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 Introduction
 The Cloud Ecosystem
 Virtualization
 Virtual Infrastructure Management
 Virtual Infrastructure Manager
  (OpenNebula)
 Conclusion
 Question/Answer Session
 References
   What is cloud computing?
    In General,
    › A simple metaphor for the internet, based on the
       symbol used to represent the worlwide network in
       computer network diagrams

    In technical terms
    › 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 released with
       minimal management effort or service provider
       interaction.[*]


    * The NIST Definition of Cloud Computing by Peter Mell, Timothy
      Grance, Sep 2011
   Characteristics of Cloud model
    › On-demand self-service
    › Broad Network Access
    › Resource pooling
    › Rapid elasticity
    › Measured services
   Architectural Layers of Cloud Computing
    › Software as a service (SaaS)
       Offers a complete application as a service on demand
       A single instance of software runs on cloud and provides
        service to multiple end users or organizations
       Examples are Google apps, salesforce.com etc.
    › Platform as a service (PaaS)
       Encapsulates a layer of software and provides it as
        service which is used to build higher-level services
       Consumers creates the software using tools and libraries
        from the provider
       Consumer controls deployment and configuration
        settings
       Provider provides networks, servers and storage
       Example, Google Apps Engine
   Architectural Layers of Cloud Computing
    (cont)

    › Infrastructure as a service (IaaS)
        Most basic cloud service model
        Provider provides computers (physical or a virtual
         machine), storage, firewalls, and networks
        Provider provides these facilities on demand
        Consumer is responsible for maintaining
         application software and operating system
        Cloud provider bill the consumer on the basis of
         amount of resources allocated and consumed
   Cloud Computing Infrastructure Model
    › Public Clouds
       Run by third parties
       Resources like applications and storage is available to
         general public over internet for free or on a pay-per-
         usage model
    › Private Clouds
       Build for exclusive use of one client
       Provides utmost control over data, security and QoS
       Provides access to external resources through web
         services
    › Hybrid Clouds
       Hybrid cloud uses local infrastructure with cloud
         computing capacity from public cloud
   Cloud ecosystem consists of :
    1.       Cloud Consumers
    2.       Cloud Management
              Used for controlling and monitoring of virtualized
               resources
              Contains cloud toolkits like, Amazon EC2, Globus
               Nimbus and Eucalyptus
    3.       Virtual Infrastructure Management
              Used for schedule and manage virtual machines
               across multiple hosts
              It contains tools like OpenNebula, Vmware vSphere
               for infrastructure management
    4.       Virtual Machine Manager
              Xen, KVM, Vmware etc
   What is virtualization?
    › Virtualization is the creation of virtual (instead
      of actual ) version of something, such as an
      operating system, a server, a storage device
      or network resources.[*]




    * Definition from whatis.com
   Types of Virtualization
    1. Server Virtualization
    2. Storage Virtualization
    3. Network I/O virtualization
   Server Virtualization
    › There are three popular approaches to
      server virtualization
      1. Virtual Machine Model
            Based on host/guest pradigm
            Each guest runs on a virtual imitation of hardware
             layer
            Guest operating systems runs without modification
            Guest requires real computing resources therefore
             it uses a virtual machine monitor (VMM) to
             coordinate instructions to cpu
            Examples are VMware and Microsoft Virtual server
   Server Virtualization (cont)
      2. Paravirtual machine Model
            Based on host/guest model
            Uses VMM
            VMM can access and modify the guest operating
             system code. This modification is called Porting
            Paravirtual machines are capable of running
             multiple operating systems
            Examples are, Xen and UML
   Server Virtualization (cont)
    3. Virtualization at operating system layer
            Host runs a single OS kernel as its core and exports
             operating system functionality to each of the
             guest
            Guest must use the same operating system as the
             host
            Different distributions of same system are allowed
            Common binaries and libraries of host are shared
             in this model, allowing thousands of guest to host
             at the same time
            Examples are, OpenVZ and Linux-Vserver
   Storage Virtualization
    › Pooling of physical storage from multiple
      network storage devices into single storage
      device
    › Storage pool is managed from a central
      console
    › Used in Storage Area Network (SAN)
    › Storage virtualization helps in
      backup, archiving and recovery more easily
      and in less time
   Network I/O Virtualization
    › Virtual machines are logical computing
      entities on a physical computers
    › VMs are realized on top of virtualization
      software layer that presents abstraction of
      the underlying physical resources
    › Network I/O virtualization provides multiple
      VMs to share common bandwidth and
      network links
   Network I/O virtualization (cont)
    › Network bridging
       Network bridging is the first step in network
        virtualization
   Network I/O virtualization (cont)
    › To address the complexity and performance
      issues following hardware and software
      oriented approaches are used
      1. NIC Bonding
                        Software oriented


