Proxmox storage with TrueNAS iSCSI volumes

A few weeks ago, I decided to wipe clean my entire lab setup running Proxmox 6.2. I wanted to connect the latest version of Proxmox VE 8.0-2 using iSCSI LUNs from the TrueNAS® system I have with me. I thought it would be fun to have the configuration steps and the process documented. This is my journal on how to provision a TrueNAS® CORE iSCSI LUN to Proxmox storage. This iSCSI volume in Proxmox is where the VMs will be installed into.

Here is a simplified network diagram of my setup but it will be expanded to a Proxmox cluster in the future with the shared storage.

Proxmox and TrueNAS network setup

Preparing the iSCSI LUN provisioning

The iSCSI LUN (logical unit number) is provisioned as a logical disk volume to the Proxmox node, where the initiator-target relationship and connection are established.

This part assumes that a zvol has been created from the zpool. At the same time, the IQN (iSCSI Qualified Name) should be known to the TrueNAS® storage as it establishes the connection between Proxmox (iSCSI initiator) and TrueNAS (iSCSI target).

The IQN for Proxmox can be found by viewing the content of the /etc/iscsi/initiatorname.iscsi within the Proxmox shell as shown in the screenshot below.

Where to find the Proxmox iSCSI IQN

The green box shows the IQN number of the Proxmox node that starts with iqn.year-month.com.domain:generated-hostname. This will be used during the iSCSI target portal configuration in the TrueNAS® webGUI.

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Disaggregation and Composability vital for AI/DL models to scale

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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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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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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Storage Elephant Compute Birds

Data movement is expensive. Not just costs, but also latency and resources as well. Thus there were many narratives to move compute closer to where the data is stored because moving compute is definitely more economical than moving data. I borrowed the analogy of the 2 animals from some old NetApp® slides which depicted storage as the elephant, and compute as birds. It was the perfect analogy, because the storage is heavy and compute is light.

“Close up of a white Great Egret perching on top of an African Elephant aa Amboseli national park, Kenya”

Before the animals representation came about I used to use the term “Data locality, Data Mobility“, because of past work on storage technology in the Oil & Gas subsurface data management pipeline.

Take stock of your data movement

I had recent conversations with an end user who has been paying a lot of dollars keeping their “backup” and “archive” in AWS Glacier. The S3 storage is cheap enough to hold several petabytes of data for years, because the IT folks said that the data in AWS Glacier are for “backup” and “archive”. I put both words in quotes because they were termed as “backup” and “archive” because of their enterprise practice. However, the face of their business is changing. They are in manufacturing, oil and gas downstream, and the definitions of “backup” and “archive” data has changed.

For one, there is a strong demand for reusing the past data for various reasons and these datasets have to be recalled from their cloud storage. Secondly, their data movement activities still mimicked what they did in the past during their enterprise storage days. It was a classic lift-and-shift when they moved to the cloud, and not taking stock of  their data movements and the operations they ran on these datasets. Still ongoing, their monthly AWS cost a bomb.

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Relinquishing Freedom in our Digital Future

There was a TV cartoon show I loved when I was a kid called “Wait till your Father gets home“. I was probably 5 or 6 then, but I can still remember the mother was practically nagging all the time of having the father to come back to deal with the problems and issues caused by the kids, and sometimes the dog.

This patriarchal mentality of having the male manning (yeah, it is not a gender neutral word) the household is also, unfortunately, mimicked in our societies, in general, being obedient and subservient to the government of the day. This is especially true in East Asian societies, .

While dissent of this mindset is sprouting in the younger generation of these societies, you can see the dichotomy of the older generation and the younger one in the recent protests in Thailand and the on-going one in Myanmar. The older generation is likely fearful of the consequences and there are strong inclinations to accept and subject their freedom to be ruled by the rulers of the day. It is almost like part of their psyche and DNA.

So when I read the article published by Data Storage Asean titled “Malaysians Optimistic on Giving the Government Increased Access to Personal Data for Better Services“, I was in two minds. Why are we giving away our Personal Data when we do not get a guarantee that the our privacy is protected?

Data Privacy should be in our own hands

Why are we giving away our freedom in new digital Malaysia when in history, we have not been truly protected of that freedom? 

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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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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.

 

A Paean to NFS

It is certainly encouraging to see both NAS protocols, NFS and SMB, featured well in the latest VMware® vSAN 7 Update 1 release. The NFS v3 and v4.1 support was already in vSAN 7.0 when it was earlier announced as part of its Native File Services for vSAN. But some years ago, NFS was not always the primary storage protocol of choice. SAN protocols, Fibre Channel and iSCSI, were almost always designated to serve enterprise applications. At the client side, Windows became prominent, and the SMB/CIFS protocol dominated the landscape of the desktop. This further pushed NFS into the back closet.

NFS or Network File System has its naysayers. The venerable, but often maligned distributed network file protocol is 36 years today. In storage vendors such as NetApp®, VAST Data, Pure Storage FlashBlade, and Dell EMC Isilon, NFS is still positioned as the primary file protocol for manufacturing testers on the shop floor, EDA/eCAD applications, seismic and subsurface applications in Oil & Gas and many more. In another development, just like its presence in the vSAN Native Services,, NFS has also quietly embedded itself into many storage platforms to serve the data platform services within the respective framework itself.

And I have experienced NFS from the client side to the enterprise applications and more, and I take this opportunity to pay tribute.

NFS (Network File System) client server network

NFS (Network File System) client server network

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The prudence needed for storage technology companies

Blitzscaling has been on my mind a lot. Ever since I discovered that word a while back, it has returned time and time again to fill my thoughts. In the wake of COVID-19, and in the mire of this devastating pandemic, is blitzscaling still the right strategy for this generation of storage technology, hyperconverged, data management and cloud storage startups?

What the heck is Blitzscaling? 

For the uninformed, here’s a video of Reid Hoffman, co-founder of Linked and a member of the Paypal mafia, explaining Blitzscaling.

Blitzscaling is about hyper growing, scaling ultra fast and rocketing to escape velocity, at the expense of things like management efficiency, financial prudence, profits and others. While this blog focuses on storage companies, blitzscaling is probably most recognizable in the massive expansion of Uber (and contraction) a few years ago. In the US, the ride hailing war is between Uber and Lyft, but over here in South East Asia, just a few years back, it was between Uber and Grab. In China it was Uber and Didi.

From the storage angle, 2 segments exemplified the blitzscaling culture between 2015 and 2020.

  • All Flash Startups
  • Hyper Converged Infrastructure Startups

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