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Added docs/specifications/backends/raic.rst for ticket #1760

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+
+=============================================================
+Redundant Array of Independent Clouds: Share To Cloud Mapping
+=============================================================
+
+
+Introduction
+============
+
+This document describes a proposed design for the mapping of LAFS shares to
+objects in a cloud storage service. It also analyzes the costs for each of the
+functional requirements, including network, disk, storage and API usage costs.
+
+
+Terminology
+===========
+
+*LAFS share*
+ A Tahoe-LAFS share representing part of a file after encryption and
+ erasure encoding.
+
+*LAFS shareset*
+ The set of shares stored by a LAFS storage server for a given storage index.
+ The shares within a shareset are numbered by a small integer.
+
+*Cloud storage service*
+ A service such as Amazon S3 `²`_, Rackspace Cloud Files `³`_,
+ Google Cloud Storage ``_, or Windows Azure ``_, that provides cloud storage.
+
+*Cloud storage interface*
+ A protocol interface supported by a cloud storage service, such as the
+ S3 interface ``_, the OpenStack Object Storage interface ``_, the
+ Google Cloud Storage interface ``_, or the Azure interface ``_. There may be
+ multiple services implementing a given cloud storage interface. In this design,
+ only REST-based APIs `¹⁰`_ over HTTP will be used as interfaces.
+
+*Cloud object*
+ A file-like abstraction provided by a cloud storage service, storing a
+ sequence of bytes. Cloud objects are mutable in the sense that the contents
+ and metadata of the cloud object with a given name in a given cloud container
+ can be replaced. Cloud objects are called “blobs” in the Azure interface,
+ and “objects” in the other interfaces.
+
+*Cloud container*
+ A container for cloud objects provided by a cloud service. Cloud containers
+ are called “buckets” in the S3 and Google Cloud Storage interfaces, and
+ “containers” in the Azure and OpenStack Storage interfaces.
+
+
+Functional Requirements
+=======================
+
+* *Upload*: a LAFS share can be uploaded to an appropriately configured
+ Tahoe-LAFS storage server and the data is stored to the cloud
+ storage service.
+
+ * *Scalable shares*: there is no hard limit on the size of LAFS share
+ that can be uploaded.
+
+ If the cloud storage interface offers scalable files, then this could be
+ implemented by using that feature of the specific cloud storage
+ interface. Alternately, it could be implemented by mapping from the LAFS
+ abstraction of an unlimited-size immutable share to a set of size-limited
+ cloud objects.
+
+ * *Streaming upload*: the size of the LAFS share that is uploaded
+ can exceed the amount of RAM and even the amount of direct attached
+ storage on the storage server. I.e., the storage server is required to
+ stream the data directly to the ultimate cloud storage service while
+ processing it, instead of to buffer the data until the client is finished
+ uploading and then transfer the data to the cloud storage service.
+
+* *Download*: a LAFS share can be downloaded from an appropriately
+ configured Tahoe-LAFS storage server, and the data is loaded from the
+ cloud storage service.
+
+ * *Streaming download*: the size of the LAFS share that is
+ downloaded can exceed the amount of RAM and even the amount of direct
+ attached storage on the storage server. I.e. the storage server is
+ required to stream the data directly to the client while processing it,
+ instead of to buffer the data until the cloud storage service is finished
+ serving and then transfer the data to the client.
+
+* *Modify*: a LAFS share can have part of its contents modified.
+
+ If the cloud storage interface offers scalable mutable files, then this
+ could be implemented by using that feature of the specific cloud storage
+ interface. Alternately, it could be implemented by mapping from the LAFS
+ abstraction of an unlimited-size mutable share to a set of size-limited
+ cloud objects.
+
+ * *Efficient modify*: the size of the LAFS share being
+ modified can exceed the amount of RAM and even the amount of direct
+ attached storage on the storage server. I.e. the storage server is
+ required to download, patch, and upload only the segment(s) of the share
+ that are being modified, instead of to download, patch, and upload the
+ entire share.
