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    Common Questions on Clustered File Systems

    November 18th, 2016

    More than 350 people have already seen our SNIA Ethernet Storage Forum (ESF) webcast “Clustered File Systems: No Limits.” Our presenters, James Coomer and Jerry Lotto, did a great job explaining what clustered file systems are, key considerations, choices and performance. As we expected, there were plenty of questions, so as promised, here are answers to them all.

    Q: Parallel NFS (pNFS) has been in development/standard effort for a long time, and I believe pNFS is not in the Linux kernel it appears pNFS is yet to be prime time.

    A: pNFS has been in Linux for over a decade! Clients and server are widely available, and you should look at the SNIA White Paper “An Updated Overview of NFSv4; NFSv4.0, NFSv4.1, pNFS, and NFSv4.2” for more information on the current state of play.

    Q: Why the emphasis on parallel I/O? Any single storage server can feed results at link capacity, so you do not need multiple storage servers to feed a client at full speed. Isn’t the more critical issue the bottleneck on access to metadata for a single directory or file? Federated NAS bottlenecks updates for each directory behind a single master server?

    A: Any one storage server can usually saturate one client, but often there are multiple hungry clients making requests simultaneously. Using parallel I/O allows multiple servers to feed multiple high-bandwidth clients across a narrow or wide set of data. This smooths out the I/O load on the servers in a near-perfect manner regardless of the number of clients performing I/O. It is absolutely true that metadata serving can become a bottleneck, so parallel file systems use cached and/or distributed metadata to overcome this and again, every client takes part in that interaction and shares some responsibility for managing communicating metadata updates.

    Q: Can any application access parallel file system (i.e. through an agent in the driver level)? Or does it require specific code within the application?

    A: Native access to a parallel file system requires a specific client or agent in the host, but many parallel file systems allow any client to access the data through a NAS protocol gateway. No changes are needed to applications to use a parallel file system – These parallel file systems are mounted as a POSIX compliant file system and therefore adhere to basically the same standards as an NFS mount for example.

    Q: Are parallel file system clients compatible with scale-out NAS servers?

    A: Nearly all scale-out NAS servers speak a standard NAS protocol like NFS or SMB. Clients running a parallel file system client can also access NAS via these standard protocols. Exceptions to this may possibly (but none that we know of) occur for scale-out NAS servers that support a modified NFS/SMB protocol or a custom NAS client which might conceivably conflict with the parallel file system client when installed on an OS.

    Q: Of course I am biased, but I am fond of the AFS (Andrew File System) Family of File Systems.   There is OpenAFS, but there is also what we are doing at AuriStor extending beyond the core AFS global namespace model (security functionality, and performance)

    A: AFS is another distributed file system which supports large scale deployments, native clients for many platforms, and strong security features. It also uses local caching of files to improve performance. It uses a weakly consistent file locking system so multiple clients can access the same file simultaneously but they cannot both update the same file at the same time. OpenAFS is an open-source implementation of AFS. Auristor (formerly Your File System, Inc.) is a startup providing a commercial parallel file system that is compatible with AFS.

    Q: I am more familiar with Veritas Cluster File System, could you please do a quick compare with Lustre or GPFS?

    A: The Veritas Cluster File System (formerly VxCFS, now part of Veritas InfoScale) is a distributed file system that runs on Linux and popular flavors of Unix. It supports up to 64 nodes and allows multiple nodes to share the same back-end storage hardware. Comparing it to Lustre and GPFS is beyond the scope of this webinar, but in basic terms, parallel file systems can offer far greater scalability and bandwidth for example, through the use of optimized RDMA clients for high performance networks.

    Q: Why do file apps need shared access to data, but block apps do not?

    A: Traditionally block storage did not offer shared access to data (except when used as shared back-end storage for a clustered file system), while apps that needed shared access to data usually chose to use a NAS protocol such as SMB or NFS. So in many cases file-based apps use file sharing protocols because they need shared access to data from multiple clients. (In other cases file-based applications do not require sharing but the storage administrators believe it’s easier to manage or less expensive than networked block storage.)

