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ceph/doc/architecture.rst
John Wilkins b71ec9c25a doc: Added some detail. Calculating PGs, maps; reorganized a bit. 
fixes: #2968

Signed-off-by: John Wilkins <john.wilkins@inktank.com>
2013-04-22 21:02:45 -07:00

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==============
Architecture
==============
Ceph provides an infinitely scalable Object Store based upon a :abbr:`RADOS
(Reliable Autonomic Distributed Object Store)`, which you can read about in
`RADOS - A Scalable, Reliable Storage Service for Petabyte-scale Storage
Clusters`_. Storage clients and OSDs both use the CRUSH algorithm to efficiently
compute information about data location, instead of having to depend on a
central lookup table. Ceph's high-level features include providing a native
interface to the Object Store via ``librados``, and a number of service
interfaces built on top of ``librados``. These include:
- **Block Devices:** The RADOS Block Device (RBD) service provides
resizable, thin-provisioned block devices with snapshotting and
cloning. Ceph stripes a block device across the cluster for high
performance. Ceph supports both kernel objects (KO) and a
QEMU hypervisor that uses ``librbd`` directly--avoiding the
kernel object overhead for virtualized systems.
- **RESTful Gateway:** The RADOS Gateway (RGW) service provides
RESTful APIs with interfaces that are compatible with Amazon S3
and OpenStack Swift.
- **Ceph FS**: The Ceph Filesystem (CephFS) service provides
a POSIX compliant filesystem usable with ``mount`` or as
a filesytem in user space (FUSE).
Ceph can run additional instances of OSDs, MDSs, and monitors for scalability
and high availability. The following diagram depicts the high-level
architecture.
.. ditaa:: +--------+ +----------+ +-------+ +--------+ +------+
| RBD KO | | QeMu RBD | | RGW | | CephFS | | FUSE |
+--------+ +----------+ +-------+ +--------+ +------+
+---------------------+ +-----------------+
| librbd | | libcephfs |
+---------------------+ +-----------------+
+---------------------------------------------------+
| librados (C, C++, Java, Python, PHP, etc.) |
+---------------------------------------------------+
+---------------+ +---------------+ +---------------+
| OSDs | | MDSs | | Monitors |
+---------------+ +---------------+ +---------------+
Ceph's Object Store takes data from clients--whether it comes through RBD, RGW,
CephFS, or a custom implementation you create using ``librados``--and stores
them as objects. Each object corresponds to a file in a filesystem, which is
typically stored on a single storage disk. ``ceph-osd`` daemons handle the
read/write operations on the storage disks.
.. ditaa:: /-----\ +-----+ +-----+
| obj |------>| {d} |------>| {s} |
\-----/ +-----+ +-----+
Object File Disk
OSDs store all data as objects in a flat namespace (e.g., no hierarchy of
directories). An object has an identifier, binary data, and metadata consisting
of a set of name/value pairs. The semantics are completely up to the client. For
example, CephFS uses metadata to store file attributes such as the file owner,
created date, last modified date, and so forth.
.. ditaa:: /------+------------------------------+----------------\
| ID | Binary Data | Metadata |
+------+------------------------------+----------------+
| 1234 | 0101010101010100110101010010 | name1 = value1 |
| | 0101100001010100110101010010 | name2 = value2 |
| | 0101100001010100110101010010 | nameN = valueN |
\------+------------------------------+----------------/
.. _RADOS - A Scalable, Reliable Storage Service for Petabyte-scale Storage Clusters: http://ceph.com/papers/weil-rados-pdsw07.pdf
.. _how-ceph-scales:
How Ceph Scales
===============
In traditional architectures, clients talk to a centralized component (e.g., a
gateway, broker, API, facade, etc.), which acts as a single point of entry to a
complex subsystem. This imposes a limit to both performance and scalability,
while introducing a single point of failure (i.e., if the centralized component
goes down, the whole system goes down, too). Ceph eliminates this problem.