+
+* *Tracking leases*: The Tahoe-LAFS storage server is required to track when
+ each share has its lease renewed so that unused shares (shares whose lease
+ has not been renewed within a time limit, e.g. 30 days) can be garbage
+ collected. This does not necessarily require code specific to each cloud
+ storage interface, because the lease tracking can be performed in the
+ storage server's generic component rather than in the component supporting
+ each interface.
+
+
+Mapping
+=======
+
+This section describes the mapping between LAFS shares and cloud objects.
+
+A LAFS share will be split into one or more “chunks” that are each stored in a
+cloud object. A LAFS share of size `C` bytes will be stored as `ceiling(C / chunksize)`
+chunks. The last chunk has a size between 1 and `chunksize` bytes inclusive.
+(It is not possible for `C` to be zero, because valid shares always have a header,
+so, there is at least one chunk for each share.)
+
+For an existing share, the chunk size is determined by the size of the first
+chunk. For a new share, it is a parameter that may depend on the storage
+interface. It is an error for any chunk to be larger than the first chunk, or
+for any chunk other than the last to be smaller than the first chunk.
+If a mutable share with total size less than the default chunk size for the
+storage interface is being modified, the new contents are split using the
+default chunk size.
+
+ *Rationale*: this design allows the `chunksize` parameter to be changed for
+ new shares written via a particular storage interface, without breaking
+ compatibility with existing stored shares. All cloud storage interfaces
+ return the sizes of cloud objects with requests to list objects, and so
+ the size of the first chunk can be determined without an additional request.
+
+The name of the cloud object for chunk `i` > 0 of a LAFS share with storage index
+`STORAGEINDEX` and share number `SHNUM`, will be
+
+ shares/`ST`/`STORAGEINDEX`/`SHNUM.i`
+
+where `ST` is the first two characters of `STORAGEINDEX`. When `i` is 0, the
+`.0` is omitted.
+
+ *Rationale*: this layout maintains compatibility with data stored by the
+ prototype S3 backend, for which Least Authority Enterprises has existing
+ customers. This prototype always used a single cloud object to store each
+ share, with name
+
+ shares/`ST`/`STORAGEINDEX`/`SHNUM`
+
+ By using the same prefix “shares/`ST`/`STORAGEINDEX`/” for old and new layouts,
+ the storage server can obtain a list of cloud objects associated with a given
+ shareset without having to know the layout in advance, and without having to
+ make multiple API requests. This also simplifies sharing of test code between the
+ disk and cloud backends.
+
+Mutable and immutable shares will be “chunked” in the same way.
+
+
+Rationale for Chunking
+----------------------
+
+Limiting the amount of data received or sent in a single request has the
+following advantages:
+
+* It is unnecessary to write separate code to take advantage of the
+ “large object” features of each cloud storage interface, which differ
+ significantly in their design.
+* Data needed for each PUT request can be discarded after it completes.
+ If a PUT request fails, it can be retried while only holding the data
+ for that request in memory.
+
+
+Costs
+=====
+
+In this section we analyze the costs of the proposed design in terms of network,
+disk, memory, cloud storage, and API usage.
+
+
+Network usage—bandwidth and number-of-round-trips
+-------------------------------------------------
+
+When a Tahoe-LAFS storage client allocates a new share on a storage server,
+the backend will request a list of the existing cloud objects with the
+appropriate prefix. This takes one HTTP request in the common case, but may
+take more for the S3 interface, which has a limit of 1000 objects returned in
+a single “GET Bucket” request.
+
+If the share is to be read, the client will make a number of calls each
+specifying the offset and length of the required span of bytes. On the first
+request that overlaps a given chunk of the share, the server will make an
+HTTP GET request for that cloud object. The server may also speculatively
+make GET requests for cloud objects that are likely to be needed soon (which
+can be predicted since reads are normally sequential), in order to reduce
+latency.
