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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OpenZFS with Object Storage

At AWS re:Invent last week, Amazon Web Services announced Amazon FSx for OpenZFS. This is the 4th managed service under the Amazon FSx umbrella, joining NetApp® ONTAP™, Lustre and Windows File Server. The highly scalable OpenZFS filesystem can provide high throughput and IOPS bandwidth to Amazon EC2, ECS, EKS and VMware® Cloud on AWS.

I am assuming the AWS OpenZFS uses EBS as the block storage backend, given the announcement that it can deliver 4GB/sec of throughput and 160,000 IOPS from the “drives” without caching. How the OpenZFS is provisioned to the AWS clients is well documented in this blog here. It is an absolutely joy (for me) to see the open source OpenZFS filesystem getting the validation and recognization from AWS. This is one hell of a filesystem.

But this blog isn’t about AWS FSx for OpenZFS with block storage. It is about what is coming, and eventually AWS FSx for OpenZFS could expand into AWS’s proficient S3 storage as well.  Can OpenZFS integrate with an S3 object storage backend? This blog looks into the burning question.

In the recently concluded OpenZFS Developer Summit 2021, one of the topics was “ZFS on Object Storage“, and the short answer is a resounding YES!

OpenZFS Developer Summit 2021

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Open Source Storage Technology Crafters

The conversation often starts with a challenge. “What’s so great about open source storage technology?

For the casual end users of storage systems, regardless of SAN (definitely not Fibre Channel) or NAS on-premises, or getting “files” from the personal cloud storage like Dropbox, OneDrive et al., there is a strong presumption that open source storage technology is cheap and flaky. This is not helped with the diet of consumer brands of NAS in the market, where the price is cheap, but the storage offering with capabilities, reliability and performance are found to be wanting. Thus this notion floats its way to the business and enterprise users, and often ended up with a negative perception of open source storage technology.

Highway Signpost with Open Source wording

Storage Assemblers

Anybody can “build” a storage system with open source storage software. Put the software together with any commodity x86 server, and it can function with the basic storage services. Most open source storage software can do the job pretty well. However, once the completed storage technology is put together, can it do the job well enough to serve a business critical end user? I have plenty of sob stories from end users I have spoken to in these many years in the industry related to so-called “enterprise” storage vendors. I wrote a few blogs in the past that related to these sad situations:

We have such storage offerings rigged with cybersecurity risks and holes too. In a recent Unit 42 report, 250,000 NAS devices are vulnerable and exposed to the public Internet. The brands in question are mentioned in the report.

I would categorize these as storage assemblers.

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Windows SMB synchronous writes with OpenZFS

Sometimes I get really pissed off with myself because I have taken a bigoted view, and ended up with eggs on my face. The past week was like that, and the problem was gnawing me on the inside all week, because I was determined to balance my equilibrium by finding the answer.

Early in the week, I was having a conversation with a potential customer. It evolved around the missing 10 seconds or so of the video footage between the users of a popular video editing software. The company had 70% Windows users, and 30% users on the Mac, both sides accessing the NAS device. The issue was the editors on the Windows side will store the raw and edited files to the NAS, but when the Mac users read them, they will often find 10 seconds or so of the stored video files missing.

The likeliest culprit of this problem is the way the SMB protocol write I/O behaves in Windows and in MacOS. Windows SMB, by default, writes I/O asynchronously while SMB on MacOS writes I/O synchronously.

I had a strong conviction I had the answer to this issue but this was not a TrueNAS®, It was another brand of NAS that I did not have knowledge of, and so, I left the conversation feeling quite embarrassed because I had the answer only on the TrueNAS® server side, not on the Windows client side. Bigotry blinded me. Hmmph! 

SMB (Server Message Block) client-server model

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RAIDZ expansion and dRAID excellent OpenZFS adventure

RAID (Redundant Array of Independent Disks) is the foundation of almost every enterprise storage array in existence. Thus a technology change to a RAID implementation is a big deal. In recent weeks, we have witnessed not one, but two seismic development updates to the volume management RAID subsystem of the OpenZFS open source storage platform.

OpenZFS logo

For the uninformed, ZFS is one of the rarities in the storage industry which combines the volume manager and the file system as one. Unlike traditional volume management, ZFS merges both the physical data storage representations (eg. Hard Disk Drives, Solid State Drives) and the logical data structures (eg. RAID stripe, mirror, Z1, Z2, Z3) together with a highly reliable file system that scales. For a storage practitioner like me, working with ZFS is that there is always a “I get it!” moment every time, because the beauty is there are both elegances of power and simplicity rolled into one.

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Setting up Nextcloud on FreeNAS Part 1

I have started to enhance the work that I did last weekend with Nextcloud on FreeNAS™. I promised to share the innards of my work but first I have to set the right expectations for the readers. This blog is just a documentation of the early work I have been doing to get Nextcloud on FreeNAS™ off the ground quickly. Also there are far better blogs than mine on the Nextcloud topic.

