 PRICE Systems, LLC All Rights RReeserrvveedd | DecaDecaddeess ooff CoCostst MMaannaaggemeemenntt ExcellExcellenencece Agenda . Introduction . Cloud Computing . Picking the right ‘as a Service’ . Case Study . Discussion and Final Thoughts © 2016 PRICE Systems, LLC All Rights Reserved | Decades of Cost Management Excellence 2 Introduction . Cloud Computing as defined by National Institute of Standards and Technology (NIST “Cloud computing is a model for enabling ubiquitous, convenient, on- demand network access to a shared pool of configurable computing resources (e.g. networks, servers, storage, applications and services) that can be rapidly provisioned and release with minimal management effort or service provider interaction” . PRNewswire reports that 90% of medium to large enterprises plan to increase or maintain annual spend on cloud for 2016 . According to CIO Magazine, the battle of the infrastructure is over – organizations have embrace outsourcing their hardware . The new battle will be in the application space © 2016 PRICE Systems, LLC All Rights Reserved | Decades of Cost Management Excellence 3 Application Migration comes with Management and Planning Challenges . How does an organization determine the right solutions to migrate to (or host in) the cloud? . How do they identify the right platform for migration? . What challenges do the various cloud solutions present? – -
Economic and Social Impacts of Google Cloud September 2018 Economic and Social Impacts of Google Cloud |
Economic and social impacts of Google Cloud September 2018 Economic and social impacts of Google Cloud | Contents Executive Summary 03 Introduction 10 Productivity impacts 15 Social and other impacts 29 Barriers to Cloud adoption and use 38 Policy actions to support Cloud adoption 42 Appendix 1. Country Sections 48 Appendix 2. Methodology 105 This final report (the “Final Report”) has been prepared by Deloitte Financial Advisory, S.L.U. (“Deloitte”) for Google in accordance with the contract with them dated 23rd February 2018 (“the Contract”) and on the basis of the scope and limitations set out below. The Final Report has been prepared solely for the purposes of assessment of the economic and social impacts of Google Cloud as set out in the Contract. It should not be used for any other purposes or in any other context, and Deloitte accepts no responsibility for its use in either regard. The Final Report is provided exclusively for Google’s use under the terms of the Contract. No party other than Google is entitled to rely on the Final Report for any purpose whatsoever and Deloitte accepts no responsibility or liability or duty of care to any party other than Google in respect of the Final Report and any of its contents. As set out in the Contract, the scope of our work has been limited by the time, information and explanations made available to us. The information contained in the Final Report has been obtained from Google and third party sources that are clearly referenced in the appropriate sections of the Final Report. -
Understanding the Cloud Computing Landscape
Chapter 1 Understanding the Cloud Computing Landscape Lamia Youseff, Dilma M. Da Silva, Maria Butrico, and Jonathan Appavoo Contents 1.1 Introduction .................................................................................................2 1.2 Cloud Systems Classifications ......................................................................2 1.3 SPI Cloud Classification ...............................................................................2 1.3.1 Cloud Software Systems ...................................................................3 1.3.2 Cloud Platform Systems ....................................................................3 1.3.3 Cloud Infrastructure Systems ...........................................................4 1.4 UCSB-IBM Cloud Ontology .......................................................................4 1.4.1 Applications (SaaS) ...........................................................................5 1.4.2 Cloud Software Environment (PaaS) ................................................7 1.4.3 Cloud Software Infrastructure ..........................................................8 1.4.4 Software Kernel Layer .......................................................................9 1.4.5 Cloud Hardware/Firmware ...............................................................9 1.5 Jackson’s Expansion on the UCSB-IBM Ontology .....................................10 1.6 Hoff’s Cloud Model ...................................................................................11 1.7 Discussion ..................................................................................................13 -
The Reality of Cloud Computing Chris Rose, Walden University, USA
International Journal of Management & Information Systems – Fourth Quarter 2011 Volume 15, Number 4 A Break In The Cloud? The Reality Of Cloud Computing Chris Rose, Walden University, USA ABSTRACT Cloud computing is on the forefront of the technological landscape with Google, Microsoft and Amazon, among others, building up their server capacity to handle the next perceived leap in technological innovation. However, not only does the security of cloud computing have to be seriously addressed, but SOA governance and the capacity in the core, connectivity and fiber layers of the Internet to absorb the increased bandwidth will also have to be considered. INTRODUCTION he term ―cloud computing‖ has many different meanings. A discussion at the 2008 IEEE International Conference on Web Services (ICWS), in Beijing, concluded that the definition depends T on whom you ask. For application and IT users, it’s IT as a service (ITaaS)—that is, delivery of computing, storage, and applications over the Internet from centralized data centers. For Internet application developers, it’s an Internet-scale software development platform and runtime environment. For infrastructure providers and administrators, it’s the massive, distributed data center infrastructure connected by IP networks (Lin et al, 2009). Everyone sees the cloud and uses the cloud differently. Some people offload ordinary desktop software and instead use web-based applications, others want on-demand computing with instant availability of extra processing power and extra storage. Nevertheless, the inescapable fact is that companies of all sizes are increasingly using the cloud to increase their businesses, perhaps by enabling remote working or simply to cut costs or even to create entirely new business models (Marshall, 2009).