Comparative Study for Selection of Open Source Hypervisors and Cloud Architectures Under Variant Requirements
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Homework #5 Answer Key
CS312 Homework #5 Answer Key March 9, 2016 Questions 1. Load balancers are designed to help with vertical scaling. (a) True (b) False 2. Layer 7 load balancers allow you to use both connection tracking and inspection of packets including modification of packets. (a) True (b) False 3. Linux containers do not require hypervisors (a) True (b) False 1 4. The RUN command can be used more than once in a Dockerfile. (a) True (b) False 5. The PID Namespace allows users to see processes from other containers (a) True (b) False 6. Paravirtualization uses cpu supported virtualization. (a) True (b) False 7. Which software load balancer primarily acts as an HTTP accelerator and a static cache server? (a) HAProxy (b) Apache (c) nginx (d) Varnish 8. Which of the following is not true about Linux Containers? (a) Operating system level virtualization (b) Provides little overhead (c) Fully emulates an operating system (d) Allows limits to resources with cgroups 9. Which service describes a virtual computing platform? (a) IaaS (b) PaaS (c) SaaS (d) VaaS 2 10. Describe the potential problems of using Round Robin DNS. • Depending on the implementation of the client resolver, this can be somewhat random or not. • Some resolvers always use alphabetical ordering. • DNS Caching and Time-To-Live (TTL) issues. • If the site goes down, you have to update DNS to reroute traffic which can cause problems. 11. Which scheduling algorithm is generally preferred if the web application uses sessions? Source Connection 12. Which HAProxy configuration section allows you to define a complete proxy? listen 13. -
Lguest a Journey of Learning the Linux Kernel Internals
Lguest A journey of learning the Linux kernel internals Daniel Baluta <[email protected]> What is lguest? ● “Lguest is an adventure, with you, the reader, as a Hero” ● Minimal 32-bit x86 hypervisor ● Introduced in 2.6.23 (October, 2007) by Rusty Russel & co ● Around 6000 lines of code ● “Relatively” “easy” to understand and hack on ● Support to learn linux kernel internals ● Porting to other architectures is a challenging task Hypervisor types make Preparation ● Guest ○ Life of a guest ● Drivers ○ virtio devices: console, block, net ● Launcher ○ User space program that sets up and configures Guests ● Host ○ Normal linux kernel + lg.ko kernel module ● Switcher ○ Low level Host <-> Guest switch ● Mastery ○ What’s next? Lguest overview make Guest ● “Simple creature, identical to the Host [..] behaving in simplified ways” ○ Same kernel as Host (or at least, built from the same source) ● booting trace (when using bzImage) ○ arch/x86/boot/compressed/head_32.S: startup_32 ■ uncompresses the kernel ○ arch/x86/kernel/head_32.S : startup_32 ■ initialization , checks hardware_subarch field ○ arch/x86/lguest/head_32.S ■ LGUEST_INIT hypercall, jumps to lguest_init ○ arch/x86/lguest/boot.c ■ once we are here we know we are a guest ■ override privileged instructions ■ boot as normal kernel, calling i386_start_kernel Hypercalls struct lguest_data ● second communication method between Host and Guest ● LHCALL_GUEST_INIT ○ hypercall to tell the Host where lguest_data struct is ● both Guest and Host publish information here ● optimize hypercalls ○ irq_enabled -
Lguest the Little Hypervisor
Lguest the little hypervisor Matías Zabaljáuregui [email protected] based on lguest documentation written by Rusty Russell note: this is a draft and incomplete version lguest introduction launcher guest kernel host kernel switcher don't have time for: virtio virtual devices patching technique async hypercalls rewriting technique guest virtual interrupt controller guest virtual clock hw assisted vs paravirtualization hybrid virtualization benchmarks introduction A hypervisor allows multiple Operating Systems to run on a single machine. lguest paravirtualization within linux kernel proof of concept (paravirt_ops, virtio...) teaching tool guests and hosts A module (lg.ko) allows us to run other Linux kernels the same way we'd run processes. We only run specially modified Guests. Setting CONFIG_LGUEST_GUEST, compiles [arch/x86/lguest/boot.c] into the kernel so it knows how to be a Guest at