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

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:

QoM1610: Will NVMe over Fabric GA in enterprise AFA by Oct’2017

NVMeNVMe over fabric (NVMeoF) was a hot topic at Flash Memory Summit last August. Facebook and others were showing off their JBOF (see my Facebook moving to JBOF post) but there were plenty of other NVMeoF offerings at the show.

NVMeoF hardware availability

When Brocade announced their Gen6 Switches they made a point of saying that both their Gen5 and Gen6 switches currently support NVMeoF protocols. In addition to Brocade’s support, in Dec 2015 Qlogic announced support for NVMeoF for select HBAs. Also, as of  July 2016, Emulex announced support for NVMeoF in their HBAs.

From an Ethernet perspective, Qlogic has a NVMe Direct NIC which supports NVMe protocol offload for iSCSI. But even without NVMe Direct, Ethernet 40GbE & 100GbE with  iWARP, RoCEv1-v2, iSCSI SER, or iSCSI RDMA all could readily support NVMeoF on Ethernet. The nice thing about NVMeoF for Ethernet is not only do you get support for iSCSI & FCoE, but CIFS/SMB and NFS as well.

InfiniBand and Omni-Path Architecture already support native RDMA, so they should already support NVMeoF.

So hardware/firmware is already available for any enterprise AFA customer to want NVMeoF for their data center storage.

NVMeoF Software

Intel claims that ~90% of the software driver functionality of NVMe is the same for NVMeoF. The primary differences between the two seem to be the NVMeoY discovery and queueing mechanisms.

There are two fabric methods that can be used to implement NVMeoF data and command transfers: capsule mode where NVMe commands and data are encapsulated in normal fabric packets or fabric dependent mode where drivers make use of native fabric memory transfer mechanisms (RDMA, …) to transfer commands and data.

12679485_245179519150700_14553389_nA (Linux) host driver for NVMeoF is currently available from Seagate. And as a result, support for NVMeoF for Linux is currently under development, and  not far from release in the next Kernel (I think). (Mellanox has a tutorial on how to compile a Linux kernel with NVMeoF driver support).

With Linux coming out, Microsoft Windows and VMware can’t be far behind. However, I could find nothing online, aside from base NVMe support, for either platform.

NVMeoF target support is another matter but with NICs/HBAs & switch hardware/firmware and drivers presently available, proprietary storage system target drivers are just a matter of time.

Boot support is a major concern. I could find no information on BIOS support for booting off of a NVMeoF AFA. Arguably, one may not need boot support for NVMeoF AFAs as they are probably not a viable target for storing App code or OS software.

From what I could tell, normal fabric multi-pathing support should work fine with NVMeoF. This should allow for HA NVMeoF storage, a critical requirement for enterprise AFA storage systems these days.

NVMeoF advantages/disadvantages

Chelsio and others have shown that NVMeoF adds ~8μsec of additional overhead beyond native NVMe SSDs, which if true would warrant implementation on all NVMe AFAs. This may or may not impact max IOPS depending on scale-ability of NVMeoF.

For instance, servers (PCIe bus hardware) typically limit the number of private NVMe SSDs to 255 or less. With an NVMeoF, one could potentially have 1000s of shared NVMe SSDs accessible to a single server. With this scale, one could have a single server attached to a scale-out NVMeoF AFA (cluster) that could supply ~4X the IOPS that a single server could perform using private NVMe storage.

Base level NVMe SSD support and protocol stacks are starting to be available for most flash vendors and operating systems such as, Linux, FreeBSD, VMware, Windows, and Solaris. If Intel’s claim of 90% common software between NVMe and NVMeoF drivers is true, then it should be a relatively easy development project to provide host NVMeoF drivers.

The need for special Ethernet hardware that supports RDMA may delay some storage vendors from implementing NVMeoF AFAs quickly. The lack of BIOS boot support may be a minor irritant in comparison.

NVMeoF forecast

AFA storage systems, as far as I can tell, are all about selling high IOPS and very-low latency IOs. It would seem that NVMeoF would offer early adopter AFA storage vendors a significant performance advantage over slower paced competition.

In previous QoM/QoW posts we have established that there are about 13 new enterprise storage systems that come out each year. Probably 80% of these will be AFA, given the current market environment.

Of the 10.4 AFA systems coming out over the next year, ~20% of these systems pride themselves on being the lowest latency solutions in the market, and thus command high margins. One would think these systems would be the first to adopt NVMeoF. But, most of these systems have their own, proprietary flash modules and do not use standard (NVMe) SSDs and can use their own proprietary interface to their proprietary flash storage. This will delay any implementation for them until they can convert their flash storage to NVMe which may take some time.