    Q: Do Lustre and GPFS have SMB Direct support?

    A: Not today. SMB Direct is an option to use RDMA and multi-channel with the SMB 3 protocol. Both Lustre and GPFS support the ability to export a file system via NFS or SMB, but generally they do not support SMB Direct yet. Both Lustre and GPFS support RDMA access through their clients.

    How to the clients avoid doing simultaneous writes to the same file?

    A: Some parallel file systems allow this by letting different clients write to different parts of the same file. Others do not allow this. In either case, distributed file locking is used to prevent two clients from writing simultaneously to the same part of a file (or to the same file if it’s not allowed).

    Q: How can you say that the application “does not have to worry about” how the clustered file system serializes writes? Doesn’t this require continuous end-to-end connectivity?

    A: When the application writes data it generally writes to a POSIX-compliant file system and does not need to worry about how the parallel file system serializes, distributes, or protects the data because this is virtualized (managed) by the file system. It usually does require continuous end-to-end connectivity from the clients to the servers, though in some cases caching could allow for brief gaps in connectivity and in some systems not every client needs to have network connectivity to every server. There are multiple mechanisms within parallel file systems to manage the various cases of clients/servers disappearing from the network, temporarily or permanently (whilst for example holding a lock).

    Q: How does a parallel file system handle the sequences of write on a same file? Just append one by one? What if a client modified a line?

    A: This is the biggest challenge for and reason to use a parallel file system.  Beneath the covers, coherency is maintained by Spectrum Scale using a token management server process which issues locks for object requests.  Similar functionality is implemented in Lustre using a distributed lock manager.  These objects are most commonly blocks within files rather than entire files, but this is application controlled.  The end result is a POSIX-compliant interface that scales to thousands of clients.

    Q: What does FPO stand for?

    A: File Placement Optimizer – a shared-nothing architecture and licensing model for IBM Spectrum Scale (aka GPFS). Learn more here.

    Q: Is there a concept in parallel file systems for “auto-tuning” yet? Seems like the early days of SAN management and tuning…

    A: Default tuning values are optimized for general purpose workloads, but the whole purpose of tuning parameters is to adjust away from those defaults to optimize the file system for a particular application workload or fil esystem architecture.  Both IBM and OpenSFS with the support of Intel have published extensive documentation on best practices for optimization and tuning for either file system.  We are not aware of any work on “automating” that process but there has been recent work (e.g. in spectrum scale) to simplify the tuning process.

    Q: Which is better as interconnect between disk and servers, shared access or share-nothing?

    A: The use of shared access in the interconnect between disks and servers is limited to providing HA functionality in Lustre or Spectrum Scale, the ability to service I/O requests to a storage device if the server which has primary responsibility for that device is not available.  This usually involves multiple server-attached external storage which can add cost to building the file system.  The alternative approach to HA is to replicate blocks of data to different disks on different servers, cutting back on the usable capacity of the file system.  If HA is not a requirement, a share-nothing architecture will generally involve less hardware and therefore be less expensive to build.

    If you have more questions, please comment on this blog. And I encourage you to check out the SNIA ESF webcast library for educational, vendor-neutral content on Ethernet networked storage topics


    Recognize Volunteer Contributions – Nominations Open for the SNIA Individual and Group Recognition Program

    November 16th, 2016

    Each year, at the Annual Members Symposium, SNIA members recognize their own – volunteers and organizations who have dedicated expertise and time to contribute to the important work done by SNIA technical work groups, committees, and initiatives.  SNIA recognizes with a “Volunteer of the Year” award an individual contributor  who has stepped up to help SNIA achieve new and groundbreaking work or significantly advanced an … Continue reading


    Storage Basics Q&A and No One’s Pride was Hurt

    November 7th, 2016

    In the first of our “Everything You Wanted To Know About Storage But Were Too Proud To Ask – Part Chartreuse,” we covered the storage basics to break down the entire storage picture and identify the places where most of the confusion falls. It was a very well attended event and I’m happy to report, everyone’s pride stayed intact! We got some great questions from the audience, so as promised, here are our answers to all of them:

    Q. What is parity? What is XOR?

    A. In RAID, there are generally two kinds of data that are stored: the actual data and the parity data. The actual data is obvious; parity data is information about the actual data that you can use to reconstruct it if something goes wrong.