+
+Each read will be satisfied as soon as the corresponding data is available,
+without waiting for the rest of the chunk, in order to minimize read latency.
+
+All four cloud storage interfaces support GET requests using the
+Range HTTP header. This could be used to optimize reads where the
+Tahoe-LAFS storage client requires only part of a share.
+
+If the share is to be written, the server will make an HTTP PUT request for
+each chunk that has been completed. Tahoe-LAFS clients only write immutable
+shares sequentially, and so we can rely on that property to simplify the
+implementation.
+
+When modifying shares of an existing mutable file, the storage server will
+be able to make PUT requests only for chunks that have changed.
+(Current Tahoe-LAFS v1.9 clients will not take advantage of this ability, but
+future versions will probably do so for MDMF files.)
+
+In some cases, it may be necessary to retry a request (see the `Structure of
+Implementation`_ section below). In the case of a PUT request, at the point
+at which a retry is needed, the new chunk contents to be stored will still be
+in memory and so this is not problematic.
+
+In the absence of retries, the maximum number of GET requests that will be made
+when downloading a file, or the maximum number of PUT requests when uploading
+or modifying a file, will be equal to the number of chunks in the file.
+
+If the new mutable share content has fewer chunks than the old content,
+then the remaining cloud objects for old chunks must be deleted (using one
+HTTP request each). When reading a share, the backend must tolerate the case
+where these cloud objects have not been deleted successfully.
+
+The last write to a share will be reported as successful only when all
+corresponding HTTP PUTs and DELETEs have completed successfully.
+
+
+
+Disk usage (local to the storage server)
+----------------------------------------
+
+It is never necessary for the storage server to write the content of share
+chunks to local disk, either when they are read or when they are written. Each
+chunk is held only in memory.
+
+A proposed change to the Tahoe-LAFS storage server implementation uses a sqlite
+database to store metadata about shares. In that case the same database would
+be used for the cloud backend. This would enable lease tracking to be implemented
+in the same way for disk and cloud backends.
+
+
+Memory usage
+------------
+
+The use of chunking simplifies bounding the memory usage of the storage server
+when handling files that may be larger than memory. However, this depends on
+limiting the number of chunks that are simultaneously held in memory.
+Multiple chunks can be held in memory either because of pipelining of requests
+for a single share, or because multiple shares are being read or written
+(possibly by multiple clients).
+
+For immutable shares, the Tahoe-LAFS storage protocol requires the client to
+specify in advance the maximum amount of data it will write. Also, a cooperative
+client (including all existing released versions of the Tahoe-LAFS code) will
+limit the amount of data that is pipelined, currently to 50 KiB. Since the chunk
+size will be greater than that, it is possible to ensure that for each allocation,
+the maximum chunk data memory usage is the lesser of two chunks, and the allocation
+size. (There is some additional overhead but it is small compared to the chunk
+data.) If the maximum memory usage of a new allocation would exceed the memory
+available, the allocation can be delayed or possibly denied, so that the total
+memory usage is bounded.
+
+It is not clear that the existing protocol allows allocations for mutable
+shares to be bounded in general; this may be addressed in a future protocol change.
+
+The above discussion assumes that clients do not maliciously send large
+messages as a denial-of-service attack. Foolscap (the protocol layer underlying
+the Tahoe-LAFS storage protocol) does not attempt to resist denial of service.
+
+
+Storage
+-------
+
+The storage requirements, including not-yet-collected garbage shares, are
+the same as for the Tahoe-LAFS disk backend. That is, the total size of cloud
+objects stored is equal to the total size of shares that the disk backend
+would store.
+
+Erasure coding causes the size of shares for each file to be a
+factor `shares.total` / `shares.needed` times the file size, plus overhead
+that is logarithmic in the file size `¹¹`_.
+
+
+API usage
+---------
+
+Cloud storage backends typically charge a small fee per API request. The number of
+requests to the cloud storage service for various operations is discussed under
+“network usage” above.
