188 lines
7.5 KiB
ReStructuredText
188 lines
7.5 KiB
ReStructuredText
=========
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Use Cases
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=========
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This appendix contains a small selection of use cases from the
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community, with more technical detail than usual. Further examples can
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be found on the `OpenStack website <https://www.openstack.org/user-stories/>`_.
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NeCTAR
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~~~~~~
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Who uses it: researchers from the Australian publicly funded research
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sector. Use is across a wide variety of disciplines, with the purpose of
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instances ranging from running simple web servers to using hundreds of
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cores for high-throughput computing.
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Deployment
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----------
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Using OpenStack Compute cells, the NeCTAR Research Cloud spans eight
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sites with approximately 4,000 cores per site.
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Each site runs a different configuration, as a resource cells in an
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OpenStack Compute cells setup. Some sites span multiple data centers,
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some use off compute node storage with a shared file system, and some
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use on compute node storage with a non-shared file system. Each site
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deploys the Image service with an Object Storage back end. A central
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Identity, dashboard, and Compute API service are used. A login to the
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dashboard triggers a SAML login with Shibboleth, which creates an
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account in the Identity service with an SQL back end. An Object Storage
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Global Cluster is used across several sites.
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Compute nodes have 24 to 48 cores, with at least 4 GB of RAM per core
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and approximately 40 GB of ephemeral storage per core.
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All sites are based on Ubuntu 14.04, with KVM as the hypervisor. The
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OpenStack version in use is typically the current stable version, with 5
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to 10 percent back-ported code from trunk and modifications.
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Resources
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---------
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- `NeCTAR-RC GitHub <https://github.com/NeCTAR-RC/>`_
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MIT CSAIL
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~~~~~~~~~
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Who uses it: researchers from the MIT Computer Science and Artificial
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Intelligence Lab.
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Deployment
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----------
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The CSAIL cloud is currently 64 physical nodes with a total of 768
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physical cores and 3,456 GB of RAM. Persistent data storage is largely
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outside the cloud on NFS, with cloud resources focused on compute
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resources. There are more than 130 users in more than 40 projects,
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typically running 2,000–2,500 vCPUs in 300 to 400 instances.
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We initially deployed on Ubuntu 12.04 with the Essex release of
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OpenStack using FlatDHCP multi-host networking.
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The software stack is still Ubuntu 12.04 LTS, but now with OpenStack
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Havana from the Ubuntu Cloud Archive. KVM is the hypervisor, deployed
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using `FAI <http://fai-project.org/>`_ and Puppet for configuration
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management. The FAI and Puppet combination is used lab-wide, not only
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for OpenStack. There is a single cloud controller node, which also acts
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as network controller, with the remainder of the server hardware
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dedicated to compute nodes.
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Host aggregates and instance-type extra specs are used to provide two
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different resource allocation ratios. The default resource allocation
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ratios we use are 4:1 CPU and 1.5:1 RAM. Compute-intensive workloads use
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instance types that require non-oversubscribed hosts where ``cpu_ratio``
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and ``ram_ratio`` are both set to 1.0. Since we have hyper-threading
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enabled on our compute nodes, this provides one vCPU per CPU thread, or
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two vCPUs per physical core.
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With our upgrade to Grizzly in August 2013, we moved to OpenStack
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Networking, neutron (quantum at the time). Compute nodes have
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two-gigabit network interfaces and a separate management card for IPMI
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management. One network interface is used for node-to-node
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communications. The other is used as a trunk port for OpenStack managed
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VLANs. The controller node uses two bonded 10g network interfaces for
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its public IP communications. Big pipes are used here because images are
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served over this port, and it is also used to connect to iSCSI storage,
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back-ending the image storage and database. The controller node also has
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a gigabit interface that is used in trunk mode for OpenStack managed
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VLAN traffic. This port handles traffic to the dhcp-agent and
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metadata-proxy.
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We approximate the older ``nova-network`` multi-host HA setup by using
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"provider VLAN networks" that connect instances directly to existing
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publicly addressable networks and use existing physical routers as their
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default gateway. This means that if our network controller goes down,
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running instances still have their network available, and no single
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Linux host becomes a traffic bottleneck. We are able to do this because
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we have a sufficient supply of IPv4 addresses to cover all of our
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instances and thus don't need NAT and don't use floating IP addresses.
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We provide a single generic public network to all projects and
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additional existing VLANs on a project-by-project basis as needed.
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Individual projects are also allowed to create their own private GRE
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based networks.
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Resources
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---------
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- `CSAIL homepage <https://www.csail.mit.edu/>`_
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DAIR
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~~~~
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Who uses it: DAIR is an integrated virtual environment that leverages
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the CANARIE network to develop and test new information communication
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technology (ICT) and other digital technologies. It combines such
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digital infrastructure as advanced networking and cloud computing and
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storage to create an environment for developing and testing innovative
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ICT applications, protocols, and services; performing at-scale
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experimentation for deployment; and facilitating a faster time to
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market.
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Deployment
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----------
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DAIR is hosted at two different data centers across Canada: one in
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Alberta and the other in Quebec. It consists of a cloud controller at
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each location, although, one is designated the "master" controller that
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is in charge of central authentication and quotas. This is done through
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custom scripts and light modifications to OpenStack. DAIR is currently
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running Havana.
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For Object Storage, each region has a swift environment.
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A NetApp appliance is used in each region for both block storage and
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instance storage. There are future plans to move the instances off the
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NetApp appliance and onto a distributed file system such as :term:`Ceph` or
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GlusterFS.
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VlanManager is used extensively for network management. All servers have
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two bonded 10GbE NICs that are connected to two redundant switches. DAIR
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is set up to use single-node networking where the cloud controller is
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the gateway for all instances on all compute nodes. Internal OpenStack
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traffic (for example, storage traffic) does not go through the cloud
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controller.
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Resources
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---------
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- `DAIR homepage <https://www.canarie.ca/cloud/>`__
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CERN
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~~~~
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Who uses it: researchers at CERN (European Organization for Nuclear
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Research) conducting high-energy physics research.
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Deployment
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----------
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The environment is largely based on Scientific Linux 6, which is Red Hat
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compatible. We use KVM as our primary hypervisor, although tests are
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ongoing with Hyper-V on Windows Server 2008.
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We use the Puppet Labs OpenStack modules to configure Compute, Image
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service, Identity, and dashboard. Puppet is used widely for instance
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configuration, and Foreman is used as a GUI for reporting and instance
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provisioning.
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Users and groups are managed through Active Directory and imported into
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the Identity service using LDAP. CLIs are available for nova and
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Euca2ools to do this.
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There are three clouds currently running at CERN, totaling about 4,700
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compute nodes, with approximately 120,000 cores. The CERN IT cloud aims
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to expand to 300,000 cores by 2015.
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Resources
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---------
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- `OpenStack in Production: A tale of 3 OpenStack
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Clouds <https://openstack-in-production.blogspot.de/2013/09/a-tale-of-3-openstack-clouds-50000.html>`_
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- `Review of CERN Data Centre
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Infrastructure <http://cds.cern.ch/record/1457989/files/chep%202012%20CERN%20infrastructure%20final.pdf?version=1>`_
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- `CERN Cloud Infrastructure User
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Guide <https://clouddocs.web.cern.ch>`_
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