Stating the case for a Storage Appliance approach

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

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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Ridding consumer storage mindset for Enterprise operations

I cut my teeth in Enterprise Storage for 3 decades. On and off, I get the opportunity to work on Cloud Storage as well, mostly more structured storage infrastructure services such as blocks and files, in cloud offerings on AWS, Azure and Alibaba Cloud. I am familiar with S3 operations (mostly the CRUD operations and HTTP headers stuff) too, although I have yet to go deep with S3 with Restful API. And I really wanted to work on stuff with the S3 Select when the opportunity arises. (Note: Homelab project to-do list)

Along with the experience is the enterprise mindset of designing and crafting storage infrastructure and data management practices that evolve around data. Understanding the characteristics of data and the behaviours data in motion is part of my skills repertoire, and I continue to have conversations with organizations, small and large alike every day of the week.

This week’s blog was triggered by an article by Tech Republic® Jack Wallen‘s interview with Fedora project leader Matthew Miller. I have been craning my neck waiting for the full release of Fedora 36 (which now has been pushed to May 10th 2022), and the Tech Republic®’s article, “The future of Linux: Fedora project leader weighs in” touched me. Let me set the context of my expanded commentaries here.

History of my open source experience- bringing Enterprise to the individual

I have been working with open source software for a long time. My first Linux experience was Soft Landing Linux in the early 90s. It was a bunch of diskettes I purchased online while dabbling with FreeBSD® on the sides. Even though my day job was on the SunOS, and later Solaris®, having the opportunity to build stuff and learn the enterprise ways with Sun Microsystems® hardware and software were difficult at my homelab. I did bring home a SPARCstation® 2 once but the CRT monitor almost broke my computer table at that time.

Having open source software on 386i (before x86) architecture was great (no matter how buggy they were) because I got to learn hardcore enterprise technology at home. I am a command line person, so the desktop experience does not bother me much because my OS foundation is there. Open source gave me a world I could master my skills as an individual. For an individual like me, my mindset is always on the Enterprise.

The Tech Republic interview and my reflections

I know the journey open source OSes has taken at the server (aka Enterprise) level. They are great, and are getting better and better. But at the desktop (aka consumer) level, the Linux desktop experience has been an arduous one even though the open source Linux desktop experience is so much better now. This interview reflected on that.

There were a few significant points that were brought up. Those poignant moments explained about the free software in open source projects, how consumers glazed over (if I get what Matt Miller meant) the cosmetics of the open source software without the deeper meaningful objectives of the software had me feeling empty. Many assumed that just because the software is open source, it should be free or of low costs and continue to apply a consumer mindset to the delivery and the capability of the software.

Case in point is the way I have been seeing many TrueNAS®/FreeNAS™ individuals who downloaded the free software and using them in consumer ways. That is perfectly fine but when they want to migrate their consumer experience with the TrueNAS® software to their critical business operations, things suddenly do not look so rosy anymore. From my experience, having built enterprise-grade storage solutions with open source software like ZFS on OpenSolaris/OpenIndiana, FreeNAS™ and TrueNAS® for over a decade plus gaining plenty of experience on many proprietary and software-defined storage platforms along this 30 year career, the consumer mindsets do not work well in enterprise missions.

And over the years, I have been seeing this newer generation of infrastructure people taking less and less interest in learning the enterprise ways or going deep dive into the workings of the open source platforms I have mentioned. Yet, they have lofty enterprise expectations while carrying a consumer mindset. More and more, I am seeing a greying crew of storage practitioners with enterprise experiences dealing with a new generation of organizations and end users with consumer practices and mindsets.

Open Source Word Cloud

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I built a 6-node Gluster cluster with TrueNAS SCALE

I haven’t had hands-on with Gluster for over a decade. My last blog about Gluster was in 2011, right after I did a proof-of-concept for the now defunct, Jaring, Malaysia’s first ISP (Internet Service Provider). But I followed Gluster’s development on and off, until I found out that Gluster was a feature in then upcoming TrueNAS® SCALE. That was almost 2 years ago, just before I accepted to offer to join iXsystems™, my present employer.

The eagerness to test drive Gluster (again) on TrueNAS® SCALE has always been there but I waited for SCALE to become GA. GA finally came on February 22, 2022. My plans for the test rig was laid out, and in the past few weeks, I have been diligently re-learning and putting up the scope to built a 6-node Gluster clustered storage with TrueNAS® SCALE VMs on Virtualbox®.

Gluster on OpenZFS with TrueNAS SCALE

Before we continue, I must warn that this is not pretty. I have limited computing resources in my homelab, but Gluster worked beautifully once I ironed out the inefficiencies. Secondly, this is not a performance test as well, for obvious reasons. So, this is the annals along with the trials and tribulations of my 6-node Gluster cluster test rig on TrueNAS® SCALE.