    It’s important to note that this is not simply a copy of A and B, but rather a logical operation that is applied to the data. Commonly for RAID (other than simple mirroring) the method used is called an exclusive or, or XOR for short. The XOR function outputs true only when inputs differ (one is true, the other is false).

    There’s a neat feature about XOR, and the reason it’s used by RAID. Calculate the value A XOR B (let’s call it AxB). Here’s an example on a pair of bytes.

    A                                  10011100

    B                                  01101100

    A XOR B is AxB              11110000

    Store all three values on separate disks. Now, if we lose A or B, we can use the fact that AxB XOR B is equal to A, and AxB XOR A is equal to B. For example, for A;

    B                                  01101100

    AxB                              11110000

    A XOR AxB is A              10011100

    We’ve regenerated the A we lost. (If we lose the parity bits, they can just be reconstructed from A and B.)

    Q. What is common notation for RAID? I have seen RAID 4+1, and RAID (4,1). In the past, I thought this meant a total of 5 disks, but in your explanation it is only 4 disks.

    A. RAID is notated by levels, which is determined by the way in which data is laid out on disk drives (there are always at least two). When attempting to achieve fault tolerance, there is always a trade-off between performance and capacity. Such is life.

    There are 4 common RAID levels in use today (there are others, but these are the most common): RAID 0, RAID 1, RAID 5, and RAID 6. As a quick reminder from the webinar (you can see pictures of these in action there):

    • RAID 0: Data is striped across the disks without any parity. Very fast, but very unsafe (if you lose one, you lose all)
    • RAID 1: Data is mirrored between disks without any parity. Slowest, but you have an exact copy of the data so there is no need to recalculate anything to reconstruct the data.
    • RAID 5: Data is striped across multiple disks, and the parity is striped across multiple disks. Often seen as the best compromise: Fast writes and good safety net. Can withstand one disk loss without losing data.
    • RAID 6: Data is striped across multiple disks, and two parity bits are stored on all the disks. Same advantages of RAID 5, except now you can lose 2 drives before data loss.

    Now, if you have enough disks, it is possible to combine RAID levels. You can, for instance, have four drives that combine mirroring and striping. In this case, you can have two sets of drives that are mirrored to each other, and the data is striped to each of those sets. That would be RAID 1+0, or often called RAID 10. Likewise, you can have two sets of RAID 5 drives, and you could stripe or mirror to each of those sets, and it would be RAID 50 or RAID 51, respectively.

    Erasure Coding has a different notation, however. It does not use levels like RAID; instead, EC identifies the number of data bits and the number of parity bits.

    So, with EC, you take a file or object and split it into ‘k’ blocks of equal size. Then, you take those k blocks and generate n blocks of the same size, such that any k out of n blocks suffice to reconstruct the original file. This results in a (n,k) notation for EC.

    Since RAID is a subset of EC, RAID6 is the equivalent of EC or RAID(n,2) or n data disks and 2 parity disks. RAID(4,1) is RAID5 with 4 data and 1 parity, and so on.

    Q. Which RAIDs are classified/referred to as EC? I have often heard people refer to RAID 5/6 as EC. Is this only limited to 5/6?

    A. All RAID levels are types of EC. The math is slightly different; traditional RAID uses XOR, and EC uses Galois Fields or polynomial arithmetic.

    Q. What’s the advantage of RAID5 over RAID1?

    A. As noted above, there is a tradeoff between the amount of capacity that you need in order to stay fault tolerant, and the performance you wish to have in any system.

