Tag: Cloud storage tiering

There’s a new cluster filesystem on the block, Elastifile

Posted on by Ray in Cloud storage, Clustered storage, Distributed computing, Ethernet, File Storage, NVMe, NVMe storage, SSD storage

At SFD12 last month we talked with the team from Elastifile. They are a new startup out of Israel working on a better cluster file system.

Elastifile was designed to support 1000s of nodes, 100,000 of users/client and 1000s of data containers (file systems/mount points), together with an infinite (64 bit) number of files and directories and up to Exabytes (10**18) in capacity. They also offer a 100% SSD file store capability. I encourage you to view the videos of their presentations at SFD12 to learn more.

Elastifile features

Elastifile supports data compression and optionally deduplication with NAND/Flash (e. g., low-/high-endurance) storage tiering, cloud storage tiering and multi-site storage. They also provide NFSv3/v4, SMB, AWS S3 and HDFS as native access protocols for their file storage.

They also offer non-disruptive hardware/software upgrades, n-way (2- or 3-way) data and metadata redundancy, self-healing capabilities, snapshots, and synchronous/asynchronous data replication or mirroring. Further, they provide multi-tenancy and QoS support.

Elastifile can be used in hyper converged mode as well as a dedicated storage server mode. For backend storage, they support heterogeneous, physical (block, I think?) storage systems as well as direct access storage in cluster nodes

Internals matter

Elastifile’s architecture supports accessor, owner and data nodes. But these can all be colocated on the same server or segregated across different servers.

Owner nodes, own all the metadata objects for a file or directory and caches the metadata working set in i’s memory. Ownership file or directory metadata may change in the case of hardware failures.

Elastifile supports a dynamic write data path, which means they determine, in real time, where to write file data rather than having the data locations identified before hand. They call this distributed write anywhere semantics.

Notably they don’t do data caching (with NVMe it doesn’t make sense) however, as noted above, they do use metadata caching

Internally, Elastifile uses variable length objects for both file data and metadata.

  • File data is composed of three object types: a file metadata (FileMD) object, mapping data objects, and file data objects. FileMD’s hold the normal file metadata (name, file size, create, access & modify ToDs, etc.) as well as pointing to all the Mapping Object (OIDs). Mapping objects exist for each 0.5MB of file data and consist of a 128 element table, each element mapping 4KB of file address space to a data object (OID). Each  data object holds the 4KB of compressed file data and journal log entries.
  • Director metadata is composed of directory metadata (DirMD) object and Directory listing objects. Directory listing objects maps file/directory names to FileMD or DirMD OIDs. Directory listing objects are accessed via an extensible hash table and contain a list of filenames/directory names within the directory

The Elastifile software architecture consists of three layers:

  • A protocol layer which terminates file system access protocols and translates requests into internal requests. The hashing and data compression of file data occur at this level.
  • A metadata layer which provides file system/directory name mapping to objects for owned files/directories and maintains file/directory metadata updates/journals/checkpoints.
  • A data layer which provides transaction consistency and a n-way redundant persistent data storage for (file or metadata) objects.

Metadata operations are persisted via journaled transactions and which are distributed across the cluster. For instance the journal entries for a mapping data object updates are written to the same file data object (OID) as the actual file data, the 4KB compressed data object.

There’s plenty of discussion on how they manage consistency for their metadata across cluster nodes. Elastifile invented and use Bizur, a key-value consensus based DB. Their chief architect Ezra Hoch (@EzraHoch) did a blog post and paper on Bizur for more information

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New file systems generally take many years to mature and get out into the market, cluster file systems even longer. Elastifile started in 2013, by some very smart engineers, is already on the market, just 4 years later. That’s impressive enough, but with their list of advanced functionality plus cloud storage tiering and multi-site operations all shipping in the current product is mind-blowing.

One lingering question is, does a market exist for another cluster file system? All flash is interesting but most of the current CFS’s do this and ship this today. Cloud storage tiering is interesting and a long term need but some CFSs already have this and others are no doubt implementing it as we speak. CFS’s use of objects for internal data and metadata management is not new and may make internals cleaner but don’t really provide a lot of customer benefit.

Exascale raw capacity, support for 100K users, 1000s of nodes, 1000s of file systems and an infinite # of files/directories is interesting. But most CFSs claim this level of support already, although this is more aspirational for some. And proving support at this scale is difficult, if not impossible.

On the other hand, Bizur is really neat. Its primary benefit is during recovery from hardware failures. For a CFS with 1000s of nodes, failures likely occur quite often. So Bizur’s advantage here may pay significant customer dividends.

Is that enough to to market a new CFS?

To see what other SFD12 bloggers have written on Elastifile, please see: