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39 lines
3.3 KiB
Markdown
39 lines
3.3 KiB
Markdown
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## Context
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Data storage is critical: it can lead to data loss if done badly and/or on hardware failure.
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Filesystems + RAID can help on a single machine but a machine failure can put the whole storage offline.
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Moreover, it put a hard limit on scalability. Often this limit can be pushed back far away by buying expensive machines.
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But here we consider non specialized off the shelf machines that can be as low powered and subject to failures as a raspberry pi.
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Distributed storage may help to solve both availability and scalability problems on these machines.
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Many solutions were proposed, they can be categorized as block storage, file storage and object storage depending on the abstraction they provide.
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## Related work
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Block storage is the most low level one, it's like exposing your raw hard drive over the network.
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It requires very low latencies and stable network, that are often dedicated.
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However it provides disk devices that can be manipulated by the operating system with the less constraints: it can be partitioned with any filesystem, meaning that it supports even the most exotic features.
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We can cite [iSCSI](https://en.wikipedia.org/wiki/ISCSI) or [Fibre Channel](https://en.wikipedia.org/wiki/Fibre_Channel).
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Openstack Cinder proxy previous solution to provide an uniform API.
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File storage provides a higher abstraction, they are one filesystem among others, which means they don't necessarily have all the exotic features of every filesystem.
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Often, they relax some POSIX constraints while many applications will still be compatible without any modification.
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As an example, we are able to run MariaDB (very slowly) over GlusterFS...
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We can also mention CephFS (read [RADOS](https://ceph.com/wp-content/uploads/2016/08/weil-rados-pdsw07.pdf) whitepaper), Lustre, LizardFS, MooseFS, etc.
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OpenStack Manila proxy previous solutions to provide an uniform API.
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Finally object storages provide the highest level abstraction.
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They are the testimony that the POSIX filesystem API is not adapted to distributed filesystems.
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Especially, the strong concistency has been dropped in favor of eventual consistency which is way more convenient and powerful in presence of high latencies and unreliability.
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We often read about S3 that pioneered the concept that it's a filesystem for the WAN.
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Applications must be adapted to work for the desired object storage service.
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Today, the S3 HTTP REST API acts as a standard in the industry.
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However, Amazon S3 source code is not open but alternatives were proposed.
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We identified Minio, Pithos, Swift and Ceph.
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Minio/Ceph enforces a total order, so properties similar to a (relaxed) filesystem.
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Swift and Pithos are probably the most similar to AWS S3 with their consistent hashing ring.
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However Pithos is not maintained anymore. More precisely the company that published Pithos version 1 has developped a second version 2 but has not open sourced it.
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Some tests conducted by the [ACIDES project](https://acides.org/) have shown that Openstack Swift consumes way more resources (CPU+RAM) that we can afford. Furthermore, people developing Swift have not designed their software for geo-distribution.
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There were many attempts in research too. I am only thinking to [LBFS](https://pdos.csail.mit.edu/papers/lbfs:sosp01/lbfs.pdf) that was used as a basis for Seafile. But none of them have been effectively implemented yet.
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