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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The young report card on Decentralized Storage

I kept this blog in my queue for over 4 months. I was reluctant to publish it because I thought the outrageous frenzies of NFTs (non-fungible tokens), metaverses and web3 were convoluting the discussions on the decentralized storage topic. 3 weeks back, a Google Trends search for these 3 opaque terms over 90 days showed that the worldwide fads were waning. Here was the Google Trends output on April 2, 2022:

Google Trends on NFT, metaverse and web3

Decentralized storage intrigues me. I like to believe in its potential and I often try to talk to people to strengthen the narratives, and support its adoption where it fits. But often, the real objectives of decentralized storage are obfuscated by the polarized conversations about cryptocurrencies that are pegged to their offerings, NFTs (non-fungible tokens), DAOs (decentralized autonomous organizations) and plenty of hyperboles with bewildering facts as well.

But I continue to seek sustainable conversations about decentralized storage without the sway of the NFTs or the cryptos. After dipping in my toes and experiencing with HODLers, and looking at the return to sanity, I believe we can discuss decentralized storage with better clarity now. The context is to position decentralized storage to the mainstream, specifically to business organizations already immersed in centralized storage. Here is my fledgling report card on decentralized storage.

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Backup – Lest we forget

World Backup Day – March 31st

Last week was World Backup Day. It is on March 31st every year so that you don’t lose your data and become an April’s Fool the next day.

Amidst the growing awareness of the importance of backup, no thanks to the ever growing destructive nature of ransomware, it is important to look into other aspects of data protection – both a data backup/recovery and a data security –  point of view as well.

3-2-1 Rule, A-B-C and Air Gaps

I highlighted the basic 3-2-1 rule before. This must always be paired with a set of practised processes and policies to cultivate all stakeholders (aka the people) in the organization to understand the importance of protecting the data and ensuring data recoverability.

The A-B-C is to look at the production dataset and decide if the data should be stored in the Tier 1 storage. In most cases, the data becomes less active and these datasets may be good candidates to be archived. Once archived, the production dataset is smaller and data backup operations become lighter, faster and have positive causation as well.

Air gaps have returned to prominence since the heightened threats on data in recent years. The threats have pushed organizations to consider doing data offsite and offline with air gaps. Cost considerations and speed of recovery can be of concerns, and logical air gaps are also gaining style as an acceptable extra layer of data. protection.

Backup is not total Data Protection cyberdefence

If we view data protection more holistically and comprehensively, backup (and recovery) is not the total data protection solution. We must ignore the fancy rhetorics of the technology marketers that backup is the solution to ensure data protection because there is much more than that.

The well respected NIST (National Institute of Standards and Technology) Cybersecurity Framework places Recovery (along with backup) as the last pillar of its framework.

NIST Cybersecurity Framework

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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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Time to Conflate Storage with Data Services

Around the year 2016, I started to put together a better structure to explain storage infrastructure. I started using the word Data Services Platform before what it is today. And I formed a pictorial scaffold to depict what I wanted to share. This was what I made at that time.

Data Services Platform (circa 2016)- Copyright Heoh Chin Fah

One of the reasons I am bringing this up again is many of the end users and resellers still look at storage from the perspective of capacity, performance and price. And as if two plus two equals five, many storage pre-sales and architects reciprocate with the same type of responses that led to the deteriorated views of the storage technology infrastructure industry as a whole. This situation irks me. A lot.

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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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How well do you know your data and the storage platform that processes the data

Last week was consumed by many conversations on this topic. I was quite jaded, really. Unfortunately many still take a very simplistic view of all the storage technology, or should I say over-marketing of the storage technology. So much so that the end users make incredible assumptions of the benefits of a storage array or software defined storage platform or even cloud storage. And too often caveats of turning on a feature and tuning a configuration to the max are discarded or neglected. Regards for good storage and data management best practices? What’s that?

I share some of my thoughts handling conversations like these and try to set the right expectations rather than overhype a feature or a function in the data storage services.

Complex data networks and the storage services that serve it

I/O Characteristics

Applications and workloads (A&W) read and write from the data storage services platforms. These could be local DAS (direct access storage), network storage arrays in SAN and NAS, and now objects, or from cloud storage services. Regardless of structured or unstructured data, different A&Ws have different behavioural I/O patterns in accessing data from storage. Therefore storage has to be configured at best to match these patterns, so that it can perform optimally for these A&Ws. Without going into deep details, here are a few to think about:

  • Random and Sequential patterns
  • Block sizes of these A&Ws ranging from typically 4K to 1024K.
  • Causal effects of synchronous and asynchronous I/Os to and from the storage

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At the mercy of the cloud deity

Amazon Web Services (AWS) went down in the middle of last week. News of the outage were mentioned:

AWS Management Console unavailable error

Piling the misery

The AWS outage headlines attract the naysayers, the fickle armchair pundits, and the opportunists. Here are a few news articles that bring these folks to chastise the cloud giant.

Of course, I am one of these critics. I don’t deny that I am not. But I read this situation from a multicloud hyperbole of which I am not a fan. Too much multicloud whitewashing by vendors trying to pitch multicloud as a disaster recovery solution without understanding that this is easier said than done.

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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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