Note:

Nextcloud 17 (latest version is version 21)

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Encryption Key Management in TrueNAS

iXsystems™ TrueNAS® has moved up a notch when it comes to encrypting data structures in the storage . In additional to supporting self encrypting disks (SEDs) and zpool encryption, version 12.0 added dataset and zvol encryption as well.

The world has become a dangerous place. The security hacks, the data leaks, the ransomware scourge have dominated the IT news in 2021, and we are only 3 months into the year. These cybersecurity threats are about to get worse and we have to be vigilant to deescalate the impacts of these threats. As such, TrueNAS® Enterprise has progressed forward to protect the data structures in its storage arrays, in addition to many other security features depicted below:

TrueNAS Multilayer Security

Key Management Interoperability Protocol (KMIP)

One of the prominent cybersecurity features in TrueNAS® Enterprise is KMIP support in version 12.0.

What is KMIP? KMIP is a client-server framework for encryption key management. It is a standard released in 2010 and governed by OASIS Open. OASIS stands for Organization for the Advancement of Structured Information Standards.

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A FreeNAS Compression Tale

David vs Goliath Credit: Miguel Robledo of https://www.artstation.com/miguel_robledo

David vs Goliath

It was an underdog tale worthy of the biblical book of Samuel. When I first caught wind of how FreeNAS™ compression prowess was going against NetApp® compression and deduplication in one use case, I had to find out more. And the results in this use case was quite impressive considering that FreeNAS™ (now known as TrueNAS® CORE) is the free, open source storage operating system and NetApp® Data ONTAP, is the industry leading, enterprise, “king of the hill” storage data management software.

Certainly a David vs Goliath story.

Compression in FreeNAS

Ah, Compression! That technology that is often hidden, hardly seen and often forgotten.

Compression is a feature within FreeNAS™ that seldom gets the attention. It works, and certainly is a mature form of data footprint reduction (DFR) technology, along with data deduplication. It is switched on by default, and is the setting when creating a dataset, as shown below:

Dataset creation with Compression (lz4) turned on

The default compression algorithm is lz4 which is fast but poor in compression ratio compared to gzip and bzip2. However, lz4 uses less CPU cycles to perform its compression and decompression processing, and thus the impact on FreeNAS™ and TrueNAS® is very low.

NetApp® ONTAP, if I am not wrong, uses lzopro as default – a commercial and optimized version of the open source LZO compression library. In addition, NetApp also has their data deduplication technology as well, something OpenZFS has to improve upon in the future.

The DFR report

This brings us to the use case at one of iXsystems™ customers in Taiwan. The data to be reduced are mostly log files at the end user, and the version of FreeNAS™ is 11.2u7. There are, of course, many factors that affect the data reduction ratio, but in this case of 4 scenarios,  the end user has been running this in production for over 2 months. The results:

FreeNAS vs NetApp Data Footprint Reduction

In 2 of the 4 scenarios, FreeNAS™ performed admirably with just the default lz4 compression alone, compared to NetApp® which was running both their inline compression and deduplication.

The intention to post this report is not to show that FreeNAS™ is better in every case. It won’t be, and there are superior data footprint reduction tech out there which can outperform it. But I would expect potential and existing end users to leverage on the compression capability of FreeNAS™ which is getting better all the time.

A better compression algorithm

Followers of OpenZFS are aware of the changing of times with OpenZFS version 2.0. One exciting update is the introduction of the zstd compression algorithm into OpenZFS late last year, and is already in TrueNAS® CORE and Enterprise version 12.x.

What is zstd? zstd is a fast compression algorithm that aims to be as efficient (or better) than gzip, but with better speed closer to lz4, relatively. For a long time, the gzip compression algorithm, from levels 1-9, has been serving very good compression ratio compared to many compression algorithms, lz4 included.

However, the efficiency came at a higher processing price and thus took a longer time. At the other end, lz4 is fast and lightweight, but its reduction ratio efficiency is very poor. zstd intends to be the in-between of gzip and lz4. In the latest results published by Facebook’s github page,

zstd performance benchmark against other compression algorithms

For comparison, zstd (level -1) performed very well against zlib, the data compression library in gzip. It was made known there are 22 levels of compression in zstd but I do not know how many levels are accepted in the OpenZFS development.

At the same time, compression takes advantage of multi-core processing, and actually can speed up disk I/O response because the original dataset to be processed is smaller after the compression reduction.

While TrueNAS® still defaults lz4 compression as of now, you can probably change the default compression with a command

# zfs set compression=zstd-6 pool/dataset

Your choice

TrueNAS® and FreeNAS™ support multiple compression algorithms. lz4, gzip and now zstd. That gives the administrator a choice to assign the right compression algorithm based on processing power, storage savings, and time to get the best out of the data stored in the datasets.

As far as the David vs Goliath tale goes, this real life use case was indeed a good one to share.

 

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.