CRUSH Background
----------------
Key to Ceph’s design is the autonomous, self-healing, and intelligent Object
Storage Daemon (OSD). Storage clients and OSDs both use the CRUSH algorithm to
efficiently compute information about data containers on demand, instead of
having to depend on a central lookup table. CRUSH provides a better data
management mechanism compared to older approaches, and enables massive scale by
cleanly distributing the work to all the clients and OSDs in the cluster. CRUSH
uses intelligent data replication to ensure resiliency, which is better suited
to hyper-scale storage. Let's take a deeper look at how CRUSH works to enable
modern cloud storage infrastructures.
Cluster Map
-----------
Ceph depends upon clients and OSDs having knowledge of the cluster topology,
which is inclusive of 5 maps collectively referred to as the "Cluster Map":
#. **The Monitor Map:** Contains the cluster ``fsid``, the position, name
address and port of each monitor. It also indicates the current epoch,
when the map was created, and the last time it changed. To view a monitor
map, execute ``ceph mon dump``.
#. **The OSD Map:** Contains the cluster ``fsid``, when the map was created and
last modified, a list of pools, replica sizes, PG numbers, a list of OSDs
and their status (e.g., ``up``, ``in``). To view an OSD map, execute
``ceph osd dump``.
#. **The PG Map:** Contains the PG version, its time stamp, the last OSD
map epoch, the full ratios, and details on each placement group such as
the PG ID, the `Up Set`, the `Acting Set`, the state of the PG (e.g.,
``active + clean``), and data usage statistics for each pool.
#. **The CRUSH Map:** Contains a list of storage devices, the failure domain
hierarchy (e.g., device, host, rack, row, room, etc.), and rules for
traversing the hierarchy when storing data. To view a CRUSH map, execute
``ceph osd getcrushmap -o {filename}``; then, decompile it by executing
``crushtool -d {comp-crushmap-filename} -o {decomp-crushmap-filename}``.
You can view the decompiled map in a text editor or with ``cat``.
#. **The MDS Map:** Contains the current MDS map epoch, when the map was
created, and the last time it changed. It also contains the pool for
storing metadata, a list of metadata servers, and which metadata servers
are ``up`` and ``in``. To view an MDS map, execute ``ceph mds dump``.
Each map maintains an iterative history of its operating state changes, which
enables Ceph to monitor the cluster. The maps that are the most relevant to
scalability include the CRUSH Map, the OSD Map, and the PG Map.
Monitor Quorums
---------------
Ceph's monitors maintain a master copy of the cluster map. So Ceph daemons and
clients merely contact the monitor periodically to ensure they have the most
recent copy of the cluster map. Ceph monitors are light-weight processes, but
for added reliability and fault tolerance, Ceph supports distributed monitors.
Ceph must have agreement among various monitor instances regarding the state of
the cluster. To establish a consensus, Ceph always uses a majority of
monitors (e.g., 1, 3-*n*, etc.) and the `Paxos`_ algorithm in order to
establish a consensus.
For details on configuring monitors, see the `Monitor Config Reference`_.
.. _Paxos: http://en.wikipedia.org/wiki/Paxos_(computer_science)
.. _Monitor Config Reference: ../rados/configuration/mon-config-ref
Smart Daemons
-------------
Ceph's cluster map determines whether a node in a network is ``in`` the
Ceph cluster or ``out`` of the Ceph cluster.
.. ditaa:: +----------------+
| |
| Node ID In |
| |
+----------------+
^
|
|
v
+----------------+
| |
| Node ID Out |
| |
+----------------+
In many clustered architectures, the primary purpose of cluster membership
is so that a centralized interface knows which hosts it can access. Ceph
takes it a step further: Ceph's nodes are cluster aware. Each node knows
about other nodes in the cluster. This enables Ceph's monitor, OSD, and
metadata server daemons to interact directly with each other. One major
benefit of this approach is that Ceph can utilize the CPU and RAM of its
nodes to easily perform tasks that would bog down a centralized server.
