My 2-day weekend with Nextcloud on FreeNAS

In recent weeks, I have been asked by friends and old cust0mers on how to extend their NAS shared drives to work-from-home, the new reality. Malaysia went into a full lockdown as of June 1st several days ago.

I have written about file synchronization stories before but I have never done a Nextcloud blog. I have little experience with TrueNAS® CORE Nextcloud plugin and this was a good weekend to build it up from scratch with Virtualbox with FreeNAS™ 11.2U5 (because my friend was using that version).

[ Note ] FreeNAS™ 11.2U5 has been EOLed.

Nextcloud login screen

So, here it how it went for my little experiment. FYI, this is not a How-to guide. That will come later after I have put all my notes together with screenshots and all. This is just a collection of my thoughts while setting up Nextcloud on FreeNAS™.

Dropbox® is expensive

Using cloud storage with file sync and share capability is not exactly a cheap thing especially when you are a small medium sized business or a school or a charity organization. Here is the pricing table for Dropbox® for Business :

Dropbox for business pricing

I am using Dropbox® as the example here but the same can be said for OneDrive or Google Drive and others. The pricing can quickly add up when the price is calculated per user per month.

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Memory cloud reality soon?

The original SAN was not always Storage Area Network. SAN had a twin nomenclature called System Area Network (SAN) back in the late 90s. Fibre Channel fabric topology (THE Storage Area Network) was only starting to take off when many of the Fibre Channel topologies at the time were either FC-AL (Fibre Channel Arbitrated Loop) or Point-to-Point. So, for a while SAN was System Area Network, or at least that was what Microsoft® wanted it to be. That SAN obviously did not take off.

System Area Network (architecture shown below) presented a high speed network where server clusters can communicate. The communication protocol of choice was VIA (Virtual Interface Adapter), and the proposed applications, notably the Microsoft® SQL Server, would use Winsock API to interface with the network services. Cache coherency in the combined memory resources of a clustered network is often the technology to ensure data synchronization, consistency and integrity.

Alas, System Area Network did not truly take off, and now it is pretty much deprecated from the Microsoft® universe.

System Area Network (SAN)

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Plotting the Crypto Coin Storage Farm

The recent craze of the Chia cryptocurrency got me excited. Mostly because it uses storage as the determinant for the Proof-of-Work consensus algorithm in a blockchain network. Yes, I am always about storage. 😉

I am not a Bitcoin miner nor am I a Chia coin farmer, and my knowledge and experience in both are very shallow. But I recently became interested in the 2 main activities of Chia – plotting and farming, because they both involved storage. I am writing this blog to find out more and document about my learning experience.

[ NB: This blog does not help you make money. It is just informational from a storage technology perspective. ]

Chia Cryptocurrency

Proof of Space and Time

Bitcoin is based on Proof-of-Work (PoW). In a nutshell, there is a complex mathematical puzzle to be solved. Bitcoin miners compete to solve this puzzle and the process uses high computational processing to solve it. Once solved, the miners are rewarded for their work.

Newer entrants like Filecoin and Chia coin (XCH) use an alternate method which is Proof-of-Space (PoS) to validate and verify the transactions. Instead of miners, Chia coin farmers have to prove to have a legitimate amount of disk and/or memory space to solve a mathematical puzzle, conceptually similar to the one in Bitcoin mining. In the beginning, this was great for folks who have unused disk space that can be “rented” out to store the crypto stuff (Note: I am not familiar with the terminology yet, and I did not want to use the word “crypto tokens” incorrectly). Storj was one of the early vendors that I remember in this space touting this method but I have not followed them for a while. Their business model might have changed.

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Blasphemous technical writing

This is so, so, so wrong! I want to hold back but I can’t hold back no more!

This article from Petapixel appeared in my daily news feed last week. When I saw the title “Seagate performed best in Backblaze’s 2020 Hard Drive Failure Report“, I literally jumped. My immediate thoughts were “This can’t be right“.

Labelling Seagate as the best performer in a Backblaze report not only sounded oxymoronic. It was moronic. For those of us who have the industry experience, we know enough that this cannot be true with just a one fell swoop statement.

Petapixel misleading article title

Backblaze report

Backblaze has been releasing Hard Drive Stats and Report every quarter since 2013. For many of us practitioners, the report has been the de facto standard and indicator of hard disks reliability. Inadvertently, it defines the quality of the hard disk drives associated with the respective manufacturer’s brand and models.

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The hot cold times of HCI

Hyperconverged Infrastructure (HCI) is a hot technology. It has been for the past decade since Nutanix™ took the first mover advantage from the Converged Infrastructure (CI) technology segment and made it pretty much its ownfor a while.