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Nakivo Backup Replication architecture and installation on TrueNAS – Part 1

Backup and Replication software have received strong mandates in organizations with enterprise mindsets and vision. But lower down the rung, small medium organizations are less invested in backup and replication software. These organizations know full well that they must backup, replicate and protect their servers, physical and virtual, and also new workloads in the clouds, given the threat of security breaches and ransomware is looming larger and larger all the time. But many are often put off by the cost of implementing and deploying a Backup and Replication software.

So I explored one of the lesser known backup and recovery software called Nakivo® Backup and Replication (NBR) and took the opportunity to build a backup and replication appliance in my homelab with TrueNAS®. My objective was to create a cost effective option for small medium organizations to enjoy enterprise-grade protection and recovery without the hefty price tag.

This blog, Part 1, writes about the architecture overview of Nakivo® and the installation of the NBR software in TrueNAS® to bake in and create the concept of a backup and replication appliance. Part 2, in a future blog post, will cover the administrative and operations usage of NBR.

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Computational Storage embodies Data Velocity and Locality

I have been earnestly observing the growth of Computational Storage for a number of years now.  It was known by several previous names, with the name “in-situ data processing” stuck with me the most. The Computational Storage nomenclature became more cohesive when SNIA® put together the CMSI (Compute Memory Storage Initiative) some time back. This initiative is where several standards bodies, the major technology players and several SIGs (special interest groups) in SNIA® collaborated to advance Computational Storage segment in the storage technology industry we know of today.

The use cases for Computational Storage are burgeoning, and the functional implementations of Computational Storage are becoming vital to tackle the explosive data tsunami. In 2018 IDC, in its Worldwide Global Datasphere Forecast 2021-2025 report, predicted that the world will have 175 ZB (zettabytes) of data. That number, according to hearsay, has been revised to a heady figure of 250ZB, given the superlative rate data is being originated, spawned and more.

Computational Storage driving factors

If we take the Computer Science definition of in-situ processing, Computational Storage can be distilled as processing data where it resides. In a nutshell, “Bring Compute closer to Storage“. This means that there is a processing unit within the storage subsystem which does not require the host CPU to perform processing. In a very simplistic manner, a RAID card in a storage array can be considered a Computational Storage device because it performs the RAID functions instead of the host CPU. But this new generation of Computational Storage has much more prowess than just the RAID function in a RAID card.

There are many factors in Computational Storage that make a lot sense. Here are a few:

  1. Voluminous data inundate the centralized architecture of the cloud platforms and the enterprise systems today. Much of the data come from end point devices – mobile devices, sensors, IoT, point-of-sales, video cameras, et.al. Pre-processing the data at the origin data points can help filter the data, reduce the size to be processed centrally, and secure the data before they are ingested into the central data processing systems
  2. Real-time processing of the data at the moment the data is received gives the opportunity to create the Velocity of Data Analytics. Much of the data do not need to move to a central data processing system for analysis. Often in use cases like autonomous vehicles, fraud detection, recommendation systems, disaster alerts etc require near instantaneous responses. Performing early data analytics at the data origin point has tremendous advantages.
  3. Moore’s Law is waning. The CPU (central processing unit) is no longer the center of the universe. We are beginning to see CPU offloading technologies to augment the CPU’s duties such as compression, encryption, transcoding and more. SmartNICs, DPUs (data processing units), VPUs (visual processing units), GPUs (graphics processing units), etc have come forth to formulate a new computing paradigm.
  4. Freeing up central resources with Computational Storage also accelerates the overall distributed data processing in the whole data architecture. The CPU and the adjoining memory subsystem are less required to perform context switching caused by I/O interrupts as in most of the compute/storage architecture today. The total effect relieves the CPU and giving back more CPU cycles to perform higher processing tasks, resulting in faster performance overall.
  5. The rise of memory interconnects is enabling a more distributed computing fabric of data processing subsystems. The rising CXL (Compute Express Link™) interconnect protocol, especially after the Gen-Z annex, has emerged a force to be reckoned with. This rise of memory interconnects will likely strengthen the testimony of Computational Storage in the fast approaching future.

Computational Storage Deployment Models

SNIA Computational Storage Universe in 2019

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Please cultivate 3-2-1 and A-B-C of Data Management

My Sunday morning was muddled 2 weeks ago. There was a frenetic call from someone whom I knew a while back and he needed some advice. Turned out that his company’s files were encrypted and the “backups” (more on this later) were gone. With some detective work, I found that their files were stored in a Synology® NAS, often accessed via QuickConnect remotely, and “backed up” to Microsoft® Azure. I put “Backup” in inverted commas because their definition of “backup” was using Synology®’s Cloud Sync to Azure. It is not a true backup but a file synchronization service that often mislabeled as a data protection backup service.

All of his company’s projects files were encrypted and there were no backups to recover from. It was a typical ransomware cluster F crime scene.

I would have gloated because many of small medium businesses like his take a very poor and lackadaisical attitude towards good data management practices. No use crying over spilled milk when prevention is better than cure. But instead of investing early in the prevention, the cure would likely be 3x more expensive. And in this case, he wanted to use Deloitte® recovery services, which I did not know existed. Good luck with the recovery was all I said to him after my Sunday morning was made topsy turvy of sorts.