Ceph OSDs join a cluster and report on their status. At the lowest level,
the OSD status is ``up`` or ``down`` reflecting whether or not it is
running and able to service requests. If an OSD is ``down`` and ``in``
the cluster, this status may indicate the failure of the OSD.
With peer awareness, OSDs can communicate with other OSDs and monitors
to perform tasks. OSDs take client requests to read data from or write
data to pools, which have placement groups. When a client makes a request
to write data to a primary OSD, the primary OSD knows how to determine
which OSDs have the placement groups for the replica copies, and then
update those OSDs. This means that OSDs can also take requests from
other OSDs. With multiple replicas of data across OSDs, OSDs can also
"peer" to ensure that the placement groups are in sync. See `Monitoring
OSDs and PGs`_ for additional details.
If an OSD is not running (e.g., it crashes), the OSD cannot notify the monitor
that it is ``down``. The monitor can ping an OSD periodically to ensure that it
is running. However, Ceph also empowers OSDs to determine if a neighboring OSD
is ``down``, to update the cluster map and to report it to the monitor(s). When
an OSD is ``down``, the data in the placement group is said to be ``degraded``.
If the OSD is ``down`` and ``in``, but subsequently taken ``out`` of the
cluster, the OSDs receive an update to the cluster map and rebalance the
placement groups within the cluster automatically. See `Heartbeats`_ for
additional details.
.. _Monitoring OSDs and PGs: ../rados/operations/monitoring-osd-pg
.. _Heartbeats: ../rados/configuration/mon-osd-interaction
Calculating PG IDs
------------------
When a Ceph client binds to a monitor, it retrieves the latest copy of the
cluster map. With the cluster map, the client knows about all of the monitors,
OSDs, and metadata servers in the cluster. However, it doesn't know anything
about object locations. Object locations get computed.
The only input required by the client is the object ID and the pool.
It's simple: Ceph stores data in named pools (e.g., "liverpool"). When a client
wants to store a named object (e.g., "john," "paul," "george," "ringo", etc.)
it calculates a placement group using the object name, a hash code, the
number of OSDs in the cluster and the pool name. Ceph clients use the following
steps to compute PG IDs.
#. The client inputs the pool ID and the object ID. (e.g., pool = "liverpool"
and object-id = "john")
#. CRUSH takes the object ID and hashes it.
#. CRUSH calculates the hash modulo the number of OSDs. (e.g., ``0x58``) to get a PG ID.
#. CRUSH gets the pool ID given the pool name (e.g., "liverpool" = ``4``)
#. CRUSH prepends the pool ID to the pool ID to the PG ID (e.g., ``4.0x58``).
Computing object locations is much faster than performing object location query
over a chatty session. The :abbr:`CRUSH (Controlled Replication Under Scalable
Hashing)` algorithm allows a client to compute where objects *should* be stored,
and enables the client to contact the primary OSD to store or retrieve the
objects.
About Pools
-----------
The Ceph storage system supports the notion of 'Pools', which are logical
partitions for storing objects. Pools set ownership/access, the number of
object replicas, the number of placement groups, and the CRUSH rule set to use.
Each pool has a number of placement groups that are mapped dynamically to OSDs.
When clients store objects, CRUSH maps each object to a placement group.
Mapping PGs to OSDs
-------------------
Mapping objects to placement groups instead of directly to OSDs creates a layer
of indirection between the OSD and the client. The cluster must be able to grow
(or shrink) and rebalance where it stores objects dynamically. If the client
"knew" which OSD had which object, that would create a tight coupling between
the client and the OSD. Instead, the CRUSH algorithm maps each object to a
placement group and then maps each placement group to one or more OSDs. This
layer of indirection allows Ceph to rebalance dynamically when new OSDs come
online. The following diagram depicts how CRUSH maps objects to placement
groups, and placement groups to OSDs.