                                                   Hardware
      1. Virtual Machine Device Queues (VMDq)      oriented
      2. Single Root I/O Virtualization (SR-IOV)
   Network I/O virtualization (cont)
    › Nic Bonding
       Software oriented approach
       It groups multiple physical
      network links and provide the
      Network bandwidth as an
      aggregate logic to the VMs
   Network I/O virtualization (cont)
    › Virtual Machine Device Queues (VMDq)
       Hardware oriented approach
       It is implemented at chipset level
       VMDq handles parallel queues of packets and
        routes them to appropriate VM
       Network throughput can reach up to 9.5Gbps
        compared to 4Gbps without VMDq
   Network I/O Virtualization (cont)
    › Single Root I/O Virtualization (SR-IOV)
       It is a feature of Peripheral component
        Interconnect (PCI)
       Multiple VMs running on a single computer
        can share natively a single PCI device
       This feature helps reducing overheads in
        resource sharing and overheads in controlling
        network I/O virtualization
   Network I/O Virtualization
    › Challenges
      1. Each host has hundreds of VMs and VNICs
         which increases complexity and
         management of each host
      2. Complexity of packet multiplexing.
      3. The ever increasing line rate. A line rate of
         10Gbps or more at host is expected which
         can add workload at the host cpu
   Network I/O virtualization (cont)
    › Virtual Switching with Intelligent NICs
       Each NIC has its own packet processor
       Offloads the processing work from CPU
   Provide a uniform and homogenous view of
    virtualized resources, regardless of
    virtualization platform
   Manage VMs lifecycle
   Setting up networks dynamically for group
    of VMs
   Managing storage requirements
   Support resource allocation to meet
    organization’s specific goals
   Adapt to organization’s changing resource
    needs
   OpenNebula
    › To control VM’s life cycle, the OpenNebula
     core orchestrates three different
     management areas:
      1. Image and storage technologies
            Virtual tools for preparing disk images for VMs
      2. The network fabric
            DHCP servers, firewalls and switches
      3. Underlying hypervisors
            For creating and controlling VMs
   OpenNebula (cont)
    › The OpenNebula core also supports service
     deployment
       Services typically include set of interrelated
        components requiring several VMs

    › The core handles the delivery of context
     information
       Web server’s IP address, digital certificates and
        software licenses
   OpenNebula (cont)
    › A separate scheduler component makes VM
     placement decisions
      Creating and updating resource schedule and
       sending appropriate deployment command
       to OpenNebula core
      The default scheduler provides a rank
       scheduling policy that places VMs on physical
       resources according to ranking algorithm that
       the administrator can configure
      It relies on real time data from both the running
       VMs and available physical resources
   OpenNebula (cont)
    › OpenNebula can support a hybrid cloud
     model
      Uses cloud drivers to interface with external
       clouds
      It helps organizations supplement the local
       infrastructure with computing capacity from
       public cloud to meet peak demands
      Includes EC2 driver which can submit requests
       to Amazon EC2 and Eucalyptus and also
       includes ElasticHosts driver
OpenNebula VI Engine Components
   The Haizea lease Manager
    › Open source resource lease manager
    › Can act as a VM scheduler for OpenNebula
    › Simulator to evaluate different scheduling strategies
        performance over time
    ›   Haizea provides resources to users on lease terms
    ›   Haizea supports advance reservation lease in which
        resources must be available at a specific time
    ›   Best effort lease in which resources are allocated as
        soon as possible
    ›   Immediate lease in which resources are provisioned
        when requested.
Comparison of tools providing VIM capabilities


