Convert Object Storage files to RST

-Object Storage Intro to RST.
-Object Storage Features table to RST.
-Object Storage Components to RST.
-Added related figures.

Change-Id: I835a4387d64afa38705fbf8e67ff89f1d7f45a3f
Implements: blueprint reorganise-user-guides
This commit is contained in:
Karen Bradshaw 2015-06-10 19:54:01 -04:00
parent 0a098c3117
commit ae71474177
11 changed files with 380 additions and 3 deletions

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@ -8,13 +8,12 @@ Contents
.. toctree::
:maxdepth: 2
objectstorage_characteristics.rst
.. TODO (karenb)
objectstorage_intro.rst
objectstorage_features.rst
objectstorage_characteristics.rst
objectstorage_components.rst
.. TODO (karenb)
objectstorage_ringbuilder.rst
objectstorage_arch.rst
objectstorage_replication.rst

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==========
Components
==========
The components that enable Object Storage to deliver high availability,
high durability, and high concurrency are:
- **Proxy servers.** Handle all of the incoming API requests.
- **Rings.** Map logical names of data to locations on particular
disks.
- **Zones.** Isolate data from other zones. A failure in one zone
doesn't impact the rest of the cluster because data is replicated
across zones.
- **Accounts and containers.** Each account and container are
individual databases that are distributed across the cluster. An
account database contains the list of containers in that account. A
container database contains the list of objects in that container.
- **Objects.** The data itself.
- **Partitions.** A partition stores objects, account databases, and
container databases and helps manage locations where data lives in
the cluster.
|
.. _objectstorage-building-blocks-figure:
**Object Storage building blocks**
.. figure:: figures/objectstorage-buildingblocks.png
|
Proxy servers
-------------
Proxy servers are the public face of Object Storage and handle all of
the incoming API requests. Once a proxy server receives a request, it
determines the storage node based on the object's URL, for example,
https://swift.example.com/v1/account/container/object. Proxy servers
also coordinate responses, handle failures, and coordinate timestamps.
Proxy servers use a shared-nothing architecture and can be scaled as
needed based on projected workloads. A minimum of two proxy servers
should be deployed for redundancy. If one proxy server fails, the others
take over.
For more information concerning proxy server configuration, please see
the `Configuration
Reference <http://docs.openstack.org/trunk/config-reference/content/proxy-server-configuration.html>`__.
Rings
-----
A ring represents a mapping between the names of entities stored on disk
and their physical locations. There are separate rings for accounts,
containers, and objects. When other components need to perform any
operation on an object, container, or account, they need to interact
with the appropriate ring to determine their location in the cluster.
The ring maintains this mapping using zones, devices, partitions, and
replicas. Each partition in the ring is replicated, by default, three
times across the cluster, and partition locations are stored in the
mapping maintained by the ring. The ring is also responsible for
determining which devices are used for handoff in failure scenarios.
Data can be isolated into zones in the ring. Each partition replica is
guaranteed to reside in a different zone. A zone could represent a
drive, a server, a cabinet, a switch, or even a data center.
The partitions of the ring are equally divided among all of the devices
in the Object Storage installation. When partitions need to be moved
around (for example, if a device is added to the cluster), the ring
ensures that a minimum number of partitions are moved at a time, and
only one replica of a partition is moved at a time.
You can use weights to balance the distribution of partitions on drives
across the cluster. This can be useful, for example, when differently
sized drives are used in a cluster.
The ring is used by the proxy server and several background processes
(like replication).
|
.. _objectstorage-ring-figure:
**The ring**
.. figure:: figures/objectstorage-ring.png
|
These rings are externally managed, in that the server processes
themselves do not modify the rings, they are instead given new rings
modified by other tools.
The ring uses a configurable number of bits from an MD5 hash for a path
as a partition index that designates a device. The number of bits kept
from the hash is known as the partition power, and 2 to the partition
power indicates the partition count. Partitioning the full MD5 hash ring
allows other parts of the cluster to work in batches of items at once
which ends up either more efficient or at least less complex than
working with each item separately or the entire cluster all at once.
Another configurable value is the replica count, which indicates how
many of the partition-device assignments make up a single ring. For a
given partition number, each replica's device will not be in the same
zone as any other replica's device. Zones can be used to group devices
based on physical locations, power separations, network separations, or
any other attribute that would improve the availability of multiple