.. ditaa::
/-----\ /-----\ /-----\ /-----\ /-----\
| obj | | obj | | obj | | obj | | obj |
\-----/ \-----/ \-----/ \-----/ \-----/
| | | | |
+--------+--------+ +---+----+
| |
v v
+-----------------------+ +-----------------------+
| Placement Group #1 | | Placement Group #2 |
| | | |
+-----------------------+ +-----------------------+
| |
| +-----------------------+---+
+------+------+-------------+ |
| | | |
v v v v
/----------\ /----------\ /----------\ /----------\
| | | | | | | |
| OSD #1 | | OSD #2 | | OSD #3 | | OSD #4 |
| | | | | | | |
\----------/ \----------/ \----------/ \----------/
With a copy of the cluster map and the CRUSH algorithm, the client can compute
exactly which OSD to use when reading or writing a particular object.
Cluster-side Replication
------------------------
The OSD daemon also uses the CRUSH algorithm, but the OSD daemon uses it to
compute where replicas of objects should be stored (and for rebalancing). In a
typical write scenario, a client uses the CRUSH algorithm to compute where to
store an object, maps the object to a pool and placement group, then looks at
the CRUSH map to identify the primary OSD for the placement group.
The client writes the object to the identified placement group in the primary
OSD. Then, the primary OSD with its own copy of the CRUSH map identifies the
secondary and tertiary OSDs for replication purposes, and replicates the object
to the appropriate placement groups in the secondary and tertiary OSDs (as many
OSDs as additional replicas), and responds to the client once it has confirmed
the object was stored successfully.
.. ditaa::
+----------+
| Client |
| |
+----------+
* ^
Write (1) | | Ack (6)
| |
v *
+-------------+
| Primary OSD |
| |
+-------------+
* ^ ^ *
Write (2) | | | | Write (3)
+------+ | | +------+
| +------+ +------+ |
| | Ack (4) Ack (5)| |
v * * v
+---------------+ +---------------+
| Secondary OSD | | Tertiary OSD |
| | | |
+---------------+ +---------------+
Since any network device has a limit to the number of concurrent connections it
can support, a centralized system has a low physical limit at high scales. By
enabling clients to contact nodes directly, Ceph increases both performance and
total system capacity simultaneously, while removing a single point of failure.
Ceph clients can maintain a session when they need to, and with a particular OSD
instead of a centralized server. For a detailed discussion of CRUSH, see `CRUSH
- Controlled, Scalable, Decentralized Placement of Replicated Data`_.
.. _CRUSH - Controlled, Scalable, Decentralized Placement of Replicated Data: http://ceph.com/papers/weil-crush-sc06.pdf
Extending Ceph
--------------
.. todo:: explain "classes"
How Ceph Clients Stripe Data
============================
Storage devices have throughput limitations, which impact performance and
scalability. So storage systems often support `striping`_--storing sequential
pieces of information across across multiple storage devices--to increase
throughput and performance. The most common form of data striping comes from
`RAID`_. The RAID type most similar to Ceph's striping is `RAID 0`_, or a
'striped volume.' Ceph's striping offers the throughput of RAID 0 striping,
the reliability of n-way RAID mirroring and faster recovery.
Ceph provides three types of clients: block device, CephFS filesystem, and
Gateway. A Ceph client converts its data from the representation format it
provides to its users (a block device image, RESTful objects, CephFS filesystem
directories) into objects for storage in the Object Store. The simplest Ceph
striping format involves a stripe count of 1 object. Clients write stripe units
to an object until the object is at its maximum capacity, and then create
another object for additional stripes of data. The simplest form of striping may
be sufficient for small block device images, S3 or Swift objects, or CephFS
files. However, this simple form doesn't take maximum advantage of Ceph's
ability to distribute data across placement groups, and consequently doesn't
improve performance very much. The following diagram depicts the simplest form
of striping:
.. ditaa::
+---------------+
| Client Data |
| Format |
| cCCC |
+---------------+
|
+--------+-------+
| |
v v
/-----------\ /-----------\
| Begin cCCC| | Begin cCCC|
| Object 0 | | Object 1 |
+-----------+ +-----------+
| stripe | | stripe |
| unit 1 | | unit 5 |
+-----------+ +-----------+
| stripe | | stripe |
| unit 2 | | unit 6 |
+-----------+ +-----------+
| stripe | | stripe |
| unit 3 | | unit 7 |
+-----------+ +-----------+
| stripe | | stripe |
| unit 4 | | unit 8 |
+-----------+ +-----------+
| End cCCC | | End cCCC |
| Object 0 | | Object 1 |
\-----------/ \-----------/
If you anticipate large images sizes, large S3 or Swift objects (video), or
large CephFS directories, you may see considerable read/write performance
improvements by striping client data over mulitple objects within an object set.