Tool        Provisioning   Default Placement Policies      Configurable      Support For hybrid Cloud    Remote
            Model                                          Placement                                     Interface
                                                           Policies                                      s

Amazon      Best Effort    Proprietary                     Proprietary       No                          EC2 Web
EC2                                                                                                      services
                                                                                                         API


VMware      Immediate      Initial placement on CPU        No                Only when both the local    vCloud
vSphere                    load and dynamic                                  and external cloud use      API
                           placement to balance                              vSphere
                           average CPU or memory
                           load and consolidate servers



OpenNebul   Best-effort    Initial placement based on      Support for any   Driver-based architecture   No
a 1.2                      requirement/rank policies to    static/dynamic    allows interfacing with
                           prioritize those resources      placement         multiple external clouds;
                           more suitable for the virtual   policy            supports EC2-compatible
                           machine (VM) using dynamic                        clouds and ElasticHosts
                           information and dynamic
                           placement to consolidate
                           servers


OpenNebul   Immediate,     Dynamic placement to            VM placement      Driver-based architecture   No
a 1.2/      best-effort,   implement AR leases             strategies        allows interfacing with
Haizea      and                                            supporting        multiple external clouds;
            advance                                        queues and        supports EC2-compatible
            reservation                                    priorities        clouds and ElasticHosts
            (AR)
 As private and hybrid IaaS clouds
  grows, the need for a diverse ecosystem of
  tools and technologies to create and
  manage clouds also grows
 Private and hybrid clouds will also face the
  challenge of efficiently managing finite
  resources
 Virtualization leads to better resource
  utilization
 Increase performance
   Network I/O virtualization for cloud computing, by Yan
    Lou, University of Massachusetts Lowell

   Virtual Infrastructure Management in Private and Hybrid
    Clouds, by Borja Sotomayor, Unv. Of Chicago, Ruben S.
    Montero and Ignacio M.Liorente, Universidad
    Complutense de Madrid and Ian Foster, Argonne
    National laboratory, Unv. Of Chicago

   Introduction to Cloud Computing Architecture, white
    paper, 1st Edition, June 2009, by Sun Microsystem

   NIST definition of Cloud Computing by Peter Mell and
    Timothy Grance, September 2011

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Virtual Infrastructure Management with OpenNebula