On the other hand, most (70%) of the other AFA systems, that currently use SAS/SATA SSDs, could boost their IOP counts and drastically reduce their IO  response times, by implementing NVMe SSDs and NVMeoF. But converting SAS/SATA backends to NVMe will take time and effort.

But, there are a select few (~10%) of AFA systems, that already use NVMe SSDs in their AFAs, and for these few, they would seem to have a fast track towards implementing NVMeoF. The fact that NVMeoF is supported over all fabrics and all storage interface protocols make it even easier.

Moreover, NVMeoF has been under discussion since the summer of 2015, which tells me that astute AFA vendors have already had 18+ months to develop it. With NVMeoF host drivers & hardware available since Dec. 2015, means hardware and software exist to test and validate against.

I believe that NVMeoF will be GA’d within the next 12 months by at least one enterprise AFA system. So my QoM1610 forecast for NVMeoF is YES, with a 0.83 probability.

Comments?

 

 

 

Exablox, bring your own disk storage

We talked with Exablox a month or so ago at Storage Field Day 10 (SFD10) and they discussed some of their unique storage solution and new software functionality. If you’re not familiar with Exablox they sell a OneBlox appliance with drive slots, but no data drives.

The OneBlox appliance provides a Linux based, scale-out, distributed object storage software with a file system in front of it. They support SMB and NFS access protocols and have inline deduplication, data compression and continuous snapshot capabilities. You supply the (SATA or SAS) drives, a bring your own drive (BYOD) storage offering.

Their OneSystem management solution is available on a subscription basis, which usually runs in the cloud as a web accessed service offering used to monitor and manage your Exablox cluster(s). However, for those customers that want it, OneSystem is also available as a Docker Container, where you can run it on any Docker compatible system.
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Pure Storage FlashBlade well positioned for next generation storage

IMG_6344Sometimes, long after I listen to a vendor’s discussion, I come away wondering why they do what they do. Oftentimes, it passes but after a recent session with Pure Storage at SFD10, it lingered.

Why engineer storage hardware?

In the last week or so, executives at Hitachi mentioned that they plan to reduce  hardware R&D activities for their high end storage. There was much confusion what it all meant but from what I hear, they are ahead now, and maybe it makes more sense to do less hardware and more software for their next generation high end storage. We have talked about hardware vs. software innovation a lot (see recent post: TPU and hardware vs. software innovation [round 3]).
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A tale of two AFAs: EMC DSSD D5 & Pure Storage FlashBlade

There’s been an ongoing debate in the analyst community about the advantages of software only innovation vs. hardware-software innovation (see Commodity hardware loses again and Commodity hardware always loses posts). Here is another example where two separate companies have turned to hardware innovation to take storage innovation to the next level.

DSSD D5 and FlashBlade

DSSD-d5Within the last couple of weeks, two radically different AFAs were introduced. One by perennial heavyweight EMC with their new DSSD D5 rack scale flash system and the other by relatively new comer Pure Storage with their new FlashBlade storage system.FB

These two arrays seem to be going after opposite ends of the storage market: the 5U DSSD D5 is going after both structured and unstructured data that needs ultra high speed IO access (<100µsec) times and the 4U FlashBlade going after more general purpose unstructured data. And yet the two have have many similarities at least superficially.
Continue reading “A tale of two AFAs: EMC DSSD D5 & Pure Storage FlashBlade”

(QoM16-002): Will Intel Omni-Path GA in scale out enterprise storage by February 2016 – NO 0.91 probability

opa-cardQuestion of the month (QoM for February is: Will Intel Omni-Path (Architecture, OPA) GA in scale out enterprise storage by February 2016?

In this forecast enterprise storage are the major and startup vendors supplying storage to data center customers.

What is OPA?

OPA is Intel’s replacement for InfiniBand and starts out at 100Gbps. It’s intended more for high performance computing (HPC), to be used as an inter-cluster server interconnect or next generation fabric. Intel says it “will maintain consistency and compatibility with existing Intel True Scale Fabric and InfiniBand APIs by working through the open source OpenFabrics Alliance (OFA) software stack on leading Linux* distribution releases”. Seems like Intel is making it as easy as possible for vendors to adopt the technology.
Continue reading “(QoM16-002): Will Intel Omni-Path GA in scale out enterprise storage by February 2016 – NO 0.91 probability”

Coho Data, the packet processing squeeze and working set exploits

Was at Coho Data this week with Storage Field Day 8 (SFD8) (see the videos here)  and we met with Andy Warfield (@andywarfield), CTO and Co-founder Coho Data. Last time we met (at SFD6) Andy talked at length about some enhancements they were working on and gave us a tutorial on HyperLogLog (HLL) data structures that can be used to identify application working sets.