Significant write performance occurs when the client writes the stripe units to
their corresponding objects in parallel. Since objects get mapped to different
placement groups and further mapped to different OSDs, each write occurs in
parallel at the maximum write speed. A write to a single disk would be limited
by the head movement (e.g. 6ms per seek) and bandwidth of that one device (e.g.
100MB/s). By spreading that write over multiple objects (which map to different
placement groups and OSDs) Ceph can reduce the number of seeks per drive and
combine the throughput of multiple drives to achieve much faster write (or read)
speeds.
In the following diagram, client data gets striped across an object set
(``object set 1`` in the following diagram) consisting of 4 objects, where the
first stripe unit is ``stripe unit 0`` in ``object 0``, and the fourth stripe
unit is ``stripe unit 3`` in ``object 3``. After writing the fourth stripe, the
client determines if the object set is full. If the object set is not full, the
client begins writing a stripe to the first object again (``object 0`` in the
following diagram). If the object set is full, the client creates a new object
set (``object set 2`` in the following diagram), and begins writing to the first
stripe (``stripe unit 16``) in the first object in the new object set (``object
4`` in the diagram below).
.. ditaa::
+---------------+
| Client Data |
| Format |
| cCCC |
+---------------+
|
+-----------------+--------+--------+-----------------+
| | | | +--\
v v v v |
/-----------\ /-----------\ /-----------\ /-----------\ |
| Begin cCCC| | Begin cCCC| | Begin cCCC| | Begin cCCC| |
| Object 0 | | Object 1 | | Object 2 | | Object 3 | |
+-----------+ +-----------+ +-----------+ +-----------+ |
| stripe | | stripe | | stripe | | stripe | |
| unit 0 | | unit 1 | | unit 2 | | unit 3 | |
+-----------+ +-----------+ +-----------+ +-----------+ |
| stripe | | stripe | | stripe | | stripe | +-\
| unit 4 | | unit 5 | | unit 6 | | unit 7 | | Object
+-----------+ +-----------+ +-----------+ +-----------+ +- Set
| stripe | | stripe | | stripe | | stripe | | 1
| unit 8 | | unit 9 | | unit 10 | | unit 11 | +-/
+-----------+ +-----------+ +-----------+ +-----------+ |
| stripe | | stripe | | stripe | | stripe | |
| unit 12 | | unit 13 | | unit 14 | | unit 15 | |
+-----------+ +-----------+ +-----------+ +-----------+ |
| End cCCC | | End cCCC | | End cCCC | | End cCCC | |
| Object 0 | | Object 1 | | Object 2 | | Object 3 | |
\-----------/ \-----------/ \-----------/ \-----------/ |
|
+--/
+--\
|
/-----------\ /-----------\ /-----------\ /-----------\ |
| Begin cCCC| | Begin cCCC| | Begin cCCC| | Begin cCCC| |
| Object 4 | | Object 5 | | Object 6 | | Object 7 | |
+-----------+ +-----------+ +-----------+ +-----------+ |
| stripe | | stripe | | stripe | | stripe | |
| unit 16 | | unit 17 | | unit 18 | | unit 19 | |
+-----------+ +-----------+ +-----------+ +-----------+ |
| stripe | | stripe | | stripe | | stripe | +-\
| unit 20 | | unit 21 | | unit 22 | | unit 23 | | Object
+-----------+ +-----------+ +-----------+ +-----------+ +- Set
| stripe | | stripe | | stripe | | stripe | | 2
| unit 24 | | unit 25 | | unit 26 | | unit 27 | +-/
+-----------+ +-----------+ +-----------+ +-----------+ |
| stripe | | stripe | | stripe | | stripe | |
| unit 28 | | unit 29 | | unit 30 | | unit 31 | |
+-----------+ +-----------+ +-----------+ +-----------+ |
| End cCCC | | End cCCC | | End cCCC | | End cCCC | |
| Object 4 | | Object 5 | | Object 6 | | Object 7 | |
\-----------/ \-----------/ \-----------/ \-----------/ |
|
+--/
Three important variables determine how Ceph stripes data:
- **Object Size:** Objects in the Ceph Object Store have a maximum
configurable size (e.g., 2MB, 4MB, etc.). The object size should be large
enough to accomodate many stripe units, and should be a multiple of
the stripe unit.