boot time. This means that you can use the same kernel you boot normally (ie. as a Host) as a Guest. These Guests know that they cannot do privileged operations, such as disable interrupts, and that they have to ask the Host to do such things explicitly. Some of the replacements for such low-level native hardware operations call the Host through a "hypercall". [ drivers/lguest/hypercalls.c ] high level overview launcher /dev/lguest guest kernel host kernel switcher Launcher main() some implementations /dev/lguest write → initialize read → run guest Launcher main [ Documentation/lguest/lguest.c ] The Launcher is the Host userspace program which sets up, runs and services the Guest. Just to confuse you: to the Host kernel, the Launcher *is* the Guest and we shall see more of that later. -
Cloud Interoperability with the Opennebula Toolkit
Cloud Computing: Interoperability and Data Portability Issues Microsoft, Brussels st 1 December 2009 Cloud Interoperability with the OpenNebula Toolkit Distributed Systems Architecture Research Group Universidad Complutense de Madrid 1/11 Cloud Computing in a Nutshell Cloud Interoperability with the OpenNebula Toolkit What Who Software as a Service On-demand End-user access to any (does not care about hw or sw) application Platform as a Service Platform for Developer building and (no managing of the delivering web underlying hw & swlayers) applications Infrastructure as a Raw computer System Administrator Serviceᄎ infrastructure (complete management of the computer infrastructure) Innovative open, flexible and scalable technology to build IaaS clouds Physical Infrastructure 2/11 What is OpenNebula? Cloud Interoperability with the OpenNebula Toolkit Innovations Designed to address the technology challenges in cloud computing management Open-source Toolkit OpenNebula v1.4 • Support to build new cloud interfaces • Open and flexible tool to fit into any datacenter and VM integrate with any ecosystem component VM • Private, public and hybrid clouds VM • Based on standards • Support federation of infrastructures • Efficient and scalable management of the cloud 3/11 A Toolkit for System Integrators Cloud Interoperability with the OpenNebula Toolkit One Size does not Fit All: Tailoring the Tool to Fit your Needs • Open, modular and extensible architecture • Easy to enhance and embed • Minimal installation requirements (distributed in Ubuntu) • Open Source – Apache 2 Virt. Virt. InterfacesVirt. SchedulersVirt. OpenNebula API Virtual and Physical Resource Management Driver API Virt. Virt. Virt. Virt. ComputeVirt. StorageVirt. NetworkVirt. CloudVirt. 4/11 Interoperability in the OpenNebula Toolkit Cloud Interoperability with the OpenNebula Toolkit Interoperation from Different Perspectives 1. -
Python for Bioinformatics, Second Edition
PYTHON FOR BIOINFORMATICS SECOND EDITION CHAPMAN & HALL/CRC Mathematical and Computational Biology Series Aims and scope: This series aims to capture new developments and summarize what is known over the entire spectrum of mathematical and computational biology and medicine. It seeks to encourage the integration of mathematical, statistical, and computational methods into biology by publishing a broad range of textbooks, reference works, and handbooks. The titles included in the series are meant to appeal to students, researchers, and professionals in the mathematical, statistical and computational sciences, fundamental biology and bioengineering, as well as interdisciplinary researchers involved in the field. The inclusion of concrete examples and applications, and programming techniques and examples, is highly encouraged. Series Editors N. F. Britton Department of Mathematical Sciences University of Bath Xihong Lin Department of Biostatistics Harvard University Nicola Mulder University of Cape Town South Africa Maria Victoria Schneider European Bioinformatics Institute Mona Singh Department of Computer Science Princeton University Anna Tramontano Department of Physics University of Rome La Sapienza Proposals for the series should be submitted to one of the series editors above or directly to: CRC Press, Taylor & Francis Group 3 Park Square, Milton Park Abingdon, Oxfordshire OX14 4RN UK Published Titles An Introduction to Systems Biology: Statistical Methods for QTL Mapping Design Principles of Biological Circuits Zehua Chen Uri Alon -
Proceedings of the Linux Symposium
Proceedings of the Linux Symposium Volume One June 27th–30th, 2007 Ottawa, Ontario Canada Contents The Price of Safety: Evaluating IOMMU Performance 9 Ben-Yehuda, Xenidis, Mostrows, Rister, Bruemmer, Van Doorn Linux on Cell Broadband Engine status update 21 Arnd Bergmann Linux Kernel Debugging on Google-sized clusters 29 M. Bligh, M. Desnoyers, & R. Schultz Ltrace Internals 41 Rodrigo Rubira Branco Evaluating effects of cache memory compression on embedded systems 53 Anderson Briglia, Allan Bezerra, Leonid Moiseichuk, & Nitin Gupta ACPI in Linux – Myths vs. Reality 65 Len Brown Cool Hand Linux – Handheld Thermal Extensions 75 Len Brown Asynchronous System Calls 81 Zach Brown Frysk 1, Kernel 0? 87 Andrew Cagney Keeping Kernel Performance from Regressions 93 T. Chen, L. Ananiev, and A. Tikhonov Breaking the Chains—Using LinuxBIOS to Liberate Embedded x86 Processors 103 J. Crouse, M. Jones, & R. Minnich GANESHA, a multi-usage with large cache NFSv4 server 113 P. Deniel, T. Leibovici, & J.-C. Lafoucrière Why Virtualization Fragmentation Sucks 125 Justin M. Forbes A New Network File System is Born: Comparison of SMB2, CIFS, and NFS 131 Steven French Supporting the Allocation of Large Contiguous Regions of Memory 141 Mel Gorman Kernel Scalability—Expanding the Horizon Beyond Fine Grain Locks 153 Corey Gough, Suresh Siddha, & Ken Chen Kdump: Smarter, Easier, Trustier 167 Vivek Goyal Using KVM to run Xen guests without Xen 179 R.A. Harper, A.N. Aliguori & M.D. Day Djprobe—Kernel probing with the smallest overhead 189 M. Hiramatsu and S. Oshima Desktop integration of Bluetooth 201 Marcel Holtmann How virtualization makes power management different 205 Yu Ke Ptrace, Utrace, Uprobes: Lightweight, Dynamic Tracing of User Apps 215 J. -
The Opennebula Standard-Based Open-Source Toolkit to Build Cloud Infrastructures
Jornadas Técnicas de RedIRIS 2009 Santiago de Compostela 27th November 2009 The OpenNebula Standard-based Open -source Toolkit to Build Cloud Infrastructures Distributed Systems Architecture Research Group Universidad Complutense de Madrid 1/20 Cloud Computing in a Nutshell The OpenNebula Standard-based Open-source Toolkit to Build Cloud Infrastructures What Who Software as a Service On-demand End-user access to any (does not care about hw or sw) application Platform as a Service Platform for Developer building and (no managing of the delivering web underlying hw & swlayers) applications Infrastructure as a Raw computer System Administrator Serviceᄎ infrastructure (complete management of the computer infrastructure) Innovative open, flexible and scalable technology to build IaaS clouds Physical Infrastructure 2/20 From Public to Private Cloud Computing The OpenNebula Standard-based Open-source Toolkit to Build Cloud Infrastructures Public Cloud • Flexible and elastic capacity • Ubiquitous network access • On-demand access • Pay per use Service Cloud User/Service Provider User (Cloud Interface) Private Cloud • Centralized management VM • VM placement optimization VM • Dynamic resizing and partitioning VM of the infrastructure • Support for heterogeneous workloads 3/20 Contents The OpenNebula Standard-based Open-source Toolkit to Build Cloud Infrastructures Innovations Designed to address the technology challenges in cloud computing management Toolkit OpenNebula v1.4 Community Users, projects and ecosystem Open-source and Standardization -
Using Ganeti for Running Highly Available Virtual Services
Using Ganeti for running highly available virtual services 2016-04-21, HEPiX Spring 2016, Zeuthen Overview ● What is Ganeti ● What is it good for ● How does it work ● NDGF usage 2 What is Ganeti ● A software stack for managing virtual machines – Like VMware or OpenStack or libvirt or ... – Supporting Xen or KVM hypervisors – Handles ● Storage: volume creation and assignment ● OS installation and customization ● Networking ● Startup, shutdown, live migration, failover of instances – Written in Python and Haskell – Aimed for ease of use and fast and simple error recovery after physical failures on commodity hardware 3 What is Ganeti ● Mainly developed by Google for their own use – Handles VMs for corporate network (office servers, remote desktops etc), not production services (what non-employees see) ● Outside