Category Archives: Clusters

The All-Important Storage Appliance Mindset for HPC and AI projects

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I am strong believer of using the right tool to do the job right. I have said this before 2 years ago, in my blog “Stating the case for a Storage Appliance approach“. It was written when I was previously working for an open source storage company. And I am an advocate of the crafter versus assembler mindset, especially in the enterprise and high- performance storage technology segments.

I have joined DDN. Even with DDN that same mindset does not change a bit. I have been saying all along that the storage appliance model should always be the mindset for the businesses’ peace-of-mind.

My view of the storage appliance model began almost 25 years. I came into NAS systems world via Sun Microsystems®. Sun was famous for running NFS servers on general Sun Solaris servers. NFS services on Unix systems. Back then, I remember arguing with one of the Sun distributors about the tenets of running NFS over 100Mbit/sec Ethernet on Sun servers. I was drinking Sun’s Kool-Aid big time.

When I joined Network Appliance® (now NetApp®) in 2000, my worldview of putting software on general purpose servers changed. Network Appliance®, had one product family, the FAS700 (720, 740, 760) family. All NetApp® did was to serve NFS services in the beginning. They were the NAS filers and nothing else.

I was completed sold on the appliance way with NetApp®. Firstly, it was my very first time knowing such network storage services could be provisioned with an appliance concept. This was different from Sun. I was used to managing NFS exports on a Sun SPARCstation 20 to Unix clients in the network.

Secondly, my mindset began to shape that “you have to have the right tool to the job correctly and extremely well“. Well, the toaster toasts bread very well and nothing else. And the fridge (an analogy used by Dave Hitz, I think) does what it does very well too. That is what the appliance does. You definitely cannot grill a steak with a bread toaster, just like you can’t run an excellent, ultra-high performance storage services to serve the demanding AI and HPC applications on a general server platform. You have to have a storage appliance solution for High-Speed Storage.

That little Network Appliance® toaster award given out to exemplary employees stood vividly in my mind. The NetApp® tagline back then was “Fast, Simple, Reliable”. That solidifies my mindset for the high-speed storage in AI and HPC projects in present times.

DDN AI400X2 Turbo Appliance

Costs Benefits and Risks

I like to think about what the end users are thinking about. There are investments costs involved, and along with it, risks to the investments as well as their benefits. Let’s just simplify and lump them into Cost-Benefits-Risk analysis triangle. These variables come into play in the decision making of AI and HPC projects.

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Preliminary Data Taxonomy at ingestion. An opportunity for Computational Storage

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Data governance has been on my mind a lot lately. With all the incessant talks and hype about Artificial Intelligence, the true value of AI comes from good data. Therefore, it is vital for any organization embarking on their AI journey to have good quality data. And the journey of the lifecycle of data in an organization starts at the point of ingestion, the data source of how data is either created, acquired to be presented up into the processing workflow and data pipelines for AI training and onwards to AI applications.

In biology, taxonomy is the scientific study and practice of naming, defining and classifying biological organisms based on shared characteristics.

And so, begins my argument of meshing these 3 topics together – data ingestion, data taxonomy and with Computational Storage. Here goes my storage punditry.

Data Taxonomy in post-injection 

I see that data, any data, has to arrive at a repository first before they are given meaning, context, specifications. These requirements are different from file permissions, ownerships, ctime and atime timestamps, the content of the ingested data stream are made to fit into the mould of the repository the data is written to. Metadata about the content of the data gives the data meaning, context and most importantly, value as it is used within the data lifecycle. However, the metadata tagging, and preparing the data in the ETL (extract load transform) or the ELT (extract load transform) process are only applied post-ingestion. This data preparation phase, in which data is enriched with content metadata, tagging, taxonomy and classification, is expensive, in term of resources, time and currency.

Elements of a modern event-driven architecture including data ingestion (Credit: Qlik)

Even in the burgeoning times of open table formats (Apache Iceberg, HUDI, Deltalake, et al), open big data file formats (Avro, Parquet) and open data formats (CSV, XML, JSON et.al), the format specifications with added context and meanings are added in and augmented post-injection.