- **Stripe Width:** Stripes have a configurable unit size (e.g., 64kb).
The Ceph client divides the data it will write to objects into equally
sized stripe units, except for the last stripe unit. A stripe width,
should be a fraction of the Object Size so that an object may contain
many stripe units.
- **Stripe Count:** The Ceph client writes a sequence of stripe units
over a series of objects determined by the stripe count. The series
of objects is called an object set. After the Ceph client writes to
the last object in the object set, it returns to the first object in
the object set.
.. important:: Test the performance of your striping configuration before
putting your cluster into production. You CANNOT change these striping
parameters after you stripe the data and write it to objects.
Once the Ceph client has striped data to stripe units and mapped the stripe
units to objects, Ceph's CRUSH algorithm maps the objects to placement groups,
and the placement groups to OSDs before the objects are stored as files on a
storage disk. See `How Ceph Scales`_ for details.
.. important:: Striping is independent of object replicas. Since CRUSH
replicates objects across OSDs, stripes get replicated automatically.
.. _striping: http://en.wikipedia.org/wiki/Data_striping
.. _RAID: http://en.wikipedia.org/wiki/RAID
.. _RAID 0: http://en.wikipedia.org/wiki/RAID_0#RAID_0
.. topic:: S3/Swift Objects and Object Store Objects Compared
Ceph's Gateway uses the term *object* to describe the data it stores.
S3 and Swift objects from the Gateway are not the same as the objects Ceph
writes to the Object Store. Gateway objects are mapped to Ceph objects that
get written to the Object Store. The S3 and Swift objects do not necessarily
correspond in a 1:1 manner with an object stored in the Object Store. It is
possible for an S3 or Swift object to map to multiple Ceph objects.
.. note:: Since a client writes to a single pool, all data striped into objects
get mapped to placement groups in the same pool. So they use the same CRUSH
map and the same access controls.
.. tip:: The objects Ceph stores in the Object Store are not striped. RGW, RBD
and CephFS automatically stripe their data over multiple RADOS objects.
Clients that write directly to the Object Store via ``librados`` must
peform the the striping (and parallel I/O) for themselves to obtain these
benefits.
Data Consistency
================
As part of maintaining data consistency and cleanliness, Ceph OSDs can also
scrub objects within placement groups. That is Ceph OSDs can compare object
metadata in one placement group with its replicas in placement groups stored in
other OSDs. Scrubbing (usually performed daily) catches OSD bugs or filesystem
errors. OSDs can also perform deeper scrubbing by comparing data in objects
bit-for-bit. Deep scrubbing (usually performed weekly) finds bad sectors on a
disk that weren't apparent in a light scrub.
See `Data Scrubbing`_ for details on configuring scrubbing.
.. _Data Scrubbing: ../rados/configuration/osd-config-ref#scrubbing
Metadata Servers
================
The Ceph filesystem service is provided by a daemon called ``ceph-mds``. It uses
RADOS to store all the filesystem metadata (directories, file ownership, access
modes, etc), and directs clients to access RADOS directly for the file contents.
The Ceph filesystem aims for POSIX compatibility. ``ceph-mds`` can run as a
single process, or it can be distributed out to multiple physical machines,
either for high availability or for scalability.