NAS is the ransomware goldmine

I have said it before and I am saying it again. NAS devices, especially the consumer and prosumer brands, are easy pickings because there was little attention paid to implement a good data management practice either by the respective vendor or the end users themselves. 2 years ago I was already seeing a consistent pattern of the heightened ransomware attacks on NAS devices, especially the NAS devices that proliferated the small medium businesses market segment.

The WFH (work from home) practice trigged by the Covid-19 pandemic has made NAS devices essential for businesses. NAS are the workhorses of many businesses after all.  The ease of connecting from anywhere with features similar to the Synology® QuickConnect I mentioned earlier, or through VPNs (virtual private networks), or a self created port forwarding (for those who wants to save a quick buck [ sarcasm ]), opened the doors to bad actors and easy ransomware incursions. Good data management practices are often sidestepped or ignored in exchange for simplicity, convenience, and trying to save foolish dollars. Until ….

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A conceptual distributed enterprise HCI with open source software

Cloud computing has changed everything, at least at the infrastructure level. Kubernetes is changing everything as well, at the application level. Enterprises are attracted by tenets of cloud computing and thus, cloud adoption has escalated. But it does not have to be a zero-sum game. Hybrid computing can give enterprises a balanced choice, and they can take advantage of the best of both worlds.

Open Source has changed everything too because organizations now has a choice to balance their costs and expenditures with top enterprise-grade software. The challenge is what can organizations do to put these pieces together using open source software? Integration of open source infrastructure software and applications can be complex and costly.

The next version of HCI

Hyperconverged Infrastructure (HCI) also changed the game. Integration of compute, network and storage became easier, more seamless and less costly when HCI entered the market. Wrapped with a single control plane, the HCI management component can orchestrate VM (virtual machine) resources without much friction. That was HCI 1.0.

But HCI 1.0 was challenged, because several key components of its architecture were based on DAS (direct attached) storage. Scaling storage from a capacity point of view was limited by storage components attached to the HCI architecture. Some storage vendors decided to be creative and created dHCI (disaggregated HCI). If you break down the components one by one, in my opinion, dHCI is just a SAN (storage area network) to HCI. Maybe this should be HCI 1.5.

A new version of an HCI architecture is swimming in as Angelfish

Kubernetes came into the HCI picture in recent years. Without the weights and dependencies of VMs and DAS at the HCI server layer, lightweight containers orchestrated, mostly by, Kubernetes, made distribution of compute easier. From on-premises to cloud and in between, compute resources can easily spun up or down anywhere.

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Crash consistent data recovery for ZFS volumes

While TrueNAS® CORE and TrueNAS® Enterprise are more well known for its NAS (network attached storage) prowess, many organizations are also confidently placing their enterprise applications such as hypervisors and databases on TrueNAS® via SANs (storage area networks) as well. Both iSCSI and Fibre Channel™ (selected TrueNAS® Enterprise storage models) protocols are supported well.

To reliably protect these block-based applications via the SAN protocols, ZFS snapshot is the key technology that can be dependent upon to restore the enterprise applications quickly. However, there are still some confusions when it comes to the state of recovery from the ZFS snapshots. On that matter, this situations are not unique to the ZFS environments because as with many other storage technologies, the confusion often stem from the (mis)understanding of the consistency state of the data in the backups and in the snapshots.

Crash Consistency vs Application Consistency

To dispel this misunderstanding, we must first begin with the understanding of a generic filesystem agnostic snapshot. It is a point-in-time copy, just like a data copy on the tape or in the disks or in the cloud backup. It is a complete image of the data and the state of the data at the storage layer at the time the storage snapshot was taken. This means that the data and metadata in this snapshot copy/version has a consistent state at that point in time. This state is frozen for this particular snapshot version, and therefore it is often labeled as “crash consistent“.

In the event of a subsystem (application, compute, storage, rack, site, etc) failure or a power loss, data recovery can be initiated using the last known “crash consistent” state, i.e. restoring from the last good backup or snapshot copy. Depending on applications, operating systems, hypervisors, filesystems and the subsystems (journals, transaction logs, protocol resiliency primitives etc) that are aligned with them, some workloads will just continue from where it stopped. It may already have some recovery mechanisms or these workloads can accept data loss without data corruption and inconsistencies.

Some applications, especially databases, are more sensitive to data and state consistencies. That is because of how these applications are designed. Take for instance, the Oracle® database. When an Oracle® database instance is online, there is an SGA (system global area) which handles all the running mechanics of the database. SGA exists in the memory of the compute along with transaction logs, tablespaces, and open files that represent the Oracle® database instance. From time to time, often measured in seconds, the state of the Oracle® instance and the data it is processing have to be synched to non-volatile, persistent storage. This commit is important to ensure the integrity of the data at all times.

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