    RAID 1 is a mirrored system, where you have a single block of data being written twice – one to each disk. This is done in parallel, so it doesn’t take any extra time to do the write, but there’s no speed-up either. One advantage, however, is that if a disk fails there is no need to perform any logical calculations to reconstruct data – you already have a copy of the intact data.

    RAID 5 is more distributed. That is, blocks of data are written to multiple disks simultaneously, along with a parity block. That is, you are breaking up the writing obligations across multiple disks, as well as sending parity data across multiple disks. This significantly speeds up the write process, but more importantly it also distributes the recovery capabilities as well so that any disk can fail without losing data.

    Q. So RAID improves WRITES? I guess because it breaks the data into smaller pieces that can be written in parallel. If this is true, then why will READ not benefit from RAID? Isn’t it that those pieces can be read and re-combined into a larger piece from parallel sources would be faster?

    A. RAID and the “striping” of IO can improve writes by reducing serialization by allowing us to write anywhere. But a specific block can only be read from the disk it was written to, and if we’re already reading or writing to that disk and it’s busy – we must wait.

    Q. Why is EC better for object stores than RAID?

    A. Because there’s more redundancy, EC can be made to operate across unreliable and less responsive links, and at potentially geographic scales.

    Q: Can you explain about the “RAID Penalty?” I’ve heard it called “Write Penalty” or “Read before Write penalty.”

    A. When updating data that’s already been written to disk, there’s a requirement to recalculate the parity data used by RAID. For example, if we update a single byte in a block, we need to read all the blocks, recalculate the parity, and write back the updated data block and the parity block (twice in the case of dual parity RAID6).

    There are some techniques that can be used to improve the performance impact. For example, some systems don’t update blocks in place, but use pointer-based systems and only write new blocks. This technique is used by flash-based SSDs as the write size is often 256KB or larger. This can be done in the drive itself, or by the RAID or storage system software. It is very important to avoid when using Erasure Coding as there are so many data blocks and parity blocks to recalculate and rewrite that it would become prohibitive to do an update.

    Q. What is the significance of RAIN? We have not heard much about it.

    A.A Redundant Array of Independent Nodes works under the same principles of RAID – that is, each node is treated as a failure domain that must be avoided as a Single Point of Failure (SPOF).Where as RAID maintains an understanding of data placement on individual drives within a node, RAIN maintains an understanding of data placement on nodes (that contain drives) within a storage environment.

    Q. Is host same as node?

    A. At its core, a “node” is an endpoint. So, a host can be a node, but so can a storage device at the other end of the wire.

    Q. Does it really matter what Erasure Coding (EC) technologies are named or is EC just EC?

    A. A. Erasure Coding notation refers to the level of resilience involved. This notation underscores not only the write patterns for storage of data, but also the mechanisms necessary for recovery. What ‘matters’ really will depend upon the level of involvement for those particular tasks.

    Q. Is the Volume Manager concept related to Logical Unit Numbering (LUNs)?

    A. It can be. A volume manager is an abstraction layer that allows a host operating system to create a Volume out of one or more media locations. These locations can be either logical or physical. A LUN is an aggregation of media on the target/storage side. You can use a Volume Manager to create a single, logical volume out of multiple LUNs, for instance.

    A. For additional information on this, you may want to watch our SNIA-ESF webcast, “Life of a Storage Packet (Walk).”

    Q. What’s the relationship between disk controller and volume manager?

    A. Following on the last question, a disk controller does exactly what it sounds like – it controls disks. A RAID controller, likewise, controls disks and the read/write mechanisms. Some RAID controllers have additional software abstraction capabilities that can act as a volume manager as well.

    We hope these answers clear things up a bit more. As you know, our “Everything You Wanted To Know About Storage, But Were Too Proud To Ask” is a series, since this Chartreuse event, we’ve done “Part Mauve – The Architecture Pod” where we explained channel vs. bus, control plane vs. data plane and fabric vs. network. Check it out on-demand and follow us on Twitter @SNIAESF for announcements on upcoming webcasts.