- **High Availability**: The extra ``ceph-mds`` instances can be `standby`,
ready to take over the duties of any failed ``ceph-mds`` that was
`active`. This is easy because all the data, including the journal, is
stored on RADOS. The transition is triggered automatically by ``ceph-mon``.
- **Scalability**: Multiple ``ceph-mds`` instances can be `active`, and they
will split the directory tree into subtrees (and shards of a single
busy directory), effectively balancing the load amongst all `active`
servers.
Combinations of `standby` and `active` etc are possible, for example
running 3 `active` ``ceph-mds`` instances for scaling, and one `standby`
intance for high availability.
Client Interfaces
=================
Authentication and Authorization
--------------------------------
Ceph clients can authenticate their users with Ceph monitors, OSDs and metadata
servers. Authenticated users gain authorization to read, write and execute Ceph
commands. The Cephx authentication system is similar to Kerberos, but avoids a
single point of failure to ensure scalability and high availability. For
details on Cephx, see `Ceph Authentication and Authorization`_.
.. _Ceph Authentication and Authorization: ../rados/operations/auth-intro/
librados
--------
.. todo:: Snapshotting, Import/Export, Backup
.. todo:: native APIs
RBD
---
RBD stripes a block device image over multiple objects in the cluster, where
each object gets mapped to a placement group and distributed, and the placement
groups are spread across separate ``ceph-osd`` daemons throughout the cluster.
.. important:: Striping allows RBD block devices to perform better than a single server could!
RBD's thin-provisioned snapshottable block devices are an attractive option for
virtualization and cloud computing. In virtual machine scenarios, people
typically deploy RBD with the ``rbd`` network storage driver in Qemu/KVM, where
the host machine uses ``librbd`` to provide a block device service to the guest.
Many cloud computing stacks use ``libvirt`` to integrate with hypervisors. You
can use RBD thin-provisioned block devices with Qemu and libvirt to support
OpenStack and CloudStack among other solutions.
While we do not provide ``librbd`` support with other hypervisors at this time, you may
also use RBD kernel objects to provide a block device to a client. Other virtualization
technologies such as Xen can access the RBD kernel object(s). This is done with the
command-line tool ``rbd``.
RGW
---
The RADOS Gateway daemon, ``radosgw``, is a FastCGI service that provides a
RESTful_ HTTP API to store objects and metadata. It layers on top of RADOS with
its own data formats, and maintains its own user database, authentication, and
access control. The RADOS Gateway uses a unified namespace, which means you can
use either the OpenStack Swift-compatible API or the Amazon S3-compatible API.
For example, you can write data using the S3-comptable API with one application
and then read data using the Swift-compatible API with another application.
See `RADOS Gateway`_ for details.
.. _RADOS Gateway: ../radosgw/
.. _RESTful: http://en.wikipedia.org/wiki/RESTful
.. index:: RBD, Rados Block Device
CephFS
------
.. todo:: cephfs, ceph-fuse
Limitations of Prior Art
========================
Today's storage systems have demonstrated an ability to scale out, but with some
significant limitations: interfaces, session managers, and stateful sessions
with a centralized point of access often limit the scalability of today's
storage architectures. Furthermore, a centralized interface that dispatches
requests from clients to server nodes within a cluster and subsequently routes
responses from those server nodes back to clients will hit a scalability and/or
performance limitation.
Another problem for storage systems is the need to manually rebalance data when
increasing or decreasing the size of a data cluster. Manual rebalancing works
fine on small scales, but it is a nightmare at larger scales because hardware
additions are common and hardware failure becomes an expectation rather than an
exception when operating at the petabyte scale and beyond.
The operational challenges of managing legacy technologies with the burgeoning
growth in the demand for unstructured storage makes legacy technologies
inadequate for scaling into petabytes. Some legacy technologies (e.g., SAN) can
be considerably more expensive, and more challenging to maintain when compared
to using commodity hardware. Ceph uses commodity hardware, because it is
substantially less expensive to purchase (or to replace), and it only requires
standard system administration skills to use it.
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