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Deploying a MinIO SNMD Object Storage Server in TrueNAS SCALE

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[ Preamble ] This deployment of MinIO SNMD (single node multi drive) object storage server on TrueNAS® SCALE 24.04 (codename “Dragonfish”) is experimental. I am just deploying this in my home lab for the fun of it. Do not deploy in any production environment.

I have been contemplating this for quite a while. Which MinIO deployment mode on TrueNAS® SCALE should I work on? For one, there are 3 modes – Standalone, SNMD (Single Node Multi Drives) and MNMD (Multi Node Multi Drives). Of course, the ideal lab experiment is MNMD deployment, the MinIO cluster, and I am still experimenting this on my meagre lab resources.

In the end, I decided to implement SNMD since this is, most likely, deployed on top of a TrueNAS® SCALE storage appliance instead an x-86 bare-metal or in a Kubernetes cluster on Linux systems. Incidentally, the concept of MNMD on top of TrueNAS® SCALE is “Kubernetes cluster”-like albeit a different container platform. At the same time, if this is deployed in a TrueNAS® SCALE Enterprise, a dual-controller TrueNAS® storage appliance, it will take care of the “MinIO nodes” availability in its active-passive HA architecture of the appliance. Otherwise, it can be a full MinIO cluster spread and distributed across several TrueNAS storage appliances (minimum 4 nodes in a 2+2 erasure set) in an MNMD deployment scheme.

Ideally, the MNMD deployment should look like this:

MinIO distributed multi-node cluster architecture (credit: MinIO)

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Enhancing NAS client resiliency and performance with SMB Multichannel and NFS nconnect

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NAS (network attached storage) is obviously the file-level workhorse for shared resources in the network of any organization. SMB (server message block) for Windows environments and NFS (network file system) for Linux platforms are the 2 most prominent protocols that rule the NAS world. Of course we have SMB implementations in the form of Samba and others in non-Windows, Linux and NFS implementations in Windows as well.

As the versions of both network file sharing protocols iterated, present versions of SMB v3.x and NFS v4.x (NFS v3 on the supported Linux kernel version) on the client-side have evolved well. Both now have enhanced resiliency and performance improvement features. And there is an underlying similarity of both implementations. This blog looks at the client-side architectures of both.

One TCP connection

NAS is a client-server architecture. Over the network, NAS clients (SMB or NFS) access their corresponding NAS server(s) – SMB or NFS server(s) – through the TCP/IP network.

NAS client-server architecture (Credit: https://hypertecsp.com/en-CA/knowledge-base/nas-vs-san/)

One very important key starting point to note is the use of one TCP connection per NAS client to the NAS server relationship. For both SMB and NFS, there is just one TCP link between client and the server even if there are several SMB mapped shares or NFS mount points respectively on the clients.

For a long time, this one TCP connection is sufficient for the NAS traffic. But as the network file accesses grow, this connection becomes both a single point of failure as well as a performance bottleneck.

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OpenZFS dRAID has risen!

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We await the 3rd iteration of TrueNAS® SCALE 23.10 codenamed Cobia. 23.10 means October 2023, and we are within weeks of its announcement.

One of the best features I have been waiting for is dRAID or distributed RAID. I have written about it dRAID a couple of years back. It was announced in 2021, in OpenZFS 2.1, but we have not seen an commercial implementation of dRAID … until iXsystems™ TrueNAS® SCALE 23.10. Why am I so excited?

I have followed the technology since Isaac Huang presented dRAID at the OpenZFS Summit in 2015. Through the years ahead, I have seen Isaac presenting dRAID at the summits, and with each iteration, dRAID got closer and closer to be developed into OpenZFS. It was not until 2021, in OpenZFS 2.1 when dRAID became part of filesystem. And now, dRAID is finally in the TrueNAS® SCALE offering.