Hyper Converged Infrastructure

But the HCI market (not the technology) is a strange one. It is hot. It is cold. The perennial leader, Nutanix™, has yet to eke out a profitable year. VMware® is strong in the market. Cisco™, which was hot with their HyperFlex solution in 2019, was also stopped short with a dismal decline in the IDC Worldwide HCI 2Q2020 tracker below:

IDC Worldwide Hyperconverged Infrastructure Tracker – 2Q2020

dHCI = Disaggregated or discombobulated? 

dHCI is known as disaggregated HCI. The disaggregation part is disaggregated hardware, especially on the storage part. Vendors like HPE® with Nimble Storage, Hitachi Vantara, NetApp® and a few more have touted the disaggregation of the performance and capacity, the separation of storage and compute as a value proposition but through close inspection, it is just another marketing ploy to attach a SAN storage to servers. It was marketing old wine in a new bottle. As rightly pointed out by my friend, Charles Chow of Commvault® quoted in his blog

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Multicloud is sprouting Storage Silos

Grain Silos

We get an avalanche of multicloud selling from storage vendors. We get promises and benefits of multicloud but from whose point of view?

Multicloud is multiple premises

This is an overly simplistic example how I created 3 copies of the same spreadsheet yesterday. I have a quotation on Google Sheets. A fairly complicated one. Someone wanted it in Excel format, but the format and the formulas were all messed up when I tried to download it as XLSX. What I had to do was to download the Google Sheets as ODS (OpenDocument Spreadsheet) format to my laptop, and then upload the LibreOffice file to my OneDrive account, and use Excel Online to open the ODS file and saved as XLSX. In one fell swoop, I have the same spreadsheet in Google Drive, my laptop and OneDrive. 3 copies in 3 different premises. 

As we look to the behaviour of data creation and data acquisition, data sharing and data movement, the central repository is the gold image, the most relevant copy of the data. However, for business reasons, data has to be moved to where the applications are. It could be in cloud A or cloud B or cloud C or it could be on-premises. The processed output from cloud A is stored in cloud A, and likewise, cloud B in cloud B and so on.

To get the most significant and relevant copy, data from all premises must be consolidated, thus it has to be moved to a centralized data storage repository. But intercloud data movement is bogged down by egress fees, latency, data migration challenges (like formats and encoding), security, data clearance policies and many other hoops and hurdles.

With all these questions and concerns in mind, the big question mark is “Is multicloud really practical?” From a storage guy like me who loves a great data management story, “It is not. Multicloud creates storage silos“.

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Layers in Storage – For better or worse

Storage arrays and storage services are built upon by layers and layers beneath its architecture. The physical components of hard disk drives and solid states are abstracted into RAID volumes, virtualized into other storage constructs before they are exposed as shares/exports, LUNs or objects to the network.

Everyone in the storage networking industry, is cognizant of the layers and it is the foundation of knowledge and experience. The public cloud storage services side is the same, albeit more opaque. Nevertheless, both have layers.

In the early 2000s, SNIA® Technical Council outlined a blueprint of the SNIA® Shared Storage Model, a framework describing layers and properties of a storage system and its services. It was similar to the OSI 7-layer model for networking. The framework helped many industry professionals and practitioners shaped their understanding and the development of knowledge in their respective fields. The layering scheme of the SNIA® Shared Storage Model is shown below:

SNIA Shared Storage Model – The layering scheme

Storage vendors layering scheme

While SNIA® storage layers were generic and open, each storage vendor had their own proprietary implementation of storage layers. Some of these architectures are simple, but some, I find a bit too complex and convoluted.

Here is an example of the layers of the Automated Volume Management (AVM) architecture of the EMC® Celerra®.

EMC Celerra AVM Layering Scheme

I would often scratch my head about AVM. Disks were grouped into RAID groups, which are LUNs (Logical Unit Numbers). Then they were defined as Celerra® dvols (disk volumes), and stripes of the dvols were consolidated into a storage pool.

From the pool, a piece of a storage capacity construct, called a slice volume, were combined with other slice volumes into a metavolume which eventually was presented as a file system to the network and their respective NAS clients. Explaining this took an effort because I was the IP Storage product manager for EMC® between 2007 – 2009. It was a far cry from the simplicity of NetApp® ONTAP 7 architecture of RAID groups and volumes, and the WAFL® (Write Anywhere File Layout) filesystem.

Another complicated layered framework I often gripe about is Ceph. Here is a look of how the layers of CephFS is constructed.

Ceph Storage Layered Framework

I work with the OpenZFS filesystem a lot. It is something I am rather familiar with, and the layered structure of the ZFS filesystem is essentially simpler.

Storage architecture mixology

Engineers are bizarre when they get too creative. They have a can do attitude that transcends the boundaries of practicality sometimes, and boggles many minds. This is what happens when they have their own mixology ideas.

Recently I spoke to two magnanimous persons who had the idea of providing Ceph iSCSI LUNs to the ZFS filesystem in order to use the simplicity of NAS file sharing capabilities in TrueNAS® CORE. From their own words, Ceph NAS capabilities sucked. I had to draw their whole idea out in a Powerpoint and this is the architecture I got from the conversation.

