openstack-manuals/doc/admin-guide-cloud/source/compute_arch.rst
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===================
System architecture
===================
OpenStack Compute contains several main components.
- The :term:`cloud controller` represents the global state and interacts with
the other components. The ``API server`` acts as the web services
front end for the cloud controller. The ``compute controller``
provides compute server resources and usually also contains the
Compute service.
- The ``object store`` is an optional component that provides storage
services; you can also use OpenStack Object Storage instead.
- An ``auth manager`` provides authentication and authorization
services when used with the Compute system; you can also use
OpenStack Identity as a separate authentication service instead.
- A ``volume controller`` provides fast and permanent block-level
storage for the compute servers.
- The ``network controller`` provides virtual networks to enable
compute servers to interact with each other and with the public
network. You can also use OpenStack Networking instead.
- The ``scheduler`` is used to select the most suitable compute
controller to host an instance.
Compute uses a messaging-based, ``shared nothing`` architecture. All
major components exist on multiple servers, including the compute,
volume, and network controllers, and the object store or image service.
The state of the entire system is stored in a database. The cloud
controller communicates with the internal object store using HTTP, but
it communicates with the scheduler, network controller, and volume
controller using AMQP (advanced message queuing protocol). To avoid
blocking a component while waiting for a response, Compute uses
asynchronous calls, with a callback that is triggered when a response is
received.
Hypervisors
~~~~~~~~~~~
Compute controls hypervisors through an API server. Selecting the best
hypervisor to use can be difficult, and you must take budget, resource
constraints, supported features, and required technical specifications
into account. However, the majority of OpenStack development is done on
systems using KVM and Xen-based hypervisors. For a detailed list of
features and support across different hypervisors, see
http://wiki.openstack.org/HypervisorSupportMatrix.
You can also orchestrate clouds using multiple hypervisors in different
availability zones. Compute supports the following hypervisors:
- `Baremetal <https://wiki.openstack.org/wiki/Ironic>`__
- `Docker <https://www.docker.io>`__
- `Hyper-V <http://www.microsoft.com/en-us/server-cloud/hyper-v-server/default.aspx>`__
- `Kernel-based Virtual Machine
(KVM) <http://www.linux-kvm.org/page/Main_Page>`__
- `Linux Containers (LXC) <https://linuxcontainers.org/>`__
- `Quick Emulator (QEMU) <http://wiki.qemu.org/Manual>`__
- `User Mode Linux (UML) <http://user-mode-linux.sourceforge.net/>`__
- `VMware
vSphere <http://www.vmware.com/products/vsphere-hypervisor/support.html>`__
- `Xen <http://www.xen.org/support/documentation.html>`__
For more information about hypervisors, see the
`Hypervisors <http://docs.openstack.org/liberty/config-reference/content/section_compute-hypervisors.html>`__
section in the OpenStack Configuration Reference.
Tenants, users, and roles
~~~~~~~~~~~~~~~~~~~~~~~~~
The Compute system is designed to be used by different consumers in the
form of tenants on a shared system, and role-based access assignments.
Roles control the actions that a user is allowed to perform.
Tenants are isolated resource containers that form the principal
organizational structure within the Compute service. They consist of an
individual VLAN, and volumes, instances, images, keys, and users. A user
can specify the tenant by appending ``project_id`` to their access key.
If no tenant is specified in the API request, Compute attempts to use a
tenant with the same ID as the user.
For tenants, you can use quota controls to limit the:
- Number of volumes that can be launched.
- Number of processor cores and the amount of RAM that can be
allocated.
- Floating IP addresses assigned to any instance when it launches. This
allows instances to have the same publicly accessible IP addresses.
- Fixed IP addresses assigned to the same instance when it launches.
This allows instances to have the same publicly or privately
accessible IP addresses.
Roles control the actions a user is allowed to perform. By default, most
actions do not require a particular role, but you can configure them by
editing the :file:`policy.json` file for user roles. For example, a rule can
be defined so that a user must have the ``admin`` role in order to be
able to allocate a public IP address.
A tenant limits users' access to particular images. Each user is
assigned a user name and password. Keypairs granting access to an
instance are enabled for each user, but quotas are set, so that each
tenant can control resource consumption across available hardware
resources.
.. note::
Earlier versions of OpenStack used the term ``project`` instead of
``tenant``. Because of this legacy terminology, some command-line tools
use ``--project_id`` where you would normally expect to enter a
tenant ID.