Packet processing time is getting squeezed

 

IMG_5551

Andy’s always a joy to talk with and this time was no exception. Andy started out talking about the speed of networking and what it meant for network packet processing time. He showed a chart with network speeds on the horizontal axis and packet processing time (in nsec) on the vertical access. It was a log-log chart but it showed an exponential decay such that at 10GbE a system had 67.2nsec to process a packet, at 40GbE, it had 16.8nsec to process a packet and at 100GbE the system had 6.7nsec to process a single packet. He was leading up to explaining why “storage datapaths are like network datapaths in hell”.

Similar performance dynamics are impacting storage device processing. In this case, NVMe PCIe flash devices are becoming processing bound.

Andy showed a chart for 4K random reads, plotting the number of cores on the bottom against K-IOPS on the vertical axis. At about 4 cores with one P3700 Intel PCIe NVMe card, the IOP performance of the storage system (as measured for IMG_5552 (1)NIC throughput) flattened out, from that point on, even after doubling the number of cores. It turns out with just one Intel P3700 NVMe PCIe flash card and 4 core Xeon processors one can quickly max out IOs across a 40GbE network, even though there’s plenty of networking bandwidth still available. Of course, this situation becomes much worse  with the new XPoint NVM which is 1000X faster than NAND, coming out next year from Micron-Intel (subject for a future post as Intel was another SFD8 presenter).

Andy also made the point that as a component of a system increases in cost, software usually tries to improve its utilization. This dynamic is now occurring for PCIe flash cards, which generally make up about 50% of the cost of a storage controller complex.

Location, location, location, …

Net Net, (network forwarding decision) storage data transfer time is shrinking as data placement times are becoming longer. By that I think he means that determining where to place data in the storage hierarchy is becoming more complex, taking more processing cycles just when we have less time to make those decisions.

So the crux of the question is how do we make those decisions better. Coho Data has attacked this problem by implementing HLLs to better identify application working sets.

IMG_5557Last year (See prior post for more info on HLLs) Coho Data had just started working with HLL technology and hadn’t fully implemented their working set analytics. But this year, Andy displayed an On-Stream reporting service treemap chart (where rectangle size indicates relative size of a parameter) that indicated an application’s cache working set size.

Using working set history to improve IO

By using a time series of properly implemented HLLs together with snapshots of working set block information, Coho Data can tell how the working set changes over time for an application or VM. Andy showed an example of application working set size changes over the course of multiple days and each day in the evening there was a giant spike in working set size. This turned out to be backup scans.

So Coho Data could then go back and snapshot the working set information before and after the spike to see if it was different. Once it was determined to be different, they then could go further and re-apply the working set cache data prior to the spike (not sure if this is implemented just yet) after the backup scan to re-warm the workload data cache. Of course, this meant that the system would have  read all this data back into cache. But doing so would leave the application’s data location optimized for upcoming IO activity.

This was just one example of what Coho Data could do to make a better data placement decision and improve the applications IO performance. Neat stuff, if you ask me.

Can’t wait until next year to see what Coho Data is working on next.

Comments?

Transporter, a private Dropbox in a tower

Move over DropboxBox and all you synch&share wannabees, there’s a new synch and share in town.

At SFD7 last month, we were visiting with Connected Data where CEO, Geoff Barrell was telling us all about what was wrong with today’s cloud storage solutions. In front of all the participants was this strange, blue glowing device. As it turns out, Connected Data’s main product is the File Transporter, which is a private file synch and share solution.

All the participants were given a new, 1TB Transporter system to take home. It was an interesting sight to see a dozen of these Transporter towers sitting in front of all the bloggers.

I was quickly, established a new account, installed the software, and activated the client service. I must admit, I took it upon myself to “claim” just about all of the Transporter towers as the other bloggers were still paying attention to the presentation.  Sigh, they later made me give back (unclaim) all but mine, but for a minute there I had about 10TB of synch and share space at my disposal.

Transporters rule

transporterB2So what is it. The Transporter is both a device and an Internet service, where you own the storage and networking hardware.

The home-office version comes as a 1 or 2TB 2.5” hard drive, in a tower configuration that plugs into a base module. The base module runs a secured version of Linux and their synch and share control software.

As tower power on, it connects to the Internet and invokes the Transporter control service. This service identifies the node, who owns it, and provides access to the storage on the Transporter to all desktops, laptops, and mobile applications that have access to it.

At initiation of the client service on a desktop/laptop it creates (by default) a new Transporter directory (folder). Files that are placed in this directory are automatically synched to the Transporter tower and then synchronized to any and all online client devices that have claimed the tower.