Google – Debian – NDGF-T1 – Lufthansa – Etc ● Maintained by Google with significant external contributions 4 What is Ganeti good at ● Running highly available services on a small set of hardware – DRBD or external reliable block devices (CEPH, Enterprise storage) – Live migrations in case of impending hardware failure ● Or reboot into new kernel security upgrade on the hardnode – Failover handled automatically in case of sudden hardware failure – No external dependencies beyond networking ● Well, if you use external storage... ● But no extra servers or services needed – Typical reasonable cluster size, 3 – 50 hardnodes ● Multiple clusters integrate well though in admin tools 5 How does Ganeti work ● gnt-cluster init ... – Creates a cluster of ganeti nodes – We'll assume DRBD for storage, as at NDGF – One member is a master node ● Others can take over with master-failover if they can get quorum A B C D E 6 How does Ganeti work ● gnt-instance add – Creates VMs, with OS install scripts (image, debootstrap, pxe) – Each VM has a secondary location (DRBD mirror, sync) A B C D E 7 How does Ganeti work ● gnt-instance migrate – No noticable service impact from live migration, <1s network pause ● Unless something is broken.. -
Developing Cloud Computing Infrastructures in Developing Countries in Asia
Walden University ScholarWorks Walden Dissertations and Doctoral Studies Walden Dissertations and Doctoral Studies Collection 2020 Developing Cloud Computing Infrastructures in Developing Countries in Asia Daryoush Charmsaz Moghaddam Walden University Follow this and additional works at: https://scholarworks.waldenu.edu/dissertations Part of the Databases and Information Systems Commons This Dissertation is brought to you for free and open access by the Walden Dissertations and Doctoral Studies Collection at ScholarWorks. It has been accepted for inclusion in Walden Dissertations and Doctoral Studies by an authorized administrator of ScholarWorks. For more information, please contact [email protected]. Walden University College of Management and Technology This is to certify that the doctoral study by Daryoush Charmsaz Moghaddam has been found to be complete and satisfactory in all respects, and that any and all revisions required by the review committee have been made. Review Committee Dr. Steven Case, Committee Chairperson, Information Technology Faculty Dr. Gail Miles, Committee Member, Information Technology Faculty Dr. Bob Duhainy, University Reviewer, Information Technology Faculty Chief Academic Officer and Provost Sue Subocz, Ph.D. Walden University 2020 Abstract Developing Cloud Computing Infrastructures in Developing Countries in Asia by Daryoush Charmsaz Moghaddam MS, Sharif University, 2005 BS, Civil Aviation Higher Education Complex, 1985 Doctoral Study Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Information Technology Walden University March 2020 Abstract Adoption and development of cloud computing in developing countries can be different from other countries, but it can provide more benefits. The purpose of this multiple case study, guided by diffusion of innovations theory, was to explore strategies that IT directors use to develop cloud computing infrastructures in Iran. -
Bunker: a Privacy-Oriented Platform for Network Tracing Andrew G
Bunker: A Privacy-Oriented Platform for Network Tracing Andrew G. Miklas†, Stefan Saroiu‡, Alec Wolman‡, and Angela Demke Brown† †University of Toronto and ‡Microsoft Research Abstract: ISPs are increasingly reluctant to collect closing social security numbers, names, addresses, or and store raw network traces because they can be used telephone numbers [5, 54]. to compromise their customers’ privacy. Anonymization Trace anonymization is the most common technique techniques mitigate this concern by protecting sensitive information. Trace anonymization can be performed of- for addressing these privacy concerns. A typical imple- fline (at a later time) or online (at collection time). Of- mentation uses a keyed one-way secure hash function to fline anonymization suffers from privacy problems be- obfuscate sensitive information contained in the trace. cause raw traces must be stored on disk – until the traces This could be as simple as transforming a few fields in are deleted, there is the potential for accidental