  • 1.
  • 2.  Introduction  The Cloud Ecosystem  Virtualization  Virtual Infrastructure Management  Virtual Infrastructure Manager (OpenNebula)  Conclusion  Question/Answer Session  References
  • 3. What is cloud computing? In General, › A simple metaphor for the internet, based on the symbol used to represent the worlwide network in computer network diagrams In technical terms › 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 released with minimal management effort or service provider interaction.[*] * The NIST Definition of Cloud Computing by Peter Mell, Timothy Grance, Sep 2011
  • 4. Characteristics of Cloud model › On-demand self-service › Broad Network Access › Resource pooling › Rapid elasticity › Measured services
  • 5. Architectural Layers of Cloud Computing › Software as a service (SaaS)  Offers a complete application as a service on demand  A single instance of software runs on cloud and provides service to multiple end users or organizations  Examples are Google apps, salesforce.com etc. › Platform as a service (PaaS)  Encapsulates a layer of software and provides it as service which is used to build higher-level services  Consumers creates the software using tools and libraries from the provider  Consumer controls deployment and configuration settings  Provider provides networks, servers and storage  Example, Google Apps Engine
  • 6. Architectural Layers of Cloud Computing (cont) › Infrastructure as a service (IaaS)  Most basic cloud service model  Provider provides computers (physical or a virtual machine), storage, firewalls, and networks  Provider provides these facilities on demand  Consumer is responsible for maintaining application software and operating system  Cloud provider bill the consumer on the basis of amount of resources allocated and consumed
  • 7. Cloud Computing Infrastructure Model › Public Clouds  Run by third parties  Resources like applications and storage is available to general public over internet for free or on a pay-per- usage model › Private Clouds  Build for exclusive use of one client  Provides utmost control over data, security and QoS  Provides access to external resources through web services › Hybrid Clouds  Hybrid cloud uses local infrastructure with cloud computing capacity from public cloud
  • 8. Cloud ecosystem consists of : 1. Cloud Consumers 2. Cloud Management  Used for controlling and monitoring of virtualized resources  Contains cloud toolkits like, Amazon EC2, Globus Nimbus and Eucalyptus 3. Virtual Infrastructure Management  Used for schedule and manage virtual machines across multiple hosts  It contains tools like OpenNebula, Vmware vSphere for infrastructure management 4. Virtual Machine Manager  Xen, KVM, Vmware etc
  • 9.
  • 10. What is virtualization? › Virtualization is the creation of virtual (instead of actual ) version of something, such as an operating system, a server, a storage device or network resources.[*] * Definition from whatis.com
  • 11. Types of Virtualization 1. Server Virtualization 2. Storage Virtualization 3. Network I/O virtualization
  • 12. Server Virtualization › There are three popular approaches to server virtualization 1. Virtual Machine Model  Based on host/guest pradigm  Each guest runs on a virtual imitation of hardware layer  Guest operating systems runs without modification  Guest requires real computing resources therefore it uses a virtual machine monitor (VMM) to coordinate instructions to cpu  Examples are VMware and Microsoft Virtual server
  • 13. Server Virtualization (cont) 2. Paravirtual machine Model  Based on host/guest model  Uses VMM  VMM can access and modify the guest operating system code. This modification is called Porting  Paravirtual machines are capable of running multiple operating systems  Examples are, Xen and UML
  • 14. Server Virtualization (cont) 3. Virtualization at operating system layer  Host runs a single OS kernel as its core and exports operating system functionality to each of the guest  Guest must use the same operating system as the host  Different distributions of same system are allowed  Common binaries and libraries of host are shared in this model, allowing thousands of guest to host at the same time  Examples are, OpenVZ and Linux-Vserver
  • 15. Storage Virtualization › Pooling of physical storage from multiple network storage devices into single storage device › Storage pool is managed from a central console › Used in Storage Area Network (SAN) › Storage virtualization helps in backup, archiving and recovery more easily and in less time
  • 16. Network I/O Virtualization › Virtual machines are logical computing entities on a physical computers › VMs are realized on top of virtualization software layer that presents abstraction of the underlying physical resources › Network I/O virtualization provides multiple VMs to share common bandwidth and network links
  • 17. Network I/O virtualization (cont) › Network bridging  Network bridging is the first step in network virtualization
  • 18. Network I/O virtualization (cont) › To address the complexity and performance issues following hardware and software oriented approaches are used 1. NIC Bonding Software oriented Hardware 1. Virtual Machine Device Queues (VMDq) oriented 2. Single Root I/O Virtualization (SR-IOV)
  • 19. Network I/O virtualization (cont) › Nic Bonding  Software oriented approach  It groups multiple physical network links and provide the Network bandwidth as an aggregate logic to the VMs
