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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When you buy storage solutions on price alone

Most people won’t bat an eye buying a car. It is a status symbol for many, but the value of the work returned from the car to the cost of buying the car is a great disparity. Furthermore, the price of the car depreciates quickly, making the “investment” more like an act of losing money fast.

So the story begins. When it comes to buying a storage technology platform, the initial price on the quote more or less decide the outcome. The reply of “Too expensive!” with little consideration about the returns of certain values relative to the initial buying price is far too frequent and plenty.

There has to be more considerations about these values. Here are in buying a storage technology platform besides just the initial price.

Performance

One recent conversation was about Intel® Optane™ vs NAND Flash. An well-known online eCommerce proprietor in South East Asia decided to go against the grain, and went for the more “expensive” Optane™ instead of the getting an array of NAND Flash NVMe SSDs.

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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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TrueNAS – The Secure Data Platform for EasiShare

The Enterprise File Sync and Share (EFSS) EasiShare presence is growing rapidly in the region, as enterprises and organizations are quickly redefining the boundaries of the new workspace. Work files and folders are no longer confined to the shared network drives within the local area network. It is going beyond to the “Work from Anywhere” phenomenon that is quickly becoming the way of life. Breaking away from the usual IT security protection creates a new challenge, but EasiShare was conceived with security baked into its DNA. With the recent release, Version 10, file sharing security and resiliency are stronger than ever.

[ Note: I have blogged about EasiShare previously. Check out the 2 links below ]

Public clouds are the obvious choice but for organizations to protect their work files, and keep data secure, services like Dropbox for Business, Microsoft® Office 365 with OneDrive and Google® Workspace are not exactly the kind of file sharing with security as their top priority. A case in point was the 13-hour disruption to Wasabi Cloud last week, where the public cloud storage provider’s domain name, wasabisys.com, was suspended by their domain name registrar because of malware discrepancy at one of its endpoints. There were other high profile cases too.

This is where EasiShare shines, because it is a secure, private EFSS solution for the enterprise and beyond, because business resiliency is in the hands and control of the organization that owns it, not the public cloud service providers.

EasiShare unifies with TrueNAS for secure business resiliency

EasiShare is just one several key business solutions iXsystems™ in Asia Pacific Japan is working closely with, and there is a strong, symbiotic integration with the TrueNAS® platform. Both have strong security features that fortify business resiliency, especially when facing the rampant ransomware scourge.

Value of a Single Unified Data Services Platform

A storage array is not a solution. It is just a box that most vendors push to sell. A storage must be a Data Services Platform. Readers of my blog would know that I have spoken about the Data Services Platform 3 years ago and you can read about it:

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Storage in a shiny multi-cloud space

The multi-cloud for infrastructure-as-a-service (IaaS) era is not here (yet). That is what the technology marketers want you to think. The hype, the vapourware, the frenzy. It is what they do. The same goes to technology analysts where they describe vision and futures, and the high level constructs and strategies to get there. The hype of multi-cloud is often thought of running applications and infrastructure services seamlessly in several public clouds such as Amazon AWS, Microsoft® Azure and Google Cloud Platform, and linking it to on-premises data centers and private clouds. Hybrid is the new black.

Multicloud connectivity to public cloud providers and on-premises private cloud

Multi-Cloud, on-premises, public and hybrid clouds

And the aspiration of multi-cloud is the right one, when it is truly ready. Gartner® wrote a high level article titled “Why Organizations Choose a Multicloud Strategy“. To take advantage of each individual cloud’s strengths and resiliency in respective geographies make good business sense, but there are many other considerations that cannot be an afterthought. In this blog, we look at a few of them from a data storage perspective.

In the beginning there was … 

For this storage dinosaur, data storage and compute have always coupled as one. In the mainframe DASD days. these 2 were together. Even with the rise of networking architectures and protocols, from IBM SNA, DECnet, Ethernet & TCP/IP, and Token Ring FC-SAN (sorry, this is just a joke), the SANs, the filers to the servers were close together, albeit with a network buffered layer.

A decade ago, when the public clouds started appearing, data storage and compute were mostly inseparable. There was demarcation of public clouds and private clouds. The notion of hybrid clouds meant public clouds and private clouds can intermix with on-premise computing and data storage but in almost all cases, this was confined to a single public cloud provider. Until these public cloud providers realized they were not able to entice the larger enterprises to move their IT out of their on-premises data centers to the cloud convincingly. So, these public cloud providers decided to reverse their strategy and peddled their cloud services back to on-prem. Today, Amazon AWS has Outposts; Microsoft® Azure has Arc; and Google Cloud Platform launched Anthos.

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