leaks or the IP headers, or as complex as performing TCP connec- exposure by subpoenas. Online anonymization drasti- tion reconstruction and then obfuscating data (e.g., email cally reduces privacy risks but complicates software en- addresses) deep within the payload. There are two cur- gineering efforts because trace processing and anony- mization must be performed at line speed. This paper rent approaches to anonymizing network traces: offline presents Bunker, a network tracing system that combines and online. Offline anonymization collects and stores the software development benefits of offline anonymiz- the entire raw trace and then performs anonymization ation with the privacy benefits of online anonymization. as a post-processing step. -
Cloud Computing and Mobile Application Development
Cloud Computing And Mobile Application Development Personal and hippopotamic Simone often derange some triploidy concertedly or empanels unceremoniously. By-past and waist-deep Georgy readjusts her neurectomy asperses individually or deactivated knee-deep, is Dennis shaping? Bacillary and undealt Pace cutinized her springtide confusing while Saw trammel some polemic insignificantly. What occurs automatically reduces additional challenges Also has the cost as much in mobile application, it means network connection to services depending on a golden software development lets you with mobile application. Advantages and Disadvantages of Cloud Computing. Blueberry considers response to cloud development environment with common, place on servers and collaboration, and get losses when you need to learn how could be. Build a Firebase Android Application by Coursera Project Network. Mobile computing uses the concept in cloud computing. Compatible available whether a music of mobile and standalone devices Changes in Approaching Cloud Software Development Cloud computing has shifted. What these Cloud-Native since It Hype or The Future these Software. We scope the sun cloud based application development company across USA India. Mobile cloud computing refers to execute same technology used to deploy. Mobile App Development merges the alternate-developing Cloud Computing Applications trends with the omnipresent smartphone One member the most. How mobile computing will continually evolving research issues and testing, in regards to the cloud application and cloud computing development is. Cloud Computing Services Cloud-Based Solutions for Future-Ready Businesses With cash-to-cash support from Rishabh Software inventory can realize flexible. That the application developer is programming such powerful device without. Learn Mobile Cloud Computing With Android online with courses like Build a Persistent Storage App in. -
Managed Conversion of Guests to Ovirt
Managed Conversion of Guests to oVirt Arik Hadas Senior Software Engineer Red Hat 21/8/15 KVM Forum, August 2015 Agenda ● Motivation ● Architecture ● Demonstration ● Implementation ● Future work KVM Forum, August 2015 Many ways to run Virtual Machines ● There are many virtualization tools ● Different hypervisors – KVM, E !"E Xi, Xen, VirtualBo$, .%% ● Different management systems – oVirt, virt'manager, v phere, Ganeti, .%% KVM Forum, August 2015 “I don't want to lose my VMs” ● Virtualization technologies are used for a long time ● +o standardization ● ,eople are tied up to the technologies they currently use ● Conversion tools are neede). KVM Forum, August 2015 virt-v2v ● ,art of virt tools – /pen source virtualization management tools ● Foreign hypervisor -0 KVM ● Standalone conversion tool KVM Forum, August 2015 Conversion to oVirt using virt-v2v ● Converts disk formats ● Enables VirtIO drivers (If needed) – Network, torage ● Fixes boot'loader ● ,roduces full oVirt-compatible OVF ● Outputs the VM in oVirt's export domain KVM Forum, August 2015 Drawbacks ● Slow ● Tedious ● Error-prone ● 5equires separate installation ● Do not support conversion of OVA 7les ● Error handlin& KVM Forum, August 2015 Our goal Improve the conversion process to oVirt – Faster – Tools are availa1le – Graphical user interface ● To con7&ure ● To monitor/cancel – Ro1ust – Support conversion of OVA files KVM Forum, August 2015 Design principles ● 8se virt-v9v capabilities – For &uest-level operations ● oVirt mana&es the conversion – -on7&ure conversion properties