Knowing RAID resilvering

RAID rebuilding or reconstruction is a painful and potentially risky process. In OpenZFS and ZFS speak, this process is called resilvering. In simple laymen terms, when a drive (or drives) failed in a parity-based RAID volume (eg. RAID-Z1 or RAID-Z2 vdev), the data which was previously in the failed drive is recreated in the newly integrated spare drive. The structural integrity of the RAID volume (and the storage pool) is preserved but the data that was lost is painstakingly remade through the mathematical algorithm of the parity function of the RAID volume.

When hard disk drives were small in capacity like 2TB or less, the RAID resilvering process was probably faster to complete, returning the parity RAID volume to a normal, online state. But today, drives are 22TB and higher, leaving the traditional RAID resilvering process to take days and even weeks. This leads the RAID volume vulnerable to another possible drive failure, weakening the integrity of the RAID volume. Even worse, most of modern day storage arrays have many disk drives, into the thousands even. And yes, solid state drives would probably be faster in the resilvering, but the same mechanics pretty much apply in OpenZFS.

At the same time, the spare drives are assigned physically and designated to the OpenZFS storage pool, and are not part of the vdev until the resilvering process kicks in.

Yes, this is pretty much a physical process that takes time, computing resources and patience. Note the operative word of “physical” here.

dRAID resilvering

dRAID speeds up the RAID resilvering process several folds, returning the RAID volume (or vdev) much faster than traditional OpenZFS RAID resilvering process. It uses a logical (as opposed to physical) RAID layout concept and uses “logical spare drives”. Thus, there will be many spares “blocks” distributed across the entire dRAID zpool, as shown in the diagram below.

Traditional RAID vdev vs dRAID vdev

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Disaggregation and Composability vital for AI/DL models to scale

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New generations of applications and workloads like AI/DL (Artificial Intelligence/Deep Learning), and HPC (High Performance Computing) are breaking the seams of entrenched storage infrastructure models and frameworks. We cannot continue to scale-up or scale-out the storage infrastructure to meet these inundating fluctuating I/O demands. It is time to look at another storage architecture type of infrastructure technology – Composable Infrastructure Architecture.

Infrastructure is changing. The previous staid infrastructure architecture parts of compute, network and storage have long been thrown of the window, precipitated by the rise of x86 server virtualization almost 20 years now. It triggered a tsunami of virtualizing everything, including storage virtualization, which eventually found a more current nomenclature – Software Defined Storage. Both storage virtualization and software defined storage (SDS) are similar and yet different and should be revered through different contexts and similar goals. This Tech Target article laid out both nicely.

As virtualization raged on, converged infrastructure (CI) which evolved into hyperconverged infrastructure (HCI) went fever pitch for a while. Companies like Maxta, Pivot3, Atlantis, are pretty much gone, with HPE® Simplivity and Cisco® Hyperflex occasionally blipped in my radar. In a market that matured very fast, HCI is now dominated by Nutanix™ and VMware®, with smaller Microsoft®, Dell EMC® following them.

From HCI, the attention of virtualization has shifted something more granular, more scalable in containerization. Despite a degree of complexity, containerization is taking agility and scalability to the next level. Kubernetes, Dockers are now mainstay nomenclature of infrastructure engineers and DevOps. So what is driving composable infrastructure? Have we reached the end of virtualization? Not really.

Evolution of infrastructure. Source: IDC

It is just that one part of the infrastructure landscape is changing. This new generation of AI/ML workloads are flipping the coin to the other side of virtualization. As we see the diagram above, IDC brought this mindset change to get us to Think Composability, the next phase of Infrastructure.

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TrueNAS SCALE Clustered SMB to the fore

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iXsystems™ released second iteration of TrueNAS® SCALE software just over a week ago. It is known as version 22.02.2 or Anglefish.2, with the most notable upgrades to HA (High Availability) for SCALE and Clustered SMB capabilities. This is the perfect excuse for me to learn about Clustered SMB and share what I have learned.