  • 20. Network I/O virtualization (cont) › Virtual Machine Device Queues (VMDq)  Hardware oriented approach  It is implemented at chipset level  VMDq handles parallel queues of packets and routes them to appropriate VM  Network throughput can reach up to 9.5Gbps compared to 4Gbps without VMDq
  • 21. Network I/O Virtualization (cont) › Single Root I/O Virtualization (SR-IOV)  It is a feature of Peripheral component Interconnect (PCI)  Multiple VMs running on a single computer can share natively a single PCI device  This feature helps reducing overheads in resource sharing and overheads in controlling network I/O virtualization
  • 22. Network I/O Virtualization › Challenges 1. Each host has hundreds of VMs and VNICs which increases complexity and management of each host 2. Complexity of packet multiplexing. 3. The ever increasing line rate. A line rate of 10Gbps or more at host is expected which can add workload at the host cpu
  • 23. Network I/O virtualization (cont) › Virtual Switching with Intelligent NICs  Each NIC has its own packet processor  Offloads the processing work from CPU
  • 24. Provide a uniform and homogenous view of virtualized resources, regardless of virtualization platform  Manage VMs lifecycle  Setting up networks dynamically for group of VMs  Managing storage requirements  Support resource allocation to meet organization’s specific goals  Adapt to organization’s changing resource needs
  • 25. OpenNebula › To control VM’s life cycle, the OpenNebula core orchestrates three different management areas: 1. Image and storage technologies  Virtual tools for preparing disk images for VMs 2. The network fabric  DHCP servers, firewalls and switches 3. Underlying hypervisors  For creating and controlling VMs
  • 26. OpenNebula (cont) › The OpenNebula core also supports service deployment  Services typically include set of interrelated components requiring several VMs › The core handles the delivery of context information  Web server’s IP address, digital certificates and software licenses
  • 27. OpenNebula (cont) › A separate scheduler component makes VM placement decisions  Creating and updating resource schedule and sending appropriate deployment command to OpenNebula core  The default scheduler provides a rank scheduling policy that places VMs on physical resources according to ranking algorithm that the administrator can configure  It relies on real time data from both the running VMs and available physical resources
  • 28. OpenNebula (cont) › OpenNebula can support a hybrid cloud model  Uses cloud drivers to interface with external clouds  It helps organizations supplement the local infrastructure with computing capacity from public cloud to meet peak demands  Includes EC2 driver which can submit requests to Amazon EC2 and Eucalyptus and also includes ElasticHosts driver
  • 29. OpenNebula VI Engine Components
  • 30. The Haizea lease Manager › Open source resource lease manager › Can act as a VM scheduler for OpenNebula › Simulator to evaluate different scheduling strategies performance over time › Haizea provides resources to users on lease terms › Haizea supports advance reservation lease in which resources must be available at a specific time › Best effort lease in which resources are allocated as soon as possible › Immediate lease in which resources are provisioned when requested.
  • 31. Comparison of tools providing VIM capabilities Tool Provisioning Default Placement Policies Configurable Support For hybrid Cloud Remote Model Placement Interface Policies s Amazon Best Effort Proprietary Proprietary No EC2 Web EC2 services API VMware Immediate Initial placement on CPU No Only when both the local vCloud vSphere load and dynamic and external cloud use API placement to balance vSphere average CPU or memory load and consolidate servers OpenNebul Best-effort Initial placement based on Support for any Driver-based architecture No a 1.2 requirement/rank policies to static/dynamic allows interfacing with prioritize those resources placement multiple external clouds; more suitable for the virtual policy supports EC2-compatible machine (VM) using dynamic clouds and ElasticHosts information and dynamic placement to consolidate servers OpenNebul Immediate, Dynamic placement to VM placement Driver-based architecture No a 1.2/ best-effort, implement AR leases strategies allows interfacing with Haizea and supporting multiple external clouds; advance queues and supports EC2-compatible reservation priorities clouds and ElasticHosts (AR)
  • 32.  As private and hybrid IaaS clouds grows, the need for a diverse ecosystem of tools and technologies to create and manage clouds also grows  Private and hybrid clouds will also face the challenge of efficiently managing finite resources  Virtualization leads to better resource utilization  Increase performance
  • 33. Network I/O virtualization for cloud computing, by Yan Lou, University of Massachusetts Lowell  Virtual Infrastructure Management in Private and Hybrid Clouds, by Borja Sotomayor, Unv. Of Chicago, Ruben S. Montero and Ignacio M.Liorente, Universidad Complutense de Madrid and Ian Foster, Argonne National laboratory, Unv. Of Chicago  Introduction to Cloud Computing Architecture, white paper, 1st Edition, June 2009, by Sun Microsystem  NIST definition of Cloud Computing by Peter Mell and Timothy Grance, September 2011