Block storage
~~~~~~~~~~~~~
OpenStack provides two classes of block storage: ephemeral storage
and persistent volume.
**Ephemeral storage**
Ephemeral storage includes a root ephemeral volume and an additional
ephemeral volume.
The root disk is associated with an instance, and exists only for the
life of this very instance. Generally, it is used to store an
instance's root file system, persists across the guest operating system
reboots, and is removed on an instance deletion. The amount of the root
ephemeral volume is defined by the flavor of an instance.
In addition to the ephemeral root volume, all default types of flavors,
except ``m1.tiny``, which is the smallest one, provide an additional
ephemeral block device sized between 20 and 160 GB (a configurable value
to suit an environment). It is represented as a raw block device with no
partition table or file system. A cloud-aware operating system can
discover, format, and mount such a storage device. OpenStack Compute
defines the default file system for different operating systems as Ext4
for Linux distributions, VFAT for non-Linux and non-Windows operating
systems, and NTFS for Windows. However, it is possible to specify any
other filesystem type by using ``virt_mkfs`` or
``default_ephemeral_format`` configuration options.
.. note::
For example, the ``cloud-init`` package included into an Ubuntu's stock
cloud image, by default, formats this space as an Ext4 file system
and mounts it on :file:`/mnt`. This is a cloud-init feature, and is not
an OpenStack mechanism. OpenStack only provisions the raw storage.
**Persistent volume**
A persistent volume is represented by a persistent virtualized block
device independent of any particular instance, and provided by OpenStack
Block Storage.
Only a single configured instance can access a persistent volume.
Multiple instances cannot access a persistent volume. This type of
configuration requires a traditional network file system to allow
multiple instances accessing the persistent volume. It also requires a
traditional network file system like NFS, CIFS, or a cluster file system
such as GlusterFS. These systems can be built within an OpenStack
cluster, or provisioned outside of it, but OpenStack software does not
provide these features.
You can configure a persistent volume as bootable and use it to provide
a persistent virtual instance similar to the traditional non-cloud-based
virtualization system. It is still possible for the resulting instance
to keep ephemeral storage, depending on the flavor selected. In this
case, the root file system can be on the persistent volume, and its
state is maintained, even if the instance is shut down. For more
information about this type of configuration, see the `OpenStack
Configuration Reference
<http://docs.openstack.org/liberty/config-reference/content/>`__.
.. note::
A persistent volume does not provide concurrent access from multiple
instances. That type of configuration requires a traditional network
file system like NFS, or CIFS, or a cluster file system such as
GlusterFS. These systems can be built within an OpenStack cluster,
or provisioned outside of it, but OpenStack software does not
provide these features.
EC2 compatibility API
~~~~~~~~~~~~~~~~~~~~~
In addition to the native compute API, OpenStack provides an
EC2-compatible API. This API allows EC2 legacy workflows built for EC2
to work with OpenStack. For more information and configuration options
about this compatibility API, see the `OpenStack Configuration
Reference <http://docs.openstack.org/liberty/config-reference/content/
configuring-ec2-api.html>`__.
Numerous third-party tools and language-specific SDKs can be used to
interact with OpenStack clouds, using both native and compatibility
APIs. Some of the more popular third-party tools are:
Euca2ools
A popular open source command-line tool for interacting with the EC2
API. This is convenient for multi-cloud environments where EC2 is
the common API, or for transitioning from EC2-based clouds to
OpenStack. For more information, see the `euca2ools
site <https://www.eucalyptus.com/docs/eucalyptus/4.1.2/index.html#shared/euca2ools_section.html>`__.
Hybridfox
A Firefox browser add-on that provides a graphical interface to many
popular public and private cloud technologies, including OpenStack.
For more information, see the `hybridfox
site <http://code.google.com/p/hybridfox/>`__.
boto
A Python library for interacting with Amazon Web Services. It can be
used to access OpenStack through the EC2 compatibility API. For more
information, see the `boto project page on
GitHub <https://github.com/boto/boto>`__.
fog
A Ruby cloud services library. It provides methods for interacting
with a large number of cloud and virtualization platforms, including
OpenStack. For more information, see the `fog
site <https://rubygems.org/gems/fog>`__.
php-opencloud
A PHP SDK designed to work with most OpenStack- based cloud
deployments, as well as Rackspace public cloud. For more
information, see the `php-opencloud
site <http://www.php-opencloud.com>`__.