Apparently you can have multiple towers that are claimed to the same account. I personally tested up to 10 ;/ and it didn’t appear as if there was any substantive limit beyond that but I’m sure there’s some maximum count somewhere.

A couple of nice things about the tower. It’s your’s so you can move it to any location you want. That means, you could take it with you to your hotel or other remote offices and have a local synch point.

Also, initial synchronization can take place over your local network so it can occur as fast as your LAN can handle it. I remember the first time I up-synched 40GB to DropBox, it seemed to take weeks to complete and then took less time to down-synch for my laptop but still days of time. With the tower on my local network, I can synch my data much faster and then take the tower with me to my other office location and have a local synch datastore. (I may have to start taking mine to conferences. Howard (@deepstorage.net, co-host on our  GreyBeards on Storage podcast) had his operating in all the subsequent SFD7 sessions.

The Transporter also allows sharing of data. Steve immediately started sharing all the presentations on his Transporter service so the bloggers could access the data in real time.

They call the Transporter a private cloud but in my view, it’s more a private synch and share service.

Transporter heritage

The Transporter people were all familiar to the SFD crowd as they were formerly with  Drobo which was at a previous SFD sessions (see SFD1). And like Drobo, you can install any 2.5″ disk drive in your Transporter and it will work.

There’s workgroup and business class versions of the Transporter storage system. The workgroup versions are desktop configurations (looks very much like a Drobo box) that support up to 8TB or 12TB supporting 15 or 30 users respectively.  The also have two business class, rack mounted appliances that have up to 12TB or 24TB each and support 75 or 150 users each. The business class solution has onboard SSDs for meta-data acceleration. Similar to the Transporter tower, the workgroup and business class appliances are bring your own disk drives.

Connected Data’s presentation

transporterA1Geoff’s discussion (see SFD7 video) was a tour of the cloud storage business model. His view was that most of these companies are losing money. In fact, even Amazon S3/Glacier appears to be bleeding money, although this may not stop Amazon. Of course, DropBox and other synch and share services all depend on cloud storage for their datastores. So, the lack of a viable, profitable business model threatens all of these services in the long run.

But the business model is different when a customer owns the storage. Here the customer owns the actual storage cost. The only thing that Connected Data provides is the client software and the internet service that runs it. Pricing for the 1TB and 2TB transporters with disk drives are $150 and $240.

Having a Transporter

One thing I don’t like is the lack of data-at-rest encryption. They use TLS for data transfers across your LAN and the Internet. But the nice thing about having possession of the actual storage is that you can move it around. But the downside is that you may move it to less secure environments (like conference hotel rooms). And as with the any disk storage, someone can come up to the device and steel the disk. Whether the data would be easily recognizable is another question but having it be encrypted would put that question to rest. There’s some indication on the Transporter support site that encryption may be coming for the business class solution. But nothing was said about the Transporter tower.

On the Mac, the Transporter folder has the shared folders as direct links (real sub-folders) but the local data is under a Transporter Library soft link. It turns out to be a hidden file (“.Transporter Library”) under the Transporter folder. When you Control click on this file your are given the option to view deleted files. You can also do this with shared files as well.

One problem with synch and share services is once someone in your collaboration group deletes some shared files they are gone (over time) from all other group users. Even if some of them wanted them. Transporter makes it a bit easier to view these files and save them elsewhere. But I assume at some point they have to be purged to free up space.

When I first installed the Transporter, it showed up as a network node on my finder shared servers. But the latest desktop version (3.1.17) has removed this.

Also some of the bloggers complained about files seeing files “in flux” or duplicates of the shared files but with unusual file suffixes appended to them, such as ” filename124224_f367b3b1-63fa-4d29-8d7b-a534e0323389.jpg”. Enrico (@ESignoretti) opened up a support ticket on this and it’s supposedly been fixed in the latest desktop and was a temporary filename used only during upload and should have been deleted-renamed after the upload was completed. I just uploaded 22MB with about 40 files and didn’t see any of this.

I really want encryption as I wanted one transporter in a remote office and another in the home office with everything synched locally and then I would hand carry the remote one to the other location. But without encryption this isn’t going to work for me. So I guess I will limit myself to just one and move it around to wherever I want to my data to go.

Here are some of the other blog posts by SFD7 participants on Transporter:

Storage field day 7 – day 2 – Connected Data by Dan Firth (@PenguinPunk)

File Transporter, private Synch&Share made easy by Enrico Signoretti (@ESignoretti)

Transporter – Storage Field Day 7 preview by Keith Townsend (@VirtualizedGeek)

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