     

     


    Cast Your Vote on November 8 for the Magic and Mystery of In-Memory Apps!

    November 2nd, 2016

    It’s an easy “Yes” vote for this great webcast from the SNIA Solid State Storage Initiative on the Magic and Mystery of In-Memory Apps! Join us on Election Day – November 8 – at 1:00 pm ET/10:00 am PT to learn about today’s market and the disruptions that happen when combining big-data vote-yes(Petabytes) with in-memory/real-time requirements.  You’ll understand the interactions with Hadoop/Spark, Tachyon, SAP HANA, NoSQL, and the related infrastructure of DRAM, NAND, 3DXpoint, NV-DIMMs, and high-speed networking and learn what happens to infrastructure design and operations when “tiered-memory” replaces “tiered storage”.

    Presenter Shaun Walsh of G2M Communications is an expert in memory technology – and a great speaker! He’ll share with you what you need to know about evaluating, planning, and implementing in-memory computing applications, and give you the framework to evaluation and plan for your adoption of in-memory computing.

    Register at: https://www.brighttalk.com/webcast/663/230103


    2017 Ethernet Roadmap for Networked Storage

    November 2nd, 2016

    When SNIA’s Ethernet Storage Forum (ESF) last looked at the Ethernet Roadmap for Networked Storage in 2015, we anticipated a world of rapid change. The list of advances in 2016 is nothing short of amazing

    • New adapters, switches, and cables have been launched supporting 25, 50, and 100Gb Ethernet speeds including support from major server vendors and storage startups
    • Multiple vendors have added or updated support for RDMA over Ethernet
    • The growth of NVMe storage devices and release of the NVMe over Fabrics standard are driving demand for both faster speeds and lower latency in networking
    • The growth of cloud, virtualization, hyper-converged infrastructure, object storage, and containers are all increasing the popularity of Ethernet as a storage fabric

    The world of Ethernet in 2017 promises more of the same. Now we revisit the topic with a look ahead at what’s in store for Ethernet in 2017.  Join us on December 1, 2016 for our live webcast, “2017 Ethernet Roadmap to Networked Storage.”

    With all the incredible advances and learning vectors, SNIA ESF has assembled a great team of experts to help you keep up. Here are some of the things to keep track of in the upcoming year:

    • Learn what is driving the adoption of faster Ethernet speeds and new Ethernet storage models
    • Understand the different copper and optical cabling choices available at different speeds and distances
    • Debate how other connectivity options will compete against Ethernet for the new cloud and software-defined storage networks
    • And finally look ahead with us at what Ethernet is planning for new connectivity options and faster speeds such as 200 and 400 Gigabit Ethernet

    The momentum is strong with Ethernet, and we’re here to help you stay informed of the lightning-fast changes. Come join us to look at the future of Ethernet for storage and join this SNIA ESF webcast on December 1st. Register here.

     


    SNIA Puts the You in YouTube

    October 26th, 2016

    Did you know that SNIA has a YouTube Channel?  SNIAVideo is the place designed for You to visit for the latest technical and educational content – all free to download – from SNIA thought leaders and events. youtube channel

    Our latest videos cover a wide range of topics discussed at last month’s SNIA Storage Developer Conference.  Enjoy The Ride Cast video playlist where industry expert Marc Farley … Continue reading


    The Next Step for Containers: Best Practices and Data Management Services

    October 25th, 2016

    In our first SNIA Cloud webcast on containers, we provided a solid foundation on what containers are, container storage challenges and Docker. If you missed the live event, it’s now available on-demand. I encourage you to check it out, as well as our webcast Q&A blog.