There are 3 different storage subsystems here just to provide NAS. As if Ceph layers aren’t complicated enough, the iSCSI LUNs from Ceph are presented as Cinder volumes to the KVM hypervisor (or VMware® ESXi) through the Cinder driver. Cinder is the persistent storage volume subsystem of the Openstack® project. The Cinder volumes/hypervisor datastore are virtualized as vdisks to the respective VMs installed with TrueNAS® CORE and OpenZFS filesystem. From the TrueNAS® CORE, shares and exports are provisioned via the SMB and NFS protocols to Windows and Linux respectively.

It works! As I was told, it worked!

A.P.P.A.R.M.S.C. considerations

Continuing from the layered framework described above for NAS, other aspects beside the technical work have to be considered, even when it can work technically.

I often use a set of diligent data storage focal points when considering a good storage design and implementation. This is the A.P.P.A.R.M.S.C. Take for instance Protection as one of the points and snapshot is the technology to use.

Snapshots can be executed at the ZFS level on the TrueNAS® CORE subsystem. Snapshots can be trigged at the volume level in Openstack® subsystem and likewise, rbd snapshots at the Ceph subsystem. The question is, which snapshot at which storage subsystem is the most valuable to the operations and business? Do you run all 3 snapshots? How do you execute them in succession in a scheduled policy?

In terms of performance, can it truly maximize its potential? Can it churn out the best IOPS, and deliver at wire speed? What is the latency we can expect with so many layers from 3 different storage subsystems?

And supporting this said architecture would be a nightmare. Where do you even start the troubleshooting?

Those are just a few considerations and questions to think about when such a layered storage architecture along. IMHO, such a design was over-engineered. I was tempted to say “Just because you can, doesn’t mean you should

Elegance in Simplicity

Einstein (I think) quoted:

Einstein’s quote on simplicity and complexity

I am not saying that having too many layers is wrong. Having a heavily layered architecture works for many storage solutions out there, where they are often masked with a simple and intuitive UI. But in yours truly point of view, as a storage architecture enthusiast and connoisseur, there is beauty and elegance in simple designs.

The purpose here is to promote better understanding of the storage layers, and how they integrate and interact with each other to deliver the data services to the network. In the end, that is how most storage architectures are built.

 

Fueling the Flywheel of AWS Storage

It was bound to happen. It happened. AWS Storage is the Number 1 Storage Company.

The tell tale signs were there when Silicon Angle reported that AWS Storage revenue was around USD$6.5-7.0 billion last year and will reach USD$10 billion at the end of 2021. That news was just a month ago. Last week, IT Brand Pulse went a step further declaring AWS Storage the Number 1 in terms of revenue. Both have the numbers to back it up.

AWS Logo

How did it become that way? How did AWS Storage became numero uno?

Flywheel juggernaut

I became interested in the Flywheel concept some years back. It was conceived in Jim Collins’ book, “Good to Great” almost 20 years ago, and since then, Amazon.com has become the real life enactment of the Flywheel concept.

Amazon.com Flywheel – How each turn becomes sturdier, brawnier.

Every turn of the flywheel requires the same amount of effort although in the beginning, the noticeable effect is minuscule. But as every turn gains momentum, the returns of each turn scales greater and greater to the fixed efforts of operating a single turn.

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Storageless shan’t be thy name

Storageless??? What kind of a tech jargon is that???

This latest jargon irked me. Storage vendor NetApp® (through its acquisition of Spot) and Hammerspace, a metadata-driven storage agnostic orchestration technology company, have begun touting the “storageless” tech jargon in hope that it will become an industry buzzword. Once again, the hype cycle jargon junkies are hard at work.

Clear, empty storage containers

Clear, nondescript storage containers

It is obvious that the storageless jargon wants to ride on the hype of serverless computing, an abstraction method of computing resources where the allocation and the consumption of resources are defined by pieces of programmatic code of the running application. The “calling” of the underlying resources are based on the application’s code, and thus, rendering the computing resources invisible, insignificant and not sexy.

My stand

Among the 3 main infrastructure technology – compute, network, storage, storage technology is a bit of a science and a bit of dark magic. It is complex and that is what makes storage technology so beautiful. The constant innovation and technology advancement continue to make storage as a data services platform relentlessly interesting.

Cloud, Kubernetes and many data-as-a-service platforms require strong persistent storage. As defined by NIST Definition of Cloud Computing, the 4 of the 5 tenets – on-demand self-service, resource pooling, rapid elasticity, measured servicedemand storage to be abstracted. Therefore, I am all for abstraction of storage resources from the data services platform.

But the storageless jargon is doing a great disservice. It is not helping. It does not lend its weight glorifying the innovations of storage. In fact, IMHO, it felt like a weighted anchor sinking storage into the deepest depth, invisible, insignificant and not sexy. I am here dutifully to promote and evangelize storage innovations, and I am duly unimpressed with such a jargon.

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