+
+
+Structure of Implementation
+===========================
+
+A generic “cloud backend”, based on the prototype S3 backend but with support
+for chunking as described above, will be written.
+
+An instance of the cloud backend can be attached to one of several
+“cloud interface adapters”, one for each cloud storage interface. These
+adapters will operate only on chunks, and need not distinguish between
+mutable and immutable shares. They will be a relatively “thin” abstraction
+layer over the HTTP APIs of each cloud storage interface, similar to the
+S3Bucket abstraction in the prototype.
+
+For some cloud storage services it may be necessary to transparently retry
+requests in order to recover from transient failures. (Although the erasure
+coding may enable a file to be retrieved even when shares are not stored by or
+not readable from all cloud storage services used in a Tahoe-LAFS grid, it may
+be desirable to retry cloud storage service requests in order to improve overall
+reliability.) Support for this will be implemented in the generic cloud backend,
+and used whenever a cloud storage adaptor reports a transient failure. Our
+experience with the prototype suggests that it is necessary to retry on transient
+failures for Amazon's S3 service.
+
+There will also be a “mock” cloud interface adaptor, based on the prototype's
+MockS3Bucket. This allows tests of the generic cloud backend to be run without
+a connection to a real cloud service. The mock adaptor will be able to simulate
+transient and non-transient failures.
+
+
+Known Issues
+============
+
+This design worsens a known “write hole” issue in Tahoe-LAFS when updating
+the contents of mutable files. An update to a mutable file can require changing
+the contents of multiple chunks, and if the client fails or is disconnected
+during the operation the resulting state of the stored cloud objects may be
+inconsistent—no longer containing all of the old version, but not yet containing
+all of the new version. A mutable share can be left in an inconsistent state
+even by the existing Tahoe-LAFS disk backend if it fails during a write, but
+that has a smaller chance of occurrence because the current client behavior
+leads to mutable shares being written to disk in a single system call.
+
+The best fix for this issue probably requires changing the Tahoe-LAFS storage
+protocol, perhaps by extending it to use a two-phase or three-phase commit
+(ticket #1755).
+
+
+
+References
+===========
+
+¹ omitted
+
+.. _²:
+
+² “Amazon S3” Amazon (2012)
+
+ https://aws.amazon.com/s3/
+
+.. _³:
+
+³ “Rackspace Cloud Files” Rackspace (2012)
+
+ https://www.rackspace.com/cloud/cloud_hosting_products/files/
+
+.. _⁴:
+
+⁴ “Google Cloud Storage” Google (2012)
+
+ https://developers.google.com/storage/
+
+.. _⁵:
+
+⁵ “Windows Azure Storage” Microsoft (2012)
+
+ https://www.windowsazure.com/en-us/develop/net/fundamentals/cloud-storage/
+
+.. _⁶:
+
+⁶ “Amazon Simple Storage Service (Amazon S3) API Reference: REST API” Amazon (2012)
+
+ http://docs.amazonwebservices.com/AmazonS3/latest/API/APIRest.html
+
+.. _⁷:
+
+⁷ “OpenStack Object Storage” openstack.org (2012)
+
+ http://openstack.org/projects/storage/
+
+.. _⁸:
+
+⁸ “Google Cloud Storage Reference Guide” Google (2012)
+
+ https://developers.google.com/storage/docs/reference-guide
+
+.. _⁹:
+
+⁹ “Windows Azure Storage Services REST API Reference” Microsoft (2012)
+
+ http://msdn.microsoft.com/en-us/library/windowsazure/dd179355.aspx
+
+.. _¹⁰:
+
+¹⁰ “Representational state transfer” English Wikipedia (2012)
+
+ https://en.wikipedia.org/wiki/Representational_state_transfer
+
+.. _¹¹:
+
+¹¹ “Performance costs for some common operations” tahoe-lafs.org (2012)
+
+ https://tahoe-lafs.org/trac/tahoe-lafs/browser/trunk/docs/performance.rst
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