    So now that we have set the stage and you’ve become acquainted with basic container technologies and the associated storage challenges in supporting applications running within containers in production, we will be back on December 7th. This time we will take a deeper dive into what differentiates this technology from what you are used to with virtual machines. Containers can both complement virtual machines and also replace them, as they promise the ability to scale exponentially higher. They can easily be ported from one physical server to another or to one platform—such as on-premise—to another—such as public cloud providers like Amazon AWS.

    At our December 7th webcast, “Containers: Best Practices and Data Management Services,” we’ll explore container best practices to address the various challenges around networking, security and logging. We’ll also look at what types of applications more easily lend themselves to a microservice architecture versus which applications may require additional investments to refactor/re-architect to take advantage of microservices.

    On December 7th, we’ll be on hand to answer your questions on the spot. I encourage you to register today. We hope you can attend!


    The Current State of Storage in the Container World

    October 25th, 2016

    It seems like everyone is talking about containers these days, but not everyone is talking about storage – and they should be. The first wave of adoption of container technology was focused on micro services and ephemeral workloads. The next wave of adoption won’t be possible without persistent, shared storage. That’s why the SNIA Ethernet Storage Forum is hosting a live webcast on November 17th, “Current State of Storage in the Container World.” In this webcast, we will provide an overview of Docker containers and the inherent challenge of persistence when containerizing traditional enterprise applications.  We will then examine the different storage solutions available for solving these challenges and provide the pros and cons of each. You’ll hear:

    • An Overview of Containers
      • Quick history, where we are now
      • Virtual machines vs. Containers
      • How Docker containers work
      • Why containers are compelling for customers
      • Challenges
      • Storage
    • Storage Options for Containers
      • NAS vs. SAN
      • Persistent and non-persistent
    • Future Considerations
      • Opportunities for future work

    This webcast should appeal to those interested in understanding the basics of containers and how it relates to storage used with containers. I encourage you to register today! We hope you can make it on November 17th. And if you’re interested in keeping up with all that SNIA is doing with containers, please sign up for our Containers Opt-In Email list and we’ll be sure to keep you posted.

     


    SNIA Storage Developer Conference-The Knowledge Continues

    October 13th, 2016

    SNIA’s 18th Storage Developer Conference is officially a success, with 124 general and breakout sessions;  Cloud Interoperability, Kinetiplugfest 5c Storage, and SMB3 plugfests; ten Birds-of-a-Feather Sessions, and amazing networking among 450+ attendees.  Sessions on NVMe over Fabrics won the title of most attended, but Persistent Memory, Object Storage, and Performance were right behind.  Many thanks to SDC 2016 Sponsors, who engaged attendees in exciting technology … Continue reading


    Not a Tempest But a Seachange – Persistent Memory

    October 12th, 2016

    by Marty Foltyn

    Persistent memory discussions are capturing the minds of SNIA members and colleagues.  At last month’s SNIA Storage Developer Conference, NVM (non-volatile memory) and NVMe sessions were standing-room-only, and opinion sharing continued into animated hallway discussions.  I encourage you to check out the many presentations on the SNIA SDC website, and to download the live recordings of the keynotes here.

    memconSNIA continued their education on persistent memory at this week’s Memcon in Santa Clara CA. SNIA’s booth was packed with attendees asking questions like what is the difference between the different kinds of NVDIMMs (you’ll want to check out our new snia_nvdimm_infographic), and is NVDIMM a standard (indeed, it is, JEDEC just released the DDR4 NVDIMM-N Design Standard Revision 1.0 last month, and you can download the link from our website).

    pm-video-jimThe work being done within SNIA on persistent memory is contributing to a seachange in the industry – the convergence of memory and storage – perhaps the most revolutionary change since the invention of the transistor more than 60 years ago.  To learn more, check out this interview with Jim Pappas, SNIA’s Vice-Chairman and co-chair of the SNIA Solid State Storage Initiative.  And mark your calendar for January 18, 2017, when SNIA will hold the 5th annual Persistent Memory Summit in San Jose CA.  The latest details can be found here.