replicas at the same time.
Zones
-----
Object Storage allows configuring zones in order to isolate failure
boundaries. Each data replica resides in a separate zone, if possible.
At the smallest level, a zone could be a single drive or a grouping of a
few drives. If there were five object storage servers, then each server
would represent its own zone. Larger deployments would have an entire
rack (or multiple racks) of object servers, each representing a zone.
The goal of zones is to allow the cluster to tolerate significant
outages of storage servers without losing all replicas of the data.
As mentioned earlier, everything in Object Storage is stored, by
default, three times. Swift will place each replica
"as-uniquely-as-possible" to ensure both high availability and high
durability. This means that when chosing a replica location, Object
Storage chooses a server in an unused zone before an unused server in a
zone that already has a replica of the data.
|
.. _objectstorage-zones-figure:
**Zones**
.. figure:: figures/objectstorage-zones.png
|
When a disk fails, replica data is automatically distributed to the
other zones to ensure there are three copies of the data.
Accounts and containers
-----------------------
Each account and container is an individual SQLite database that is
distributed across the cluster. An account database contains the list of
containers in that account. A container database contains the list of
objects in that container.
|
.. _objectstorage-accountscontainers-figure:
**Accounts and containers**
.. figure:: figures/objectstorage-accountscontainers.png
|
To keep track of object data locations, each account in the system has a
database that references all of its containers, and each container
database references each object.
Partitions
----------
A partition is a collection of stored data, including account databases,
container databases, and objects. Partitions are core to the replication
system.
Think of a partition as a bin moving throughout a fulfillment center
warehouse. Individual orders get thrown into the bin. The system treats
that bin as a cohesive entity as it moves throughout the system. A bin
is easier to deal with than many little things. It makes for fewer
moving parts throughout the system.
System replicators and object uploads/downloads operate on partitions.
As the system scales up, its behavior continues to be predictable
because the number of partitions is a fixed number.
Implementing a partition is conceptually simple, a partition is just a
directory sitting on a disk with a corresponding hash table of what it
contains.
|
.. _objectstorage-partitions-figure:
**Partitions**
.. figure:: figures/objectstorage-partitions.png
|
Replicators
-----------
In order to ensure that there are three copies of the data everywhere,
replicators continuously examine each partition. For each local
partition, the replicator compares it against the replicated copies in
the other zones to see if there are any differences.
The replicator knows if replication needs to take place by examining
hashes. A hash file is created for each partition, which contains hashes
of each directory in the partition. Each of the three hash files is
compared. For a given partition, the hash files for each of the
partition's copies are compared. If the hashes are different, then it is
time to replicate, and the directory that needs to be replicated is
copied over.
This is where partitions come in handy. With fewer things in the system,
larger chunks of data are transferred around (rather than lots of little
TCP connections, which is inefficient) and there is a consistent number
of hashes to compare.
The cluster eventually has a consistent behavior where the newest data
has a priority.
|
.. _objectstorage-replication-figure:
**Replication**
.. figure:: figures/objectstorage-replication.png
|
If a zone goes down, one of the nodes containing a replica notices and
proactively copies data to a handoff location.
Use cases
---------
The following sections show use cases for object uploads and downloads
and introduce the components.
Upload
~~~~~~
A client uses the REST API to make a HTTP request to PUT an object into
an existing container. The cluster receives the request. First, the
system must figure out where the data is going to go. To do this, the
account name, container name, and object name are all used to determine
the partition where this object should live.
Then a lookup in the ring figures out which storage nodes contain the
partitions in question.
The data is then sent to each storage node where it is placed in the
appropriate partition. At least two of the three writes must be
successful before the client is notified that the upload was successful.
Next, the container database is updated asynchronously to reflect that
there is a new object in it.
|
.. _objectstorage-usecase-figure:
**Object Storage in use**
.. figure:: figures/objectstorage-usecase.png
|
Download
~~~~~~~~
A request comes in for an account/container/object. Using the same
consistent hashing, the partition name is generated. A lookup in the
ring reveals which storage nodes contain that partition. A request is
made to one of the storage nodes to fetch the object and, if that fails,
requests are made to the other nodes.