TrueNAS SCALEFor the

For the uninformed, Clustered SMB brings highly available SMB file sharing services to mission critical environments. More importantly, Clustered SMB is high availability in a scale-out clustered architecture.

My view beyond HA SMB

I am not familiar with Clustered SMB in a NAS (Network Attached Storage). The world I am more familiar with is either having CIFS/SMB file services on a dual controller storage appliance or running Windows File Sharing on an Microsoft® Clustered Service (MSCS). Typically in these 2 types of HA SMB services, the scale up architecture require a shared access to a consolidated storage volume. Behind the scenes, there are many mechanisms at play to ensure that one, and only one, storage controller or HA host can have write access capabilities at one time. The most common mechanism is the SCSI-3 Persistent Reservation or sometimes known as SCSI fencing, using the SPC-3 (SCSI Primary Command) primitives. The whole objective is to prevent 2 nodes or hosts to writing to the shared storage volume at the same time and other issues like split-brain.

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Stating the case for a Storage Appliance approach

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I was in Indonesia last week to meet with iXsystems™‘ partner PT Maha Data Solusi. I had the wonderful opportunity to meet with many people there and one interesting and often-replayed question arose. Why aren’t iX doing software-defined-storage (SDS)? It was a very obvious and deliberate question.

After all, iX is already providing the free use of the open source TrueNAS® CORE software that runs on many x86 systems as an SDS solution and yet commercially, iX sell the TrueNAS® storage appliances.

This argument between a storage appliance model and a storage storage only model has been debated for more than a decade, and it does come into my conversations on and off. I finally want to address this here, with my own views and opinions. And I want to inform that I am open to both models, because as a storage consultant, both have their pros and cons, advantages and disadvantages. Up front I gravitate to the storage appliance model, and here’s why.

My story of the storage appliance begins …

Back in the 90s, most of my work was on Fibre Channel and NFS. iSCSI has not existed yet (iSCSI was ratified in 2003). It was almost exclusively on the Sun Microsystems® enterprise storage with Sun’s software resell of the Veritas® software suite that included the Sun Volume Manager (VxVM), Veritas® Filesystem (VxFS), Veritas® Replication (VxVR) and Veritas® Cluster Server (VCS). I didn’t do much Veritas® NetBackup (NBU) although I was trained at Veritas® in Boston in July 1997 (I remembered that 2 weeks’ trip fondly). It was just over 2 months after Veritas® acquired OpenVision. Backup Plus was the NetBackup.

Between 1998-1999, I spent a lot of time working Sun NFS servers. The prevalent networking speed at that time was 100Mbits/sec. And I remember having this argument with a Sun partner engineer by the name of Wong Teck Seng. Teck Seng was an inquisitive fella (still is) and he was raving about this purpose-built NFS server he knew about and he shared his experience with me. I detracted him, brushing aside his always-on tech orgasm, and did not find great things about a NAS storage appliance. Auspex™ was big then, and I knew of them.

I joined NetApp® as Malaysia’s employee #2. It was an odd few months working with a storage appliance but after a couple of months, I started to understand and appreciate the philosophy. The storage Appliance Model made sense to me, even through these days.

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As Disk Drive capacity gets larger (and larger), the resilient Filesystem matters

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I just got home from the wonderful iXsystems™ Sales Summit in Knoxville, Tennessee. The key highlight was to christian the opening of iXsystems™ Maryville facility, the key operations center that will house iX engineering, support and part of marketing as well. News of this can be found here.

iX datacenter in the new Maryville facility

Western Digital® has always been a big advocate of iX, and at the Summit, they shared their hard disk drives HDD, solid state drives SSD, and other storage platforms roadmaps. I felt like a kid a candy store because I love all these excitements in the disk drive industry. Who says HDDs are going to be usurped by SSDs?

Several other disk drive manufacturers, including Western Digital®, have announced larger capacity drives. Here are some news of each vendor in recent months

Other than the AFR (annualized failure rates) numbers published by Backblaze every quarter, the Capacity factor has always been a measurement of high interest in the storage industry.

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