Building blocks
~~~~~~~~~~~~~~~
In OpenStack the base operating system is usually copied from an image
stored in the OpenStack Image service. This is the most common case and
results in an ephemeral instance that starts from a known template state
and loses all accumulated states on virtual machine deletion. It is also
possible to put an operating system on a persistent volume in the
OpenStack Block Storage volume system. This gives a more traditional
persistent system that accumulates states which are preserved on the
OpenStack Block Storage volume across the deletion and re-creation of
the virtual machine. To get a list of available images on your system,
run::
$ nova image-list
+--------------------------------------+-----------------------------+--------+---------+
| ID | Name | Status | Server |
+--------------------------------------+-----------------------------+--------+---------+
| aee1d242-730f-431f-88c1-87630c0f07ba | Ubuntu 14.04 cloudimg amd64 | ACTIVE | |
| 0b27baa1-0ca6-49a7-b3f4-48388e440245 | Ubuntu 14.10 cloudimg amd64 | ACTIVE | |
| df8d56fc-9cea-4dfd-a8d3-28764de3cb08 | jenkins | ACTIVE | |
+--------------------------------------+-----------------------------+--------+---------+
The displayed image attributes are:
``ID``
Automatically generated UUID of the image
``Name``
Free form, human-readable name for image
``Status``
The status of the image. Images marked ``ACTIVE`` are available for
use.
``Server``
For images that are created as snapshots of running instances, this
is the UUID of the instance the snapshot derives from. For uploaded
images, this field is blank.
Virtual hardware templates are called ``flavors``. The default
installation provides five flavors. By default, these are configurable
by admin users, however that behavior can be changed by redefining the
access controls for ``compute_extension:flavormanage`` in
:file:`/etc/nova/policy.json` on the ``compute-api`` server.
For a list of flavors that are available on your system::
$ nova flavor-list
+-----+-----------+-----------+------+-----------+------+-------+-------------+-----------+
| ID | Name | Memory_MB | Disk | Ephemeral | Swap | VCPUs | RXTX_Factor | Is_Public |
+-----+-----------+-----------+------+-----------+------+-------+-------------+-----------+
| 1 | m1.tiny | 512 | 1 | 0 | | 1 | 1.0 | True |
| 2 | m1.small | 2048 | 20 | 0 | | 1 | 1.0 | True |
| 3 | m1.medium | 4096 | 40 | 0 | | 2 | 1.0 | True |
| 4 | m1.large | 8192 | 80 | 0 | | 4 | 1.0 | True |
| 5 | m1.xlarge | 16384 | 160 | 0 | | 8 | 1.0 | True |
+-----+-----------+-----------+------+-----------+------+-------+-------------+-----------+
Compute service architecture
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
These basic categories describe the service architecture and information
about the cloud controller.
**API server**
At the heart of the cloud framework is an API server, which makes
command and control of the hypervisor, storage, and networking
programmatically available to users.
The API endpoints are basic HTTP web services which handle
authentication, authorization, and basic command and control functions
using various API interfaces under the Amazon, Rackspace, and related
models. This enables API compatibility with multiple existing tool sets
created for interaction with offerings from other vendors. This broad
compatibility prevents vendor lock-in.
**Message queue**
A messaging queue brokers the interaction between compute nodes
(processing), the networking controllers (software which controls
network infrastructure), API endpoints, the scheduler (determines which
physical hardware to allocate to a virtual resource), and similar
components. Communication to and from the cloud controller is handled by
HTTP requests through multiple API endpoints.
A typical message passing event begins with the API server receiving a
request from a user. The API server authenticates the user and ensures
that they are permitted to issue the subject command. The availability
of objects implicated in the request is evaluated and, if available, the
request is routed to the queuing engine for the relevant workers.
Workers continually listen to the queue based on their role, and
occasionally their type host name. When an applicable work request
arrives on the queue, the worker takes assignment of the task and begins
executing it. Upon completion, a response is dispatched to the queue
which is received by the API server and relayed to the originating user.
Database entries are queried, added, or removed as necessary during the
process.
**Compute worker**
Compute workers manage computing instances on host machines. The API
dispatches commands to compute workers to complete these tasks:
- Run instances
- Terminate instances
- Reboot instances
- Attach volumes
- Detach volumes
- Get console output
**Network Controller**
The Network Controller manages the networking resources on host
machines. The API server dispatches commands through the message queue,
which are subsequently processed by Network Controllers. Specific
operations include:
- Allocating fixed IP addresses
- Configuring VLANs for projects
- Configuring networks for compute nodes