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=====================
Features and benefits
=====================
+-----------------------------+--------------------------------------------------+
| Features | Benefits |
+=============================+==================================================+
| Leverages commodity | No lock-in, lower price/GB. |
| hardware | |
+-----------------------------+--------------------------------------------------+
| HDD/node failure agnostic | Self-healing, reliable, data redundancy protects |
| | from failures. |
+-----------------------------+--------------------------------------------------+
| Unlimited storage | Large and flat namespace, highly scalable |
| | read/write access, able to serve content |
| | directly from storage system. |
+-----------------------------+--------------------------------------------------+
| Multi-dimensional | Scale-out architecture: Scale vertically and |
| scalability | horizontally-distributed storage. Backs up |
| | and archives large amounts of data with |
| | linear performance. |
+-----------------------------+--------------------------------------------------+
| Account/container/object | No nesting, not a traditional file system: |
| structure | Optimized for scale, it scales to multiple |
| | petabytes and billions of objects. |
+-----------------------------+--------------------------------------------------+
| Built-in replication | A configurable number of accounts, containers |
| 3✕ + data redundancy | and object copies for high availability. |
| (compared with 2✕ on RAID) | |
+-----------------------------+--------------------------------------------------+
| Easily add capacity (unlike | Elastic data scaling with ease |
| RAID resize) | |
+-----------------------------+--------------------------------------------------+
| No central database | Higher performance, no bottlenecks |
+-----------------------------+--------------------------------------------------+
| RAID not required | Handle many small, random reads and writes |
| | efficiently |
+-----------------------------+--------------------------------------------------+
| Built-in management | Account management: Create, add, verify, |
| utilities | and delete users; Container management: Upload, |
| | download, and verify; Monitoring: Capacity, |
| | host, network, log trawling, and cluster health. |
+-----------------------------+--------------------------------------------------+
| Drive auditing | Detect drive failures preempting data corruption |
+-----------------------------+--------------------------------------------------+
| Expiring objects | Users can set an expiration time or a TTL on an |
| | object to control access |
+-----------------------------+--------------------------------------------------+
| Direct object access | Enable direct browser access to content, such as |
| | for a control panel |
+-----------------------------+--------------------------------------------------+
| Realtime visibility into | Know what users are requesting. |
| client requests | |
+-----------------------------+--------------------------------------------------+
| Supports S3 API | Utilize tools that were designed for the popular |
| | S3 API. |
+-----------------------------+--------------------------------------------------+
| Restrict containers per | Limit access to control usage by user. |
| account | |
+-----------------------------+--------------------------------------------------+
| Support for NetApp, | Unified support for block volumes using a |
| Nexenta, SolidFire | variety of storage systems. |
+-----------------------------+--------------------------------------------------+
| Snapshot and backup API for | Data protection and recovery for VM data. |
| block volumes | |
+-----------------------------+--------------------------------------------------+
| Standalone volume API | Separate endpoint and API for integration with |
| available | other compute systems. |
+-----------------------------+--------------------------------------------------+
| Integration with Compute | Fully integrated with Compute for attaching |
| | block volumes and reporting on usage. |
+-----------------------------+--------------------------------------------------+

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==============================
Introduction to Object Storage
==============================
OpenStack Object Storage (code-named swift) is open source software for
creating redundant, scalable data storage using clusters of standardized
servers to store petabytes of accessible data. It is a long-term storage
system for large amounts of static data that can be retrieved,
leveraged, and updated. Object Storage uses a distributed architecture
with no central point of control, providing greater scalability,
redundancy, and permanence. Objects are written to multiple hardware
devices, with the OpenStack software responsible for ensuring data
replication and integrity across the cluster. Storage clusters scale
horizontally by adding new nodes. Should a node fail, OpenStack works to
replicate its content from other active nodes. Because OpenStack uses
software logic to ensure data replication and distribution across
different devices, inexpensive commodity hard drives and servers can be
used in lieu of more expensive equipment.
Object Storage is ideal for cost effective, scale-out storage. It
provides a fully distributed, API-accessible storage platform that can
be integrated directly into applications or used